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All Journal Media Statistika JURNAL SISTEM INFORMASI BISNIS Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) bit-Tech G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems ESTIMASI: Journal of Statistics and Its Application Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Journal of Technology and Informatics (JoTI) International Journal of Data Science, Engineering, and Analytics (IJDASEA) International Journal Of Computer, Network Security and Information System (IJCONSIST) Journal of Information Systems and Technology Research Journal of International Conference Proceedings Journal of Data Mining and Information Systems Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal PETISI (Pendidikan Teknologi Informasi) Joong-Ki
Kartika Maulida Hindrayani
Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology

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Journal : Journal of Data Mining and Information Systems

 1 
Deteksi Sentimen Komentar Aplikasi Gobis Suroboyo dengan Metode Naive Bayes dan Metode Regresi Logistik Elmaliyasari, Shifa; Alzam, Muhammad Arsyad; Pratiwi, Nanda Aulia; Wara, Shindi Shella May; Hindrayani, Kartika Maulida
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 2 (2025): August 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i2.4691

Abstract

This research discusses sentiment analysis of user comments on the Gobis Suroboyo application using the Naive Bayes algorithm and Logistic Regression. Data was obtained through web scraping method from Google Play Store, with a total of 1,015 comments which then went through text pre-processing such as data cleaning, case folding, stemming, normalisation, filtering, tokenizing, and feature selection using TF-IDF. Sentiment labels were determined based on user ratings, with ratings above 3 as positive and 3 and below as negative. The results show that the Naive Bayes algorithm is better at classifying positive sentiment with a precision of 81% and f1-score of 77%, while Logistic Regression excels at negative sentiment with a precision of 82% and f1-score of 82%. The WordCloud visualisation shows dominant words such as “app”, “good”, and “bus stop” that reflect users attention to the app features and transportation services. The findings show that both algorithms have competitive and reliable performance for evaluating public opinion on comment-based digital services. This research is expected to be a reference for app developers and local governments in improving the quality of digital public services.
Analisis Sentimen Ulasan Aplikasi Maxim Merchant dengan Support Vector Machine (SVM) dan Random Forest Rizkiyah, Selly; Rizqin, Indira Zein; Putri, Milla Akbarany Baktiar; Wara, Shindi Shella May; Hindrayani, Kartika Maulida
JDMIS: Journal of Data Mining and Information Systems Vol. 4 No. 1 (2026): February 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v4i1.4765

Abstract

The development of digital technology, especially mobile devices, has led to an increase in application-based services. One important aspect in app development is to deeply understand user perception and satisfaction. This study aims to analyze user sentiment towards the Maxim Merchant application based on reviews obtained from the Google Play Store platform. A total of more than 2800 Indonesian-language reviews were collected using web scraping techniques. The review data was processed through pre-processing stages such as text cleaning, normalization, tokenization, removal of unimportant words, and stemming. Sentiments are categorized into positive and negative based on the review score, where scores of 1 to 3 are considered negative, and scores of 4 and 5 are considered positive. Word cloud visualization is used to show the dominant words of each sentiment category. The data is then converted into numerical form using TF-IDF and selected using the Chi-Square method. Classification was performed using Support Vector Machine and Random Forest algorithms. The evaluation results show that the Support Vector Machine algorithm performs better in classifying sentiment, especially in handling high-dimensional text data.
Co-Authors Adhigiadany, Chelsea Ayu Afandy, Selena Nurmanina Afidria, Zulfa Febi Ahmad, Davin Anezta Aisyah Kirana Putri Isyanto Alfiansyah , Achmad Dzulfiqar Altetiko, Faizal Johan Alzam, Muhammad Arsyad Amelia, Meisya Vira Amri Muhaimin Aviolla Terza Damaliana Azizah, Alisa Jihan Betty Dewi Puspasari Bhalqis, Anissa Andiar Brescia Ayundina Yuniarossy Budi, Aditya Septa Burhan Syarif Acarya Christina Halim Christina, Enzelica Vica Damaliana, Aviolla Terza Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Elmaliyasari, Shifa Eristya Maya Safitri Fahrudin, Tresna Maulana Fajar Ramadhani Fernando, Moch. Firman Fortuna, Edelin I Gede Susrama Mas Diayasa idhom, Mohammad Imelda Widya Ningrum Isyanto, Aisyah Kirana Putri Jauharis Saputra, Wahyu Syaifullah Kartini Kartini Made Hanindia Prami Swari Maulana F, Tresna Mohammad Idhom Ningrum, Imelda Widya Ningrum, Lisya Septyo Nur Aini Rakhmawati Pakpahan, Vera Febrianti Pratiwi, Nanda Aulia Prismahardi Aji Riyantoko Purwadwika, Reza Sadiya Putri, Milla Akbarany Baktiar Putro, R. Kokoh H. rachmanto, Nugroho Fajar Rafli, Muhammad Riskiyah, Ameliyah Risnaldy Novendra Irawan Riyantoko, Prismahardi Aji Rizkiyah, Selly Rizqin, Indira Zein Safira, Alya Mirza Saputra, Wahyu S. J. Saputra, Wahyu Syaifullah Jauharis Shindi Shella May Wara Tresna Maulana F Tresna Maulana Fahruddin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Trimono Trimono, Trimono Wahyu Syaifullah JS Wardati, Nanda Kurnia Wibowo, Muhammad Bagas Satrio