Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi
e-ISSN: 2685-0893
Pengembangan Model Random Forest Regressor untuk Prediksi Kelembaban pada Pertanian Perkotaan Berkelanjutan
Agriculture is a sector that supports food security. Currently, agriculture faces serious challenges due to climate change, land limitations, and low technology adoption. This study aims to develop an Internet of Things (IoT)-based smart farming system integrated with artificial intelligence and run through edge computing. The prototype system is designed to collect real-time data on crop growth environments using pH, TDS, temperature, humidity, and water level sensors. The data is then processed locally using the Random Forest Regressor algorithm to determine optimal environmental conditions. Test results show that the model has very high accuracy in predicting humidity (R² = 0.99; RMSE = 0.65) and temperature (R² = 0.99; RMSE = 0.17), although there are still discrepancies in extreme conditions. The integration of IoT, AI, and edge computing has proven to improve energy efficiency, accelerate response times, and provide adaptive and affordable solutions in support of sustainable urban agriculture productivity. Keywords: Artificial Intelligence; Random Forest Regressor; IoT; Edge Computing Abstrak Pertanian merupakan sektor yang mendukung ketahanan pangan, saat ini pertanian menghadapi tantangan serius akibat perubahan iklim, keterbatasan lahan, dan rendahnya adopsi teknologi. Penelitian ini bertujuan mengembangkan sistem pertanian cerdas berbasis Internet of Things (IoT) yang terintegrasi dengan kecerdasan buatan dan dijalankan melalui komputasi tepi. Prototipe sistem dirancang untuk mengumpulkan data lingkungan pertumbuhan tanaman secara real-time menggunakan sensor pH, TDS, suhu, kelembaban, dan tinggi permukaan air. Data kemudian diproses secara lokal menggunakan algoritma Random Forest Regressor untuk menentukan kondisi lingkungan optimal. Hasil pengujian menunjukkan model memiliki akurasi sangat tinggi pada prediksi kelembaban (R² = 0,99; RMSE = 0,65) dan suhu (R² = 0,99; RMSE = 0,17), meskipun masih terdapat selisih pada kondisi ekstrem. Integrasi IoT, AI, dan edge computing terbukti mampu meningkatkan efisiensi energi, mempercepat respons, serta memberikan solusi adaptif dan terjangkau dalam mendukung produktivitas pertanian perkotaan berkelanjutan.
Copyright (c) 2025 Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi
Prediksi Pergerakan Harga Saham Bank Mandiri Menggunakan Metode Support Vector Regression dan Algoritma Grid Search
The volatile nature of stock price movements poses a major challenge for investors in making accurate investment decisions. This study aims to predict the stock price movement of PT. Bank Mandiri (Persero) Tbk [BMRI] using Support Vector Regression (SVR) optimized through the Grid Search algorithm. The dataset consists of daily stock prices from August 2020 to August 2025, including open, high, low, close, adjusted close, and trading volume. The research process involves data collection, preprocessing (cleaning, feature selection, normalization), splitting into training and testing sets, parameter optimization using Grid Search with Leave-One-Out Cross Validation (LOOCV), model training, and evaluation with R², MSE, and RMSE. The results show that the SVR model with a linear kernel, C = 1 and epsilon = 0.01, achieved the best performance, with high accuracy (R² = 0.9991 on training data and R² = 0.9976 on testing data). These findings confirm the effectiveness of Grid Search–based SVR in predicting stock prices and supporting investment decision-making. Keywords: Stock Price Prediction; Support Vector Regression; Grid Search; Bank Mandiri Abstrak Pergerakan harga saham yang fluktuatif menjadi tantangan utama bagi investor dalam menentukan strategi investasi yang tepat. Penelitian ini bertujuan memprediksi pergerakan harga saham PT. Bank Mandiri (Persero) Tbk [BMRI] dengan metode Support Vector Regression (SVR) yang dioptimalkan menggunakan algoritma Grid Search. Data yang digunakan berupa harga saham harian periode Agustus 2020–Agustus 2025, mencakup variabel open, high, low, close, adjusted close, dan volume. Tahapan penelitian meliputi pengumpulan data, pra-pemrosesan (pembersihan, seleksi fitur, normalisasi), pembagian data latih dan uji, optimasi parameter dengan Grid Search berbasis Leave-One-Out Cross Validation (LOOCV), pelatihan model, serta evaluasi dengan R², MSE, dan RMSE. Hasil penelitian menunjukkan SVR dengan kernel linear, parameter C = 1 dan epsilon = 0,01 memberikan performa terbaik dengan akurasi tinggi (R² = 0,9991 pada data latih dan R² = 0,9976 pada data uji). Temuan ini menegaskan efektivitas SVR berbasis Grid Search dalam memprediksi harga saham dan mendukung pengambilan keputusan investasi.
Analisis Kinerja Algoritma SVM dan Naïve Bayes untuk Klasifikasi Sentimen Program Makan Gratis
The development of social media facilitates the massive dissemination of public opinion, including towards the government’s free meal program. The high volume of comments makes manual analysis inefficient, thus requiring technological approaches such as sentiment analysis for automatic opinion classification. This study focuses on comparing the performance of the SVM (Support Vector Machine) and Naïve Bayes algorithms in classifying public sentiment collected from X social media data. The research method includes data crawling, preprocessing with Natural Language Processing (NLP), and classification using both algorithms. Testing results on an imbalanced dataset show that SVM is the best model with 96% accuracy and an F1-score of 0.48 for the minority (negative) class, significantly outperforming Naïve Bayes variants which tend to predict the majority class. The findings demonstrate that the SVM algorithm has higher reliability in sentiment classification on datasets with imbalanced class distribution. Keywords: Sentiment Analysis; Support Vector Machines; Naive Bayes; Free Lunch Program; Text Classification Abstrak Perkembangan media sosial memfasilitasi penyampaian opini publik secara masif, termasuk terhadap program makan gratis pemerintah. Volume komentar yang tinggi menjadikan analisis manual tidak efisien, sehingga memerlukan pendekatan teknologi seperti analisis sentimen untuk klasifikasi opini otomatis. Penelitian ini berfokus pada perbandingan performa algoritma SVM (Support Vector Machine) dan Naïve Bayes dalam mengklasifikasikan sentimen masyarakat yang diambil dari data media sosial X. Metode penelitian mencakup pengumpulan data crawling, pra-pemrosesan dengan Natural Language Processing (NLP), hingga klasifikasi menggunakan kedua algoritma. Hasil pengujian pada dataset yang tidak seimbang menunjukkan bahwa SVM merupakan model terbaik dengan akurasi 96% dan nilai F1-score 0.48 pada kelas minoritas (negatif), secara signifikan mengungguli varian Algoritma Naïve Bayes sering kali lebih condong memprediksi pada kelas mayoritas. Hasil penelitian ini membuktikan bahwa algoritma SVM memiliki keandalan lebih tinggi dalam klasifikasi sentimen pada dataset dengan distribusi kelas yang tidak seimbang.
Model Pembeda Sampah Organik dan Anorganik dengan Machine Learning berbasis Phyton
This research developed an artificial intelligence-based system to differentiate between organic and inorganic waste using a Convolutional Neural Network (CNN) model. The problem addressed is the community's limited understanding of how to properly separate types of waste, which contributes to environmental pollution. The methodology employed includes data collection of waste images, training the CNN model, and system testing. The test results showed that the model achieved an accuracy of 75%, with a precision of 78% and a recall of 70%. These findings suggest that the developed system can help the community better understand and separate waste more effectively. This research makes a positive contribution to waste management and is expected to serve as a foundation for further development in waste classification technology. Keywords: Artificial intelligence; Convolutional Neural Network; Waste separation; Environmental management; Machine learning Abstrak Penelitian ini mengembangkan sistem berbasis kecerdasan buatan untuk membedakan sampah organik dan anorganik menggunakan model Convolutional Neural Network (CNN). Permasalahan yang dihadapi adalah rendahnya pemahaman masyarakat dalam memisahkan jenis sampah, yang berdampak pada pencemaran lingkungan. Metodologi yang digunakan meliputi pengumpulan data gambar sampah, pelatihan model CNN, dan pengujian sistem. Hasil pengujian menunjukkan bahwa model mencapai akurasi 75%, dengan presisi 78% dan recall 70%. Temuan ini menunjukkan bahwa sistem yang dikembangkan dapat membantu masyarakat dalam memahami dan memisahkan sampah dengan lebih baik. Penelitian ini memberikan kontribusi positif terhadap pengelolaan sampah dan diharapkan dapat menjadi dasar untuk pengembangan lebih lanjut dalam teknologi klasifikasi sampah.
Pengembangan Model Deep Learning dengan Slang-Aware Embeddings untuk Deteksi Promosi Judi Online
Online gambling promotions on social media platforms such as YouTube often employ slang or non-standard language to evade traditional moderation systems, increasing the spread of illegal content in Indonesia. This study aims to develop a hybrid deep learning model combining BERT and LSTM to accurately detect online gambling promotions. Data were collected from YouTube comments through a web scraping process, followed by text cleaning, labeling, and normalization using a semi-automatic slang dictionary. The model was trained with slang-aware embeddings to capture informal language context. Evaluation was conducted using precision, recall, F1-score, and confusion matrix metrics. The results show an accuracy of 96% with an F1-score of 0.96, indicating a strong balance between precision and recall. These findings demonstrate the effectiveness of the proposed hybrid approach in automatically detecting online gambling promotional content. Kata kunci: Online Gambling Detection; Deep Learning; NLP; Slang-Aware Embeddings; BERT-LTSM Abstrak Promosi judi daring di media sosial seperti YouTube sering menggunakan bahasa tidak baku atau slang untuk menghindari deteksi sistem moderasi. Kondisi ini berpotensi meningkatkan penyebaran konten ilegal di Indonesia. Penelitian ini bertujuan mengembangkan model deep learning hibrida yang mengombinasikan BERT dan LSTM guna mendeteksi promosi judi daring secara lebih akurat. Data dikumpulkan dari komentar YouTube melalui proses web scraping, kemudian diproses melalui tahap pembersihan teks, pelabelan, dan normalisasi menggunakan kamus slang semi-otomatis. Model dilatih dengan slang-aware embeddings untuk menangkap konteks bahasa tidak resmi. Pengujian dilakukan menggunakan metrik precision, recall, F1-score, dan confusion matrix. Hasil menunjukkan akurasi sebesar 96% dengan nilai F1-score 0,96, menandakan keseimbangan tinggi antara presisi dan sensitivitas model. Temuan ini membuktikan efektivitas pendekatan hibrida dalam mendeteksi konten promosi judi daring secara otomatis.
Model Penerimaan Sistem E-purchasing: Analisis Peran Kepercayaan dan Keamanan Pengguna
E-purchasing System Acceptance Model: Analysis of the Role of User Trust and Security. The adoption of local Business-to-Government (B2G) E-purchasing platforms faces challenges, as indicated by a decline in new user registrations. This study aims to analyze the influence of User Trust and Perceived Security on the Behavioral Intention to Use the Parto.id platform, extending the Technology Acceptance Model (TAM). This quantitative study surveyed 100 seller partners in Jambi City. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that Perceived Usefulness and User Trust significantly and positively influence Behavioral Intention to Use. However, Perceived Security was found to have no significant direct effect on user intention. The results highlight that User Trust is a more crucial determinant than Perceived Security in the adoption of B2G E-purchasing systems, suggesting that security is considered a standard prerequisite. Platform providers should prioritize trust-building initiatives to enhance user adoption. Keywords: Technology Acceptance Model; User Trust; Perceived Security; E-purchasing; B2G System. Abstrak Model Penerimaan Sistem E-purchasing: Analisis Peran Kepercayaan dan Keamanan Pengguna. Adopsi platform E-purchasing lokal Business-to-Government (B2G) menghadapi tantangan yang ditunjukkan dengan adanya penurunan jumlah pendaftar pengguna baru. Penelitian ini bertujuan untuk menganalisis pengaruh kepercayaan pengguna dan persepsi keamanan terhadap niat perilaku untuk menggunakan platform Parto.id dengan memperluas Technology Acceptance Model (TAM). Penelitian kuantitatif ini menggunakan survei terhadap 100 mitra penjual di Kota Jambi. Data dianalisis menggunakan Partial Least Squares Structural Equation Modeling (PLS-SEM). Hasil penelitian menunjukkan bahwa persepsi kemanfaatan dan kepercayaan pengguna berpengaruh positif dan signifikan terhadap niat perilaku untuk menggunakan. Namun, persepsi keamanan ditemukan tidak memiliki pengaruh langsung yang signifikan terhadap niat pengguna. Hasil ini menyoroti bahwa kepercayaan pengguna merupakan faktor penentu yang lebih krusial dibandingkan persepsi keamanan dalam adopsi sistem E-purchasing B2G, yang mengindikasikan bahwa keamanan dianggap sebagai prasyarat standar. Penyedia platform harus memprioritaskan inisiatif pembangunan kepercayaan untuk meningkatkan adopsi pengguna.
Penerapan Metode SAW Pada Sistem Pendukung Keputusan Penentuan Perangkat Lunak Anti Virus
The increasing dependence of society on computers and the internet highlights the urgency of protecting data and privacy from cyber threats. Antivirus software is one of the common solutions; however, the abundance of options, each with its own advantages and disadvantages, often makes it difficult for users to select the most suitable one. This study aims to assist users in choosing the best free antivirus through a systematic approach using a decision support system. The method applied is Simple Additive Weighting (SAW) with five evaluation criteria: scanning speed, detection capability, rating, resource optimization, and available features. Five antivirus software were tested as alternatives, namely Windows Security, Avira, Avast, Bitdefender, and Kaspersky. The testing and calculation results indicate that Windows Security ranked the highest with a vector value of 0.257, due to its high detection rate, fast scanning performance, good rating, and sufficient features. Therefore, the SAW method proves effective in providing objective and systematic recommendations for selecting the best antivirus software. Keywords: Decision support system; Simple additive weighting; Antivirus Abstrak Meningkatnya ketergantungan masyarakat terhadap sistem komputer dan internet menimbulkan urgensi akan perlindungan data dan privasi dari ancaman siber. Salah satu solusi yang umum digunakan adalah perangkat lunak antivirus, namun banyaknya pilihan dengan kelebihan dan kekurangan masing-masing seringkali menimbulkan kebingungan dalam menentukan pilihan yang tepat. Penelitian ini bertujuan untuk membantu pengguna dalam memilih antivirus gratis terbaik dengan pendekatan sistematis melalui sistem pendukung keputusan. Metode yang digunakan adalah Simple Additive Weighting (SAW) dengan lima kriteria penilaian, yaitu kecepatan pemindaian, kemampuan deteksi, rating, optimasi sumber daya, dan jumlah fitur. Lima perangkat lunak antivirus diuji sebagai alternatif, yakni Windows Security, Avira, Avast, Bitdefender, dan Kaspersky. Hasil pengujian dan perhitungan menunjukkan bahwa Windows Security memperoleh peringkat tertinggi dengan nilai vektor 0,257 karena memiliki kecepatan dan tingkat deteksi yang tinggi, rating yang baik, serta fitur yang cukup banyak. Dengan demikian, metode SAW terbukti efektif dalam memberikan rekomendasi obyektif dan sistematis untuk pemilihan perangkat lunak antivirus terbaik.
Optimalisasi Proses Penjualan dan Pengecekan Stok Pada Toko Mozza Aquatic Menggunakan BPMN
An efficient sales process and stock checking are crucial components in maintaining smooth operations and customer satisfaction, especially for MSMEs such as Toko Mozza Aquatic. This research aims to redesign these two main processes using the Business Process Model and Notation (BPMN) approach. This study involves comprehensive business flow analysis, throughput efficiency evaluation, and identification of information technology-based solutions. The research results show that the new system design, which digitally integrates sales and inventory interfaces, is able to improve process structure, reduce service time, and minimize manual errors. Features such as product search, transaction tracking, stock availability indicators also support more responsive and accurate decision making. These findings confirm that the implementation of BPMN accompanied by digitalization and HR training is an effective strategy in increasing the efficiency and competitiveness of MSMEs amidst competitive market dynamics. Keywords: Business Process Modeling Notation; Sales Process; Stock Checking; Information Systems; Operational Efficiency. Abstrak Proses penjualan dan pengecekan stok yang efisien merupakan komponen krusial dalam menjaga kelancaran operasional dan kepuasan pelanggan, terutama bagi pelaku UMKM seperti Toko Mozza Aquatic. Penelitian ini bertujuan untuk merancang ulang dua proses utama tersebut menggunakan pendekatan Business Process Model and Notation (BPMN). Studi ini melibatkan analisis alur bisnis secara menyeluruh, evaluasi efisiensi throughput, serta identifikasi solusi berbasis teknologi informasi. Hasil penelitian menunjukkan bahwa rancangan sistem baru, yang mengintegrasikan antarmuka penjualan dan inventaris secara digital, mampu meningkatkan struktur proses, mengurangi waktu layanan, dan meminimalkan kesalahan manual. Fitur-fitur seperti pencarian produk, pelacakan transaksi, indikator ketersediaan stok turut mendukung pengambilan keputusan yang lebih responsif dan akurat. Temuan ini menegaskan bahwa penerapan BPMN yang diiringi digitalisasi dan pelatihan SDM merupakan strategi efektif dalam meningkatkan efisiensi dan daya saing UMKM di tengah dinamika pasar yang kompetitif.
Pengembangan Sistem Informasi Monitoring Kinerja Guru dan Siswa Menggunakan Metode Agile
This study aims to develop a web-based monitoring information system for teachers and students using the Agile methodology. The system integrates the Google Classroom API to monitor teacher performance and student learning progress in real time. Unlike previous studies that focused only on academic data management, this research applies Agile stages—product backlog, sprint planning, execution, and review—in an iterative process involving teachers and students. The system was tested at Tunas Gading School, Jakarta, featuring key functions such as a teacher performance dashboard, student progress tracking, and automated task notifications. Results from User Acceptance Testing (UAT) show that 90% of teachers found the system helpful in monitoring student progress, while 85% of students benefited from task notifications. The system effectively improves learning monitoring efficiency and provides an innovative approach to automated academic monitoring integrated with online learning platforms. Keywords: Information System; Agile; Google Classroom; Academic Monitoring; Online Learning Abstrak Penelitian ini bertujuan mengembangkan sistem informasi monitoring kinerja guru dan siswa berbasis web menggunakan metode Agile. Sistem ini mengintegrasikan Google Classroom API untuk memantau kinerja guru dan perkembangan belajar siswa secara real-time. Berbeda dari penelitian sebelumnya yang hanya mengelola data akademik, pendekatan Agile diterapkan melalui tahapan product backlog, sprint planning, execution, dan review secara iteratif melibatkan guru dan siswa. Uji coba di Sekolah Tunas Gading Jakarta menampilkan fitur utama seperti dashboard kinerja guru, pemantauan progres siswa, dan notifikasi tugas otomatis. Hasil User Acceptance Testing (UAT) menunjukkan 90% guru menyatakan sistem membantu pemantauan siswa dan 85% siswa merasa terbantu dengan notifikasi tugas. Sistem ini meningkatkan efisiensi pemantauan pembelajaran serta menghadirkan inovasi dalam otomatisasi monitoring akademik terintegrasi dengan platform pembelajaran daring.
Penerapan Design Thinking dan SUS pada Pengembangan Website SIA SMA Sedes Sapientiae
User experience in web-based academic information systems is strongly influenced by the efficiency and intuitiveness of the user interface design. This study focuses on developing the user interface of the Academic Information System at SMA Sedes Sapientiae Jambu, which previously had not been fully optimized in presenting students’ academic progress reports. By applying the Design Thinking method, feature requirements were identified and designed according to users’ needs and preferences. To evaluate usability, the System Usability Scale (SUS) was employed after the system was developed. The evaluation results indicated a score in category “B” and a “good” rating on the adjective scale. These findings demonstrate that the Design Thinking approach contributes positively to enhancing usability and improving user comfort in accessing the academic information system. Keywords: User Interface; Design Thinking; System Usability Scale; Academic Information System, User Experience Abstrak Pengalaman pengguna dalam sistem informasi akademik berbasis website dipengaruhi oleh desain antarmuka pengguna yang efisien dan intuitif. Penelitian ini menitikberatkan pada pengembangan tampilan pengguna Sistem Informasi Akademik (SIA) di SMA Sedes Sapientiae Jambu yang sebelumnya belum maksimal dalam menyajikan laporan perkembangan akademik siswa. Melalui penerapan metode Design Thinking, kebutuhan fitur diidentifikasi sekaligus dirancang sesuai dengan keinginan dan kebutuhan. Untuk menilai tingkat kegunaan, digunakan metode System Usability Scale (SUS) setelah sistem selesai dikembangkan. Hasil evaluasi menunjukkan nilai dengan kategori “B” serta penilaian “good” pada skala adjektiva. Temuan ini membuktikan bahwa pendekatan design thinking mampu memberikan kontribusi positif terhadap peningkatan kegunaan dan kenyamanan pengguna dalam mengakses SIA di SMA Sedes Sapientiae Jambu.
Analisis Peran Media Sosial dalam Membangun Kepercayaan Publik Layanan E-Government Pendidikan
The development of E-Government in the education sector requires public services that are credible and capable of strengthening public trust. However, in the implementation of online student admission in South Sumatra, issues remain regarding transparency, responsiveness, and clarity of information. This study aims to examine the factors influencing public trust in the Provincial Education Office’s admission service through its social media platforms. A quantitative approach was applied using a survey analyzed with PLS-SEM, involving six variables: transparency, accountability, information quality, system quality and responsiveness, security and privacy, and managerial competence. The results indicate that only accountability and information quality have a positive and significant impact on public trust. These findings highlight that institutional responsibility and reliable information are essential in fostering trust in digital education services. Keywords: Public trust; Government social media; Accountability; Information quality; Education services Abstrak Perkembangan pelayanan pendidikan berbasis E-Government menuntut pemerintah daerah menyediakan layanan yang kredibel dan mampu membangun kepercayaan publik. Namun, dalam pelaksanaan PPDB di Provinsi Sumatera Selatan masih muncul keluhan terkait transparansi, responsivitas, dan kejelasan informasi. Penelitian ini bertujuan menganalisis faktor-faktor yang memengaruhi kepercayaan publik terhadap layanan PPDB melalui media sosial Dinas Pendidikan sebagai kanal komunikasi digital pemerintah. Metode yang digunakan adalah pendekatan kuantitatif melalui survei, dengan analisis menggunakan PLS-SEM pada enam variabel: transparansi, akuntabilitas, kualitas informasi, kualitas sistem dan responsivitas, keamanan dan privasi, serta kompetensi pengelola. Hasil penelitian menunjukkan bahwa hanya akuntabilitas dan kualitas informasi yang berpengaruh positif dan signifikan terhadap kepercayaan publik. Temuan ini menegaskan pentingnya tanggung jawab lembaga dan kualitas konten informasi dalam membangun kepercayaan pada layanan pendidikan digital.
Implementasi YOLOv10 untuk Pengenalan Alfabet SIBI berbasis Deteksi Gerakan Tangan
Sign language is a primary communication tool for people with hearing and speech impairments. One key component of the Indonesian Sign System (SIBI) is the SIBI alphabet, used for words without specific signs. However, limited public understanding creates communication gaps. This study develops a web-based SIBI alphabet recognition system using the YOLOv10 model. The dataset initially contained 6,110 images and was augmented to 15,859 images. Eight hyperparameter settings were tested, with the best result at a learning rate of 0.001, batch size 32, and Adam optimizer, achieving mAP@50 of 0.988 and mAP@50–95 of 0.971. The model was then converted to ONNX for faster inference, yielding mAP@50 of 0.953 and 797.7 ms per image. The ONNX model was integrated into a web app capable of real-time SIBI recognition. Results show this approach is effective, inclusive, and accessible as an assistive communication tool. Keywords: Deep learning; SIBI Alphabet; YOLOv10 Abstrak Bahasa isyarat merupakan sarana utama komunikasi bagi penyandang tunarungu dan tunawicara. Salah satu komponennya, alfabet Sistem Isyarat Bahasa Indonesia (SIBI), digunakan untuk menyampaikan kata yang tidak memiliki padanan isyarat khusus. Namun, kurangnya pemahaman masyarakat terhadap alfabet SIBI menimbulkan kesenjangan komunikasi. Penelitian ini bertujuan mengembangkan sistem pengenalan alfabet SIBI berbasis web menggunakan model YOLOv10. Dataset awal berjumlah 6.110 gambar dan diaugmentasi menjadi 15.859 gambar. Model dilatih menggunakan delapan konfigurasi hyperparameter yang menghasilkan performa terbaik pada learning rate 0,001, batch size 32, dan optimizer Adam dengan mAP@50 sebesar 0,988 dan mAP@50–95 sebesar 0,971. Untuk meningkatkan efisiensi, model dikonversi ke format ONNX dan diuji ulang menghasilkan mAP@50 sebesar 0,953 serta waktu inferensi 797,7 ms per gambar. Model ONNX kemudian diintegrasikan ke aplikasi web yang mampu mengenali alfabet SIBI secara real-time. Hasil menunjukkan pendekatan ini efektif sebagai alat bantu komunikasi yang inklusif dan mudah diakses.
Aplikasi Pendaftaran Online Poliklinik Di Rumah Sakit Karomah Holistic Berbasis Android
Karomah Holistic Hospital is a healthcare facility committed to providing high-quality and efficient medical services to the community. To enhance patient convenience in accessing healthcare services, an Android-based outpatient registration application has been developed. This application enables patients to register online, reduce physical queues, and provide more structured information regarding doctor schedules, room availability, and laboratory and radiology test results. The development of this application utilized the Waterfall method, which includes the stages of requirement analysis, design, implementation, testing, and maintenance. The application was developed using the Kotlin programming language with Jetpack Compose as the user interface framework and supported by WorkManager to manage the delivery of appointment reminder notifications. User Acceptance Testing of the application demonstrated that it is easy for patients to use and helps them access healthcare services more quickly and conveniently. With this application, it is hoped that patients will experience more efficient and comfortable service at Karomah Holistic Hospital. Keywords: Clinic registration; Android; Jetpack compose; Workmanager; Waterfall Abstrak Rumah Sakit Karomah Holistic adalah fasilitas layanan Kesehatan yang berkomitmen untuk memberikan pelayanan medis yang berkualitas dan efisien kepada masyarakat. Untuk meningkatkan kemudahan pasien dalam mengakses layanan kesehatan, dikembangkan aplikasi pendaftaran poliklinik berbasis Android. Aplikasi ini memungkinkan pasien untuk melakukan pendaftaran secara online, mengurangi antrean fisik, serta memberikan informasi yang lebih terstruktur terkait jadwal dokter, ketersediaan kamar, dan hasil pemeriksaan laboratorium maupun radiologi. Pengembangan aplikasi ini menggunakan metode Waterfall, yang mencakup tahap analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Aplikasi dikembangkan dengan bahasa pemrograman Kotlin menggunakan Jetpack Compose sebagai framework antarmuka pengguna, serta didukung oleh WorkManager untuk mengatur pengiriman notifikasi pengingat jadwal pemeriksaan. Pengujian aplikasi menggunakan metode User Acceptance Test menunjukkan bahwa aplikasi ini mudah digunakan oleh pasien dan membantu mereka dalam mengakses layanan kesehatan secara lebih cepat dan praktis. Dengan adanya aplikasi ini, diharapkan pasien dapat merasakan pengalaman layanan yang lebih efisien dan nyaman di Rumah Sakit Karomah Holistic.
Perbandingan Weighted Product Dengan AHP+WP Dalam Penentuan Pegawai Berprestasi Di Universitas XYZ
The selection of outstanding employees is an important aspect of human resource management in higher education, requiring objective and accurate evaluation. This study compares two multi-criteria decision-making methods: Weighted Product (WP) and a combination of Analytic Hierarchy Process with WP (AHP+WP) in ranking high-performing staff at XYZ University. The evaluation uses Mean Absolute Percentage Error (MAPE) to measure the closeness of the method’s results to expert-based manual assessments. WP produced a MAPE of 16.86%, while AHP+WP yielded only 9.17%, indicating higher accuracy. The Wilcoxon signed-rank test resulted in a p-value of 0.0002 (< 0.05), indicating a significant difference. AHP+WP is superior due to its systematic and consistent weighting mechanism, compared to the more subjective WP. These findings align with previous studies recommending hybrid methods. AHP+WP is considered more appropriate for official implementation in employee performance assessment systems to support fair, transparent, and data-driven evaluation. Kata kunci: AHP; Weighted Product; outstanding employee; MAPE; Wilcoxon. Abstrak Pemilihan pegawai berprestasi merupakan bagian penting dalam manajemen sumber daya manusia di perguruan tinggi, yang memerlukan evaluasi objektif dan akurat. Penelitian ini membandingkan dua metode pengambilan keputusan multikriteria: Weighted Product (WP) dan kombinasi Analytic Hierarchy Process dengan WP (AHP+WP) dalam menentukan peringkat pegawai berprestasi di Universitas XYZ. Evaluasi menggunakan Mean Absolute Percentage Error (MAPE) untuk mengukur kedekatan hasil metode dengan penilaian manual oleh pakar. WP menghasilkan MAPE sebesar 16,86%, sementara AHP+WP hanya 9,17%, menunjukkan akurasi lebih tinggi. Uji Wilcoxon signed-rank memberikan nilai p = 0,0002 (< 0,05), mengindikasikan perbedaan signifikan. AHP+WP unggul karena mekanisme pembobotannya yang sistematis dan konsisten, dibandingkan WP yang lebih subjektif. Temuan ini sejalan dengan studi sebelumnya yang merekomendasikan metode hybrid. AHP+WP dinilai lebih layak untuk diimplementasikan secara resmi dalam sistem penilaian pegawai berprestasi, guna mendukung evaluasi kinerja yang adil, transparan, dan berbasis data.
Model Aplikasi Sistem E-Commerce untuk Rekomendasi dan Pemantauan Harga Produk Penjual
Sellers on e-commerce platforms face difficulties in determining strategic pricing due to dynamic competition. To address this problem, an integrated system application model was developed as a solution to assist sellers. This research utilized the Research and Development (R&D) methodology with a waterfall model, which included the stages of needs analysis, system design, implementation, performance verification and data analysis, and final evaluation and revision. The result is a functional application capable of providing features such as search, strategic price recommendations at three levels (lowest, average/middle, highest), viewing more detailed information about products sold in graphical form, and other features. Usability testing conducted on target users yielded average scores of 95.54% for free-type customers, 91.26% for premium-type customers, and 96.8% for buyer-type cutomers. This indicates excellent ease of use and a high level of acceptance. This website model proved to be an effective and practical tool for sellers to establish competitive pricing strategies. Keywords: E-commerce; Price Monitoring; Strategic Pricing; Research and Development; Recommender System Abstrak Penjual pada platform e-commerce menghadapi kesulitan dalam menentukan harga strategis akibat persaingan dinamis. Untuk mengatasi masalah ini, sebuah model aplikasi sistem terintegrasi dikembangkan sebagai solusi untuk membantu penjual. Penelitian ini menggunakan metodologi Research and Development (R&D) dengan waterfall yang mencakup tahap analisis kebutuhan; perancangan sistem; implementasi; verifikasi kinerja dan analisis data; dan evaluasi akhir dan revisi. Hasilnya adalah sebuah aplikasi fungsional yang mampu menyediakan fitur pencarian, rekomendasi harga strategis pada tiga level (terendah, rata-rata/menengah, tertinggi), melihat informasi lebih detail mengenai produk yang dijual dalam bentuk grafik, dan fitur lainnya. Pengujian usabilitas menggunakan usability testing terhadap target pengguna menghasilkan skor rata-rata 95,54% pada customer yang bertipe gratis, 91,26% untuk pengguna bertipe premium, dan 96,8% pengguna yang bertipe pembeli. Hal ini yang mengindikasikan kemudahan penggunaan dan tingkat penerimaan sangat baik. Model website ini terbukti menjadi alat bantu yang efektif dan praktis bagi penjual untuk menetapkan strategi harga kompetitif.
Penerapan RFID dan WhatsApp Gateway untuk Monitoring Kehadiran Siswa secara Real-Time
This study aims to design and implement a real-time student attendance system based on Radio Frequency Identification (RFID) integrated with a WhatsApp Gateway. The background of this research is the need for a fast and accurate attendance system that can instantly provide attendance information to parents. The research method adopts Research and Development (R&D) with a system development approach, including requirements analysis, system architecture design, development of a PHP and MySQL-based web application, integration of the WhatsApp Gateway API (e.g., Fonnte or Wablas), as well as functional and reliability testing. The black-box testing results show that all core functions, such as RFID reading, database recording, and notification delivery, operate as designed without errors. Meanwhile, the load test demonstrates that the system can process more than 500 transactions per minute with a notification delivery success rate of >=98% and an average latency of 2–3 seconds, meeting real-time service standards This system not only provides attendance reports accessible at any time but also enhances parental involvement through instant WhatsApp notifications. These findings confirm the reliability of RFID in automating attendance and introduce novelty through the integration of a WhatsApp Gateway, which has rarely been addressed in previous studies. Keywords: RFID; WhatsApp Gateway; Student Attendance; Real-Time; Attendance Monitoring Abstrak Sistem absensi manual di sekolah masih lambat, rawan manipulasi, dan sulit direkap, sehingga diperlukan solusi presensi yang cepat dan akurat. Penelitian ini bertujuan mengembangkan sistem absensi siswa real-time berbasis RFID yang terintegrasi dengan WhatsApp Gateway untuk mengirimkan notifikasi otomatis kepada orang tua. Penelitian menggunakan pendekatan R&D melalui analisis kebutuhan, perancangan arsitektur, pengembangan aplikasi PHP MySQL, dan integrasi API WhatsApp. Pengujian dilakukan menggunakan metode black-box dan load test. Pada pengujian beban, sistem berhasil memproses hingga 800 transaksi dalam satu gelombang pemindaian puncak, yang merepresentasikan kondisi saat sebagian besar dari 830 siswa melakukan absensi dalam rentang waktu sangat singkat. Tingkat keberhasilan pengiriman notifikasi mencapai 98.7%, dengan latency rata-rata 2.7 detik. Seluruh fungsi berjalan sesuai rancangan tanpa kesalahan. Sistem ini terbukti cepat, stabil, dan efektif untuk mendukung monitoring kehadiran siswa secara real-time serta meningkatkan transparansi komunikasi antara sekolah dan orang tua.
Analisis Clustering Pengguna SIKP FTI UKSW Menggunakan User Experience Questionnaire
The ease of access to technology today encourages the use of technology to improve productivity and efficiency in the lecture process, including in the lecture process at FTI UKSW (Faculty of Information Technology, Satya Wacana Christian University) which uses SIKP (Practical Work Information System). This study identifies the grouping/clustering of SIKP user students based on student user experience. The UEQ and Fuzzy C-Means methods are used to formulate the clustering of SIKP user students with the aim of determining the level of satisfaction of FTI UKSW students with the SIKP currently in use and hopefully providing an analysis of which parts of the FTI UKSW SIKP need to be improved. The UEQ method uses six elements, namely Attractiveness, Clarity, Efficiency, Accuracy, Stimulation, and Novelty. Meanwhile, the Fuzzy C-Means method measures the degree of membership of a data set to determine the satisfaction level grouping. Testing the accuracy of the algorithm's performance showed that the clustering process can form groupings with a level of clarity and cluster separation that provides good performance and can still be developed to obtain more optimal performance. Keywords: Clustering; User Experience Questionnaire; Fuzzy C-Means Abstrak Mudahnya akses teknologi saat ini mendorong pemanfaatan teknologi untuk meningkatkan produktivitas dan efisiensi pada proses perkuliahan, termasuk pada proses perkuliahan di FTI UKSW (Fakultas Teknologi Informasi Universitas Kristen Satya Wacana) yang menggunakan SIKP (Sistem Informasi Kerja Praktek). Penelitian ini mengidentifikasi pengelompokan mahasiswa pengguna SIKP berdasarkan user experience mahasiswa. Metode UEQ dan Fuzzy C-Means adalah metode yang digunakan untuk merumuskan clustering mahasiswa pengguna SIKP dengan tujuan mengetahui tingkat kepuasan mahasiswa FTI UKSW terhadap SIKP yang digunakan saat ini dan diharapkan dapat memberikan analisis bagian mana yang perlu ditingkatkan pada SIKP FTI UKSW. Metode UEQ akan menggunakan 6 elemen yaitu Daya tarik, Kejelasan, Efisiensi, Ketepatan, Stimulasi, dan Kebaruan. Sementara itu, metode Fuzzy C-Means akan mengukur derajat keanggotaan suatu data untuk mengetahui pengelompokan tingkat kepuasan. Pengujian akurasi performa algoritma memberikan hasil bahwa proses clustering dapat membentuk pengelompokan dengan tingkat kejelasan dan pemisahan cluster yang memberikan performa baik serta masih dapat dikembangkan untuk memperoleh performa yang lebih optimal.
Model Aplikasi Point of Sale Berbasis Mobile dengan Modul Pre Order Real Time
Point of sale (POS) systems are critical to retail operations because they serve as the hub for transaction capture, inventory synchronization, and real time reporting, thereby reducing input errors and accelerating service. This study develops a mobile based point of sale application equipped with a real time pre order mechanism to address issues such as manual transaction recording, delayed recap processes, and limited visibility of scheduled orders. Development followed the Waterfall methodology, comprising the Communication, Planning, Modeling, Construction, and Deployment phases. The proposed architecture is mobile first, providing real time synchronization of stock and order status along with a sales-summary dashboard. System testing employed black box methods on core scenarios, including authentication, master data management, transactions and payments, order scheduling, and reporting. The result is a mobile software solution that implements POS and pre order concepts and has been deployed at ALVIN’S Bakery. Keywords: Point of Sale; Mobile Application; Pre Order; Real Time; Waterfall Abstrak Point of sale (POS) system penting bagi bisnis ritel karena menjadi pusat pencatatan transaksi, sinkronisasi stok, dan pelaporan real time yang menekan kesalahan input serta mempercepat layanan. Penelitian ini mengembangkan aplikasi point of sale berbasis mobile yang dilengkapi mekanisme pre order real time untuk mengatasi masalah seperti pencatatan transaksi manual, keterlambatan rekapitulasi, keterbatasan visibilitas pesanan yang dijadwalkan. Metode pengembangan aplikasi menggunakan Waterfall system meliputi: communication, planning, modeling, construction, dan deployment. Arsitektur yang diusulkan bersifat mobile first dengan sinkronisasi stok dan status pesanan secara real time serta dashboard ringkasan penjualan. Pengujian sistem menggunakan black box pada skenario inti, mencakup autentikasi, pengelolaan master data, transaksi dan pembayaran, penjadwalan pesanan, serta pelaporan. Hasil penelitian adalah perangkat lunak berbasis mobile dengan penerapan konsep POS dan pre order yang diterapkan pada salah satu bisnis ALVIN’S Bakery.
Optimalisasi TinyBERT-Vosk Untuk Kontrol Suara Real-Time Robot Mecanum Raspberry Pi
Intelligent Document Processing Berbasis OCR + Transformers dan CNN untuk Verifikasi Dokumen Bantuan Pangan
The rice assistance program is a government initiative to alleviate poverty by distributing rice to low-income households. This study aims to design and implement an Intelligent Document Processing system based on Convolutional Neural Networks (CNN) and hybrid Optical Character Recognition (OCR) to facilitate the verification of social assistance documents. The system integrates the LayoutLMv3 model for text entity extraction and a ResNet-18 CNN for signature-box classification, supported by conventional OCR and TrOCR for challenging text regions. The research methodology covers system design and model development. Experimental results show that the system can successfully convert PDF documents into images and accurately recognize key entities such as names and national ID numbers using LayoutLMv3 (validation accuracy 96.78%). Although ResNet-18 achieves a validation accuracy of 99.04%, it remains biased toward majority classes and is not yet reliable for verification decisions. The proposed system has the potential to accelerate and standardize document verification, with future work focusing on dataset rebalancing and improving the signature classification model. Keywords: LayoutLMv3; ResNet-18; Optical Character Recognition; TrOCR Abstrak Program bantuan pangan beras merupakan upaya pemerintah dalam menanggulangi kemiskinan melalui distribusi beras kepada masyarakat kurang mampu. Penelitian ini bertujuan merancang dan mengimplementasikan Intelligent Document Processing berbasis Convolutional Neural Network (CNN) dan OCR hibrida untuk mempermudah proses verifikasi dokumen bantuan pangan. Sistem ini mengintegrasikan model machine learning LayoutLMv3 untuk ekstraksi entitas teks serta CNN ResNet-18 untuk klasifikasi tanda tangan, dengan dukungan Optical Character Recognition (OCR) dan TrOCR. Metode penelitian mencakup perancangan sistem dan pengembangan perangkat. Hasil pengujian menunjukkan bahwa sistem mampu mengekstraksi dokumen PDF menjadi citra, mengenali entitas seperti nama dan NIK dengan akurasi tinggi menggunakan LayoutLMv3 (val_accuracy 96,78%), serta mengklasifikasikan kotak tanda tangan dengan ResNet-18 (val_accuracy 99,04%). Namun, ResNet-18 masih bias terhadap kelas mayoritas sehingga belum dapat dianggap andal untuk keputusan verifikasi. Sistem yang diusulkan berpotensi mempercepat pemeriksaan dokumen bantuan pangan, sementara pengembangan lanjut difokuskan pada penyeimbangan data dan penyempurnaan model klasifikasi tanda tangan.
Pengembangan Aplikasi Multimedia Pembelajaran Bahasa Inggris
The development of science and technology encourages innovations in the teaching and learning process, one of which is interactive learning multimedia that integrates text, images, audio, video, animation, and simulations to create a more engaging learning experience. English is often considered difficult by students because it is not used in their daily lives, resulting in relatively lower learning outcomes. The problem arises because teachers still use conventional teaching methods and make limited use of digital technology. This study aims to develop an English learning multimedia application to optimize the learning process for both students and teachers. The development method used is the Waterfall model, which includes needs analysis, system design, implementation, testing, and maintenance. Based on the functionality testing results, the developed multimedia application operates properly and meets all system requirements, making it feasible to use as a supporting learning medium. Keywords: Multimedia; Learning; Interactive; Android; Waterfall Abstrak Perkembangan ilmu pengetahuan dan teknologi mendorong pembaruan dalam proses belajar mengajar, salah satunya melalui multimedia pembelajaran interaktif yang menggabungkan teks, gambar, audio, video, animasi, dan simulasi untuk menciptakan pengalaman belajar yang lebih menarik. Bahasa Inggris sering dianggap sulit oleh siswa karena bukan bahasa yang digunakan sehari-hari, sehingga nilai hasil belajar cenderung lebih rendah. Permasalahan muncul karena metode pembelajaran yang digunakan guru masih konvensional dan kurang memanfaatkan teknologi digital. Penelitian ini bertujuan mengembangkan aplikasi multimedia pembelajaran Bahasa Inggris untuk mengoptimalkan proses pembelajaran siswa dan guru. Metode pengembangan yang digunakan adalah Waterfall, meliputi analisis kebutuhan, desain, implementasi, pengujian, dan pemeliharaan. Berdasarkan hasil pengujian fungsionalitas, aplikasi multimedia yang dikembangkan berfungsi dengan baik dan memenuhi seluruh kebutuhan sistem, sehingga dinilai layak digunakan sebagai media pendukung pembelajaran.
Desain User Interface Pendaftaran Akta Kelahiran Dan Kartu Identitas Anak Pada Data Kependudukan
Efficient and easy-to-understand public services are a primary demand in today’s digital era. One essential service that needs improvement is the registration system for birth certificates and Child Identity Cards (KIA). This study aims to design an efficient and user friendly user interface (UI) to facilitate online registration for the public. The Design Thinking method is used as the main approach in this research, consisting of five stages: empathize, define, ideate, prototype, and test. Through interviews and observations involving users and civil registration officers (Disdukcapil), several challenges were identified, such as long queues and the perception of excessive documentation required for registering birth certificates and KIAs. The ideation and prototyping process resulted in a simpler and more understandable UI design. Testing of the prototype showed a significant improvement in users’ understanding of the registration process and their overall satisfaction. Therefore, the Design Thinking approach has proven effective in producing a UI design that meets user needs and enhances the efficiency of digital public services. Keywords: Design user interface; Design Thinking; Birth certificate registration; Child identity card registration Abstrak Pelayanan publik yang efisien dan mudah dipahami merupakan tuntutan utama dalam era digital saat ini. Salah satu layanan penting yang perlu ditingkatkan adalah sistem pendaftaran akta kelahiran dan Kartu Identitas Anak (KIA). Penelitian ini bertujuan untuk merancang antarmuka pengguna (UI) yang efisien dan user-friendly guna mempermudah masyarakat dalam melakukan pendaftaran secara daring. Metode Design Thinking digunakan sebagai pendekatan utama dalam penelitian ini, yang terdiri dari lima tahap: empathize, define, ideate, prototype, dan test. Melalui wawancara dan observasi terhadap pengguna serta petugas Disdukcapil, ditemukan berbagai kendala seperti antrian yang panjang serta dokumen yang dianggap banyak dalam mengurus pendaftaran akta kelahiran dan Kartu Identitas Anak (KIA). Hasil dari proses ideasi dan prototyping menghasilkan desain UI yang lebih sederhana, dan mudah dipahami. Pengujian terhadap prototype menunjukkan peningkatan signifikan dalam pemahaman alur pendaftaran dan kepuasan pengguna. Dengan demikian, pendekatan Design Thinking terbukti efektif dalam menghasilkan desain UI yang mampu menjawab kebutuhan pengguna serta meningkatkan efisiensi layanan publik digital.
Designing a Data Mart at the Indonesian Psychological Healthcare Center Using Pentaho
Critical data is essential for organisational success, providing essential information for decision-making. This study focuses on the Indonesian Mental Health Centre (IndoPsyCare), which utilises data to improve service performance. The research aims to design a data mart to support analytical needs by transforming the Online Transaction Processing (OLTP) database into Online Analytical Processing (OLAP). This design follows Kimball's Nine-Step Approach and integrates the Extract, Transform, Load (ETL) process. Data was collected from August 2023 to August 2024 through interviews and electronic documentation. The system was implemented using Microsoft SQL Server Management Studio 18 and Pentaho Data Integration. The resulting data mart uses a star schema with fact and dimension tables tailored to stakeholder needs, particularly in appointment analysis. Findings indicate that the data mart facilitates efficient access, targeted analysis, and improved query performance, thereby supporting IndoPsyCare's decision-making and overall service optimisation.
Sistem Reservasi Berbasis Android dengan Dasbor Analitik
The conventional reservation process at Ema Mom Kids Baby Spa has led to various operational issues, such as scheduling errors and inefficient queues. This research aims to address these challenges through the development of an integrated digital reservation system. This study successfully produced a dual-platform system (a mobile application for the business owner and a web platform for customers) that manages booking, schedule, and service data. Testing using the black-box method demonstrated that all core system functionalities from booking to schedule management performed validly. The system also features a descriptive analytics dashboard that serves as a data-driven decision-making tool for the business owner. The developed system has proven effective in improving operational efficiency, minimizing operational errors, and providing strategic business insights. Keywords: Reservation system; Analytics dashboard; Baby spa; Schedule management; Android Abstrak Proses reservasi konvensional di Ema Mom Kids Baby Spa memicu antrean yang tidak efisien dan kesalahan jadwal. Untuk mengatasi masalah itu, sebuah sistem reservasi digital terintegrasi dikembangkan. Penelitian ini berhasil menghasilkan sistem dua platform (aplikasi mobile untuk pemilik usaha dan platform web untuk pelanggan) yang mampu mengelola seluruh fungsionalitas utama. Validasi fungsional menggunakan metode black box testing membuktikan bahwa seluruh fitur inti, dari alur pemesanan hingga pengelolaan jadwal, telah berjalan sesuai harapan. Aplikasi ini juga menyediakan dasbor analitik deskriptif yang berfungsi sebagai alat bantu pengambilan keputusan berbasis data bagi pemilik usaha. Implementasi sistem ini terbukti tidak hanya meningkatkan efisiensi dan meminimalkan galat (error) operasional, tetapi juga menyediakan wawasan bisnis strategis bagi pemilik.
Designing a Dashboard for Sales Trends and Analysis at Coventown Glodok Jakarta
Coventown is a coffee shop with a Chinese theme located in the Petak Enam Glodok area, Jakarta. The sales dashboard design allows Coventown Glodok Jakarta to identify sales patterns, and predict sales performance through historical data analysis. This study aims to present data in easy-to-understand visualizations to demonstrate the use of dashboards in improving the efficiency of sales monitoring, providing strategic insights into trends, and achieving sales targets to support more precise and effective decision-making. The prototype development iterations were planned quickly, and the data was processed using Microsoft Power BI and the Python programming language. The results of this study show that the sales dashboard at Coventown Glodok Jakarta effectively monitors sales in line with Key Performance Indicators (KPIs) such as time, category, product, price, and quantity. The resulting dashboard improves the efficiency of monitoring sales performance and helps the company display sales trends for best-selling products.
Machine Learning Classification of Insomnia Using Multidimensional Features and SMOTE
Sleep disorders, especially insomnia, are common among adolescents and negatively affect health. Early detection is crucial for appropriate treatment. This study aims to classify insomnia severity in adolescents using a Machine Learning (ML) model and multidimensional features derived from 19 questionnaire instruments. The dataset consists of 95 adolescents aged 16–19 years, categorized into Insomnia, Subclinical Insomnia, and Control classes. The modeling process includes reducing multicollinearity, class balancing with SMOTE, and hyperparameter optimization using GridSearchCV and StratifiedKFold. Feature importance analysis was conducted using decision tree-based methods and permutation importance. The results show that SMOTE improves SVM performance from 0.690 to 0.793 and positively affects Random Forest. Logistic Regression performs best without SMOTE (accuracy 0.759), while XGBoost shows the lowest accuracy (0.614) even with SMOTE. A total of 11 features consistently contribute to all models. In conclusion, ML models, particularly SVM, are effective for classifying insomnia severity in adolescents.
Business Process Reengineering Pencatatan Laporan Harian Mandor Pada PT. Nyalindung Menggunakan ODOO
The manual recording of the Foreman's Daily Report (LHM) at PT Nyalindung has caused various problems, such as inefficiency, potential data errors, and delays in the reporting process. This research aims to apply the Business Process Reengineering (BPR) approach by utilizing the Odoo system to automate and simplify the LHM recording workflow. The methods used include analyzing current business processes, identifying system requirements, redesigning workflows, and implementing web-based Odoo custom modules. The results showed a significant increase in reporting speed with an initial result of 60% increasing to 72%, as well as efficiency in resource usage. Based on these findings, it can be concluded that the implementation of BPR using Odoo can effectively optimize the LHM recording process. Keywords: Business Process Reengineering; Foreman Daily Report; Odoo; Automation, Business Process Efficiency. Abstrak Pencatatan Laporan Harian Mandor (LHM) di PT. Nyalindung yang masih dilakukan secara manual menimbulkan berbagai permasalahan, seperti ketidakefisienan, potensi kesalahan data, serta keterlambatan dalam proses pelaporan. Penelitian ini bertujuan menerapkan pendekatan Business Process Reengineering (BPR) dengan memanfaatkan sistem Odoo untuk mengotomatisasi dan menyederhanakan alur kerja pencatatan LHM. Metode yang digunakan mencakup analisis proses bisnis saat ini, identifikasi kebutuhan sistem, perancangan ulang alur kerja, hingga implementasi modul kostum Odoo berbasis web. Hasil penelitian menunjukkan adanya peningkatan signifikan dalam hal kecepatan pelaporan dengan hasil awal 60% meningkat menjadi 72%, serta efisiensi penggunaan sumber daya. Berdasarkan temuan tersebut, dapat disimpulkan bahwa penerapan BPR menggunakan Odoo secara efektif mampu mengoptimalkan proses pencatatan LHM.
Data Warehouse for Study Program Accreditation Data Management at Private University X
Technological advancements in the Fourth Industrial Revolution have transformed higher education, yet accreditation processes often suffer from inefficient data management, causing delays, inconsistencies, and limited monitoring of performance indicators. This study designs a data warehouse integrated with a dashboard and Early Warning System (EWS) to improve accreditation data management at University X, West Jakarta. Using Kimball’s Dimensional Model, data were structured into fact and dimension tables, with collection methods including interviews with the Head of the IT Department and document analysis of accreditation processes. Descriptive statistics were applied to identify trends and patterns. The dashboard enables real-time visualisation of key metrics, while the EWS issues alerts on missing or outdated data. Results show that the snowflake schema enhances data organisation and clarity, reducing manual processing and facilitating proactive monitoring. The system supports more efficient accreditation management and strengthens institutional readiness for assessment.
Analisis Usability eOffice UKSW Menggunakan Technology Acceptance Model
Design of a Data Mart for Optimizing Product Sales Analysis at PT. X
With the advancement of technology, companies can now efficiently manage and analyze their data, providing valuable insights that support better business decisions. PT. X is one such company that wants to leverage this capability to optimize its sales data analysis. Therefore, the goal of this study is to design an effective data mart. During the development process, we used Kimbal's Nine-Step Methodology alongside the ETL (extract, transform, load) process to ensure the data was accurately extracted, transformed, and loaded into the data mart. The outcome of this research is a data mart and star schema tailored to PT. X specific needs. Testing results showed that query execution time increased by 40% and data accuracy improved by 80%. Report generation time was also optimized, resulting in a process that was 83% faster. These results demonstrate how a well-structured data mart can improve decision-making efficiency and data reliability.
Pengembangan Aplikasi Pengaduan dan Monitoring Fasilitas Umum
Public facilities such as roads, street lights and drainage channels are vital elements that support the comfort and safety of the community. However, damage to these facilities is often not repaired immediately due to the lack of an integrated reporting and monitoring system. This study aims to design and develop a mobile and web-based public facility complaint and monitoring application that allows the community to report damage directly, along with the location, description, and photos. The system was developed using the Waterfall method, which includes needs analysis, design, implementation, testing, and maintenance. Testing results using Black Box Testing show that all features function according to specifications, including location-based reporting and real-time status monitoring. Keywords: Public facilities; Reporting system; Mobile application; Digitization of public services; Monitoring. Abstrak Fasilitas umum seperti jalan, lampu penerangan, dan saluran drainase merupakan elemen vital yang menunjang kenyamanan dan keselamatan masyarakat. Namun, kerusakan pada fasilitas tersebut sering kali tidak segera diperbaiki karena belum adanya sistem pelaporan dan pemantauan yang terintegrasi. Penelitian ini bertujuan untuk merancang dan mengembangkan aplikasi pengaduan dan monitoring fasilitas umum berbasis mobile dan web yang memungkinkan masyarakat melaporkan kerusakan secara langsung disertai lokasi, deskripsi, dan foto. Pengembangan sistem dilakukan menggunakan metode Waterfall yang meliputi analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Hasil pengujian menggunakan Black Box Testing menunjukkan bahwa seluruh fitur berfungsi sesuai spesifikasi, termasuk pelaporan berbasis lokasi dan pemantauan status secara real-time.
Pengembangan Aplikasi Sistem Informasi Perpustakaan untuk Efisiensi Layanan di SMP Negeri 4 Mauliru
The library is a strategic element as a learning resource center at Mauliru State Junior High School 4. However, the manual management process results in low service effectiveness, potential recording errors, and limited access to information on book collection availability. To address these issues, this study designed and developed a web-based library information system using the Extreme Programming (XP) method. This system provides centralized data management, real-time book borrowing and return services, automatic updates on availability status, fine calculations, and transaction history as a basis for reporting. Testing using the black box method showed that all system functions ran according to specifications and were able to improve service efficiency, data accuracy, and information access. Thus, this system is suitable for implementation as a library digitization solution to support the learning process Keywords: Black Box Testing; Extreme Programming; Mauliru State Junior High School 4 Abstrak Perpustakaan merupakan elemen strategis sebagai pusat sumber belajar di SMP Negeri 4 Mauliru. Namun, proses pengelolaan yang masih dilakukan secara manual menimbulkan rendahnya efektivitas layanan, potensi kesalahan pencatatan, serta keterbatasan akses informasi ketersediaan koleksi buku. Untuk mengatasi permasalahan tersebut, penelitian ini merancang dan mengembangkan sistem informasi perpustakaan berbasis web dengan metode Extreme Programming (XP). Sistem ini menyediakan pengelolaan data terpusat, layanan peminjaman dan pengembalian buku secara real-time, pembaruan otomatis status ketersediaan, perhitungan denda, serta riwayat transaksi sebagai dasar pelaporan. Hasil pengujian menggunakan metode black box menunjukkan seluruh fungsi sistem berjalan sesuai spesifikasi dan mampu meningkatkan efisiensi layanan, keakuratan data, serta akses informasi. Dengan demikian, sistem ini layak diterapkan sebagai solusi digitalisasi perpustakaan untuk mendukung proses pembelajaran.
Implementasi Dynamic Pricing dan Point System pada Aplikasi Pemesanan Air Minum Isi Ulang
The increasing demand for refillable drinking water, driven by population growth and a practical lifestyle, creates the need for an efficient ordering system. On the other hand, the manual ordering process still faces constraints such as inefficient record-keeping, delivery delays, and a lack of incentives for loyal customers. This research focuses on developing a mobile-based water ordering application that integrates the concepts of dynamic pricing and a point system to improve operational efficiency and strengthen customer retention. The dynamic pricing model is implemented to adjust prices based on the time of ordering, while the point system is designed to encourage repeat transactions. The system was developed using Flutter for the user application and React with Firebase for the admin dashboard. System testing using the Black Box Testing method shows that the main system functionalities encompassing the ordering process, dynamic pricing calculation, and point system management have operated in accordance with the functional design. Keywords: Drinking water ordering; Dynamic pricing; point system; Mobile application; Flutter; Firebase Abstrak Permintaan air minum isi ulang yang meningkat akibat pertumbuhan populasi dan gaya hidup praktis menimbulkan kebutuhan akan sistem pemesanan yang efisien. Di sisi lain, proses pemesanan manual masih menghadapi kendala seperti ketidakefisienan pencatatan, keterlambatan pengiriman, dan kurangnya insentif bagi pelanggan setia. Penelitian ini berfokus pada pengembangan aplikasi pemesanan air minum berbasis mobile yang mengintegrasikan konsep dynamic pricing dan point system guna meningkatkan efisiensi operasional serta memperkuat retensi pelanggan. Model dynamic pricing diterapkan guna menyesuaikan harga berdasarkan waktu pemesanan, sedangkan point system dirancang untuk mendorong transaksi berulang. Sistem dikembangkan menggunakan Flutter sebagai aplikasi pengguna dan React dengan Firebase untuk dashboard admin. Pengujian sistem menggunakan metode Black Box Testing menunjukkan bahwa fungsionalitas utama sistem mencakup proses pemesanan, kalkulasi dynamic pricing, dan pengelolaan point system telah berjalan sesuai dengan rancangan fungsional.
Rancang Bangun Aplikasi Rumah Aspirasi Berbasis Android dengan Metode Rapid Application Development
Technology development encourages government services to become more effective and responsive. However, in practice, the process of submitting public aspirations in Surabaya is still carried out manually, making it prone to delays and data inaccuracies. This study aims to design and develop the Rumah Aspirasi Android application as a more structured platform for managing citizen feedback and complaints. The system was developed using the Rapid Application Development (RAD) method through two iterations, followed by evaluation using Blackbox Testing and User Acceptance Testing (UAT). The results show that all main functions run well, with the UAT achieving an average score of more than 93% for functionality, reliability, usability, and efficiency. These findings indicate that the application can improve the efficiency and quality of services in managing public aspirations in Surabaya. Keyword: Rumah Aspirasi; Deputy Mayor of Surabaya; Kotlin; Rapid Application Development Abstrak Perkembangan teknologi menuntut layanan pemerintah untuk bertransformasi menjadi lebih efektif dan responsif. Namun, dalam praktiknya, proses penyampaian aspirasi masyarakat di Surabaya masih dilakukan secara manual, sehingga rentan mengalami keterlambatan dan ketidaktepatan data. Penelitian ini bertujuan merancang dan mengembangkan aplikasi Rumah Aspirasi berbasis Android sebagai sarana yang lebih terstruktur dalam pengelolaan masukan dan keluhan warga. Metode pengembangan yang digunakan adalah Rapid Application Development (RAD) melalui dua tahapan iterasi, disertai evaluasi sistem menggunakan Blackbox Testing dan User Acceptance Testing (UAT). Hasil pengujian menunjukkan bahwa seluruh fungsi utama berjalan dengan baik, dengan tingkat kelayakan UAT rata-rata melebihi 93% pada aspek functionality, reliability, usability, dan efficiency. Hasil ini menunjukkan bahwa aplikasi yang dikembangkan mampu meningkatkan efisiensi dan kualitas layanan dalam pengelolaan aspirasi Masyarakat Kota Surabaya.
Analytical Hierarchy Process Method of Prosthetic and Orthotic Materials for Patient Needs
This study highlights the importance of optimising assistive devices for people with disability, as the law says in Law No. 8 of 2016. Ligar Mandiri Prosthetics and Orthopaedics Clinic offer related services, where choosing the right materials is getting more complicated because of fast tech advances and lots of options like carbon fibre, plastic, and titanium. This study aims to develop a Decision Support System (DSS) to assist practitioners in selecting materials based on quality, cost, and production time criteria. The alternatives evaluated include local, semi-imported, and imported materials. Using the Analytic Hierarchy Process (AHP) method, the analysis shows that imported materials received the highest ranking (0.54708), followed by local materials (0.24157) and semi-imported materials (0.21155). The DSS developed in this study has enhanced the accuracy, efficiency, and transparency of decision-making, thereby supporting practitioners in providing effective and reliable prosthetic and orthotic solutions.