ANALISIS SENTIMEN MAHASISWA TERHADAP LAYANAN KAMPUS DAN FASILITAS KAMPUS MENGGUNAKAN METODE NAIVE BAYES

Semai Kabelen, Bartolomeus (2026) ANALISIS SENTIMEN MAHASISWA TERHADAP LAYANAN KAMPUS DAN FASILITAS KAMPUS MENGGUNAKAN METODE NAIVE BAYES. S1 Teknik Informatika thesis, STMIK Widya Cipta Dharma.

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Abstract

Bartolomeus Semai Kabelen, 2026, Analisis Sentimen Mahasiswa Terhadap Layanan Kampus dan Fasilitas Kampus Menggunakan Metode Naive Bayes, Sekolah Tinggi Manajemen Informatika dan Komputer Widya Cipta Dharma, Dosen Pembimbing Utama: Siti Lailiyah, S.Kom., M.Kom., Dosen Pembimbing Pendamping: Yulindawati, S.H., M.Kom. Kata Kunci: Analisis Sentimen, Naive Bayes, TF-IDF, CRISP-DM, Layanan Kampus, Fasilitas Kampus Penelitian ini bertujuan untuk menganalisis sentimen mahasiswa terhadap layanan kampus dan fasilitas kampus menggunakan metode Naive Bayes. Analisis sentimen dilakukan untuk mengelompokkan opini mahasiswa ke dalam kategori sentimen positif, negatif, dan netral sehingga dapat memberikan gambaran mengenai tingkat kepuasan mahasiswa terhadap layanan dan fasilitas yang disediakan oleh pihak kampus. Penelitian ini menggunakan metodologi CRISP-DM (Cross Industry Standard Process for Data Mining) yang meliputi tahapan business understanding, data understanding, data preparation, modeling, evaluation, dan deployment. Data yang digunakan berupa ulasan atau komentar mahasiswa yang diproses melalui tahapan preprocessing, yaitu case folding, tokenizing, stopword removal, dan stemming. Selanjutnya dilakukan pembobotan kata menggunakan metode TF-IDF (Term Frequency–Inverse Document Frequency) sebelum proses klasifikasi dengan algoritma Naive Bayes. Kinerja model dievaluasi menggunakan confusion matrix untuk memperoleh nilai akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa metode Naive Bayes mampu mengklasifikasikan sentimen mahasiswa dengan baik sehingga dapat memberikan informasi yang bermanfaat sebagai bahan evaluasi dalam meningkatkan kualitas layanan dan fasilitas kampus. Selain itu, hasil penelitian diimplementasikan dalam sebuah aplikasi berbasis web yang dapat membantu proses analisis sentimen secara efektif dan efisien. ============================================================ Bartolomeus Semai Kabelen, 2026, Analysis of Student Sentiment Regarding Campus Services and Facilities Using the Naive Bayes Method, STMIK Widya Cipta Dharma, Main Supervisor: Siti Lailiyah, S.Kom., M.Kom., Co-Supervisor: Yulindawati, S.H., M.Kom. Keywords: Sentiment Analysis, Naive Bayes, TF-IDF, CRISP-DM, Campus Services, Campus Facilities. This study aims to analyze students' sentiments toward campus services and facilities using the Naive Bayes method. Sentiment analysis is conducted to classify students' opinions into positive, negative, and neutral categories in order to provide an overview of student satisfaction with the services and facilities provided by the university. This research adopts the CRISP-DM (Cross Industry Standard Process for Data Mining) methodology, which consists of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The dataset consists of student reviews and comments that undergo preprocessing stages, including case folding, tokenization, stopword removal, and stemming. The processed data are then weighted using the TF-IDF (Term Frequency–Inverse Document Frequency) method before being classified using the Naive Bayes algorithm. Model performance is evaluated using a confusion matrix to measure accuracy, precision, recall, and F1-score. The results indicate that the Naive Bayes method is capable of classifying student sentiments effectively and provides valuable insights that can be used to evaluate and improve the quality of campus services and facilities. Furthermore, the research findings are implemented in a web-based application to facilitate sentiment analysis in an effective and efficient manner.

Item Type:	Thesis (S1 Teknik Informatika)
Additional Information:	Pembimbing 1 : Siti Lailiyah, S.Kom., M.Kom Pembimbing 2 : Yulindawati, S.H., M.Kom
Uncontrolled Keywords:	Analisis Sentimen, Naive Bayes, TF-IDF, CRISP-DM, Layanan Kampus, Fasilitas Kampus
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Teknik Informatika
Depositing User:	Mr Bartolomeus Semai Kabelen
Date Deposited:	06 Aug 2026 07:32
Last Modified:	06 Aug 2026 07:32
URI:	http://repository.wicida.ac.id/id/eprint/6390

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