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All Journal Journal of Innovation Research and Knowledge
Riska Oktapiana
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Humanities Economics, Econometrics & Finance Education Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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SISTEM REKOMENDASI PEMILIHAN DOSEN PEMBIMBING SKRIPSI BERDASARKAN CONTENT BASED FILTERING PADA PROGRAM STUDI SISTEM INFORMASI UNIVERSITAS BINA DARMA Riska Oktapiana; Mohamad Farozi
Journal of Innovation Research and Knowledge Vol. 5 No. 5 (2025): Oktober 2025
Publisher : Bajang Institute

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Abstract

This Final Project is entitled "A Recommendation System for Selecting Thesis Supervisors Based on Content-Based Filtering in the Information Systems Study Program at Bina Darma University." This research aims to develop a recommendation system to assist students in selecting thesis supervisors based on the alignment between the student's proposed thesis topic and the lecturer's expertise. The method used is Content-Based Filtering with the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm for weighting keywords and Cosine Similarity to calculate the similarity level between the student's thesis title and the lecturer's journal publications. The system is built as a web-based application using PHP and MySQL. Testing results based on 30 data samples show that the system provides accurate recommendations with a Precision of 86.7%, a Recall of 80.0%, and an F1-Score of 83.2%. The highest recommendation score achieved was 98.69 for a lecturer whose journal closely matched the proposed thesis title. The implementation of this system is expected to streamline the thesis supervisor selection process, ensuring a more objective and appropriate match between students and supervisors based on their research fields.
Co-Authors Mohamad Farozi