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All Journal Jurnal Penelitian dan Pengembangan Sains dan Humaniora (JPPSH) Tarbawi : Jurnal Ilmu Pendidikan IJID (International Journal on Informatics for Development) JURTEKSI Jurnal Linguistik Komputasional METIK JURNAL Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Advanced in Information and Industrial Technology (JAIIT) Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research Indonesian Journal of Educational Development (IJED) Malcom: Indonesian Journal of Machine Learning and Computer Science
Hanif, Isa Faqihuddin
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Building of Informatics, Technology and Science

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Analisis Sentimen Terhadap Kualitas Pelayanan Aplikasi In-Drive Menggunakan Metode Naive Bayes Classifier Prakoso, Muhammad Sidiq Bagus; Hanif, Isa Faqihuddin
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6682

Abstract

This research analyzes user sentiment towards the service quality of the In-Drive application using the Naive Bayes Classifier method. A total of 15,000 reviews from the Google Play Store were collected using web scraping techniques from the results of sentiment analysis of the data, 9,665 negative sentiments and 5,335 positive sentiments were found. The data went through a pre-processing stage including cleaning, case folding, stopword removal, tokenizing, and stemming. Naive Bayes algorithm was used to classify the reviews into positive and negative sentiments. Evaluation using the confusion matrix resulted in 76.56% accuracy, 78.26% precision, 87.69% recall, and 82.71% F1 score. These results indicate that most reviews are negative. This research is expected to help In-Drive app developers understand user experience and improve service quality based on automatically available reviews.
Co-Authors Abiansyah, Adillah Halim Affandi, Irfan Ricky Akbar, Mohammad Farhan Apriani, Elsa Bagas Fadillah Bilal, Mohamad Farhan Nurhidayah Fatayan, Arum Fauzan, Muhammad Fathan Fauzan, Nabil Ahmad Fillah, Syaddad Abdurrasyid Firdani, Ella Firdani, Ella Fadila Firman Noor Hasan Fredianto Fredianto Handayani, Isnaini Handika, Yusuf Hapsah, Dido Muhammad Hasbi, Muhammad Adryan Hendriana, Benny Indah Winarni Irdalisa KHOIRUNNISA Marpandi, Pajar Monasari, La Denna Hasri Muhammad Febriansyah Nugroho, Dafa Setyo Oktavianalisti, Falah Pajar Marpandi Pangestu, Muhammad Bagas Adi Prakoso, Muhammad Sidiq Bagus Rivaldi, Muhamad Sadam Saputra, Adrian Maulana Sinduningrum, Estu Subarkah, Achmad Rizqon Tri Wintolo Apoko Widsono, Maulana Yusuf Yaasiin, Muhammad Yusrizal, Najla Qurrata Aini Putri Zildjian, Rachmad Zuhri Halim, Zuhri