Pengembangan Aplikasi Sistem Rekomendasi Tempat Wisata Dengan Collaborative Filtering
Abstract
Tourists often face difficulties in choosing tourist destinations that match their preferences and interests among the many available options. The purpose of this research is to develop a tourism recommendation system application for Jakarta using the Collaborative Filtering method. This study will develop a tourist recommendation system for Jakarta using collaborative filtering with Python programming language and WxPython as the Graphical User Interface (GUI) framework using the Pycharm application. A dataset consisting of 985 entries has undergone pre-processing. The model evaluation results show that the Mean Squared Error (MAE) value is 0.7561 and the Root Mean Squared Error (RMSE) value is 1.0634. This indicates that the recommendation system's accuracy is approximately 91.60% based on the Mean Squared Error (MAE) and 88.18% based on the Root Mean Squared Error (RMSE).
Key Word : Recommendation System; Collaborative Filtering; Jakarta; Tourist attraction; Pycharm
Abstrak
Wisatawan seringkali menghadapi kesulitan dalam memilih tempat wisata yang sesuai dengan preferensi dan minat mereka di antara banyak pilihan yang tersedia.Tujuan penelitian ini adalah untuk membuat aplikasi sistem rekomendasi tempat wisata di Jakarta yang menggunakan metode Collaborative Filltering. Penelitian ini akan mengembangkan sistem rekomendasi tempat wisata di Jakarta yang menggunakan collaborative filltering dengan menggunakan bahasa pemograman Pyhton dan Wxpyhton sebagai framework Grapichal User interfaceI (GUI) menggunakan aplikasi Pycharm. Dataset yang terdiri dari 985 data telah melewati tahap pree-processing. Hasil evaluasi model menunjukkan bahwa nilai Mean Squared Error (MAE) adalah 0.7561 dan nilai Root Mean Squared Error (RMSE) adalah 1.0634. Ini menunjukkan bahwa akurasi sistem rekomendasi adalah sekitar 91.60% berdasarkan Mean Squared Error (MAE) dan 88.18% berdasarkan Root Mean Squared Error (RMSE).
Kata kunci: Sistem Rekomendasi; Collaborative Filtering; Jakarta; Tempat Wisata; Pycharm.
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