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All Journal Jupiter Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal sistem informasi, Teknologi informasi dan komputer Infotech Journal Jurnal Ilmiah KOMPUTASI Prosiding Seminar Nasional Teknoka JITK (Jurnal Ilmu Pengetahuan dan Komputer) Indonesian Journal of Applied Informatics Jurnal Riset Informatika Progresif: Jurnal Ilmiah Komputer Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat Infotech: Journal of Technology Information Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Journal of Business and Audit Information System (JBASE) Jurnal Pendidikan dan Teknologi Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Abdi Masyarakat Indonesia SYNERGY: Jurnal Bisnis dan Manajemen Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Jurnal Sistem Informasi dan Manajemen The Indonesian Journal of Computer Science Jurnal Kemuhammadiyahan dan Integrasi Ilmu Jurnal Media Digital Journal of Nexural Intelligence
Ade Davy Wiranata
Universitas Muhammadiyah Prof. Dr. HAMKA Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences

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Journal : progresif jurnal ilmiah komputer

 1 
Analisis Sentimen Ulasan Aplikasi Gojek Menggunakan Support Vector Machine Muhammad Fariz; Ade Davy Wiranata
Progresif: Jurnal Ilmiah Komputer Vol. 22 No. 3 (2026): Juli
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v22i3.3969

Abstract

Evaluating Gojek’s service quality can be achieved by extracting valuable insights from the Google Play Store review corpus. However, the surging volume of data necessitates computational automation to substitute inefficient manual analysis. This study develops a sentiment analysis model using the Support Vector Machine (SVM) algorithm applied to 2,000 scraped reviews. The corpus undergoes comprehensive text preprocessing, rating-based polarity labeling, and lexical feature extraction via Term Frequency-Inverse Document Frequency (TF-IDF). Model validation demonstrates an impressive predictive performance, achieving an accuracy of 86.21%. The distribution of public opinion reveals a dominance of positive sentiment at 57.47%, outperforming the negative cluster at 42.53%. Empirically, the methodological fusion of TF-IDF and SVM is highly reliable as an analytical instrument to dissect consumer perceptions for future service improvements. Keywords: Sentiment Classification; Support Vector Machine; TF-IDF Weighting; Service Evaluation; Gojek. Abstrak Evaluasi kualitas layanan Gojek dapat diekstraksi dari korpus ulasan Google Play Store. Namun, lonjakan volume data menuntut otomatisasi komputasional guna mensubstitusi analisis manual yang inefisien. Penelitian ini mengonstruksi model analisis sentimen menggunakan algoritma Support Vector Machine (SVM) terhadap 2.000 entri ulasan hasil web scraping. Korpus diproses melalui tahapan prapemrosesan teks komprehensif, pelabelan polaritas berbasis rating, serta ekstraksi fitur leksikal mendayagunakan metode Term Frequency-Inverse Document Frequency (TF-IDF). Validasi arsitektur klasifikasi membuktikan performa prediktif yang impresif, dengan raihan akurasi menyentuh 86,21%. Peta distribusi opini publik mendemonstrasikan dominasi sentimen afirmatif (positif) sebesar 57,47%, mengungguli klaster negatif di angka 42,53%. Secara empiris, fusi metodologis antara pembobotan TF-IDF dan SVM terbukti sangat andal sebagai instrumen analitik komputasional guna membedah persepsi konsumen demi mendukung evaluasi perbaikan layanan Gojek di masa depan.
Co-Authors Ahamad Ahdani Ahmad, Irsana Al-Tain, Qolibu Rozak Aldisa, Rima Tamara Anton Maulana Ibrahim Ariyansyah, Riyan Asruddin Asruddin Rudi Asrul Sani Azhar, Nur Chalik Bagus Arfian Laksono Baktiar, Muhammad Yusuf Budiyantara, Agus Catur Nugroho Cleary Syafi'i, Akbar Dede Irawan Deni Mahdiana Dwi Prastiko, Andika Dzikrillah, Ahmad Rizal Elvinaadellia, Elvinaadellia Erizal Erizal Fadhilah, Ash Shoffi Hana Fakhriyyah , Alma Nisa Firdaus Firmansyah Firmansyah, Firadaus Fitria Nur Hasanah Gunadi, Reza Haderiansyah Haderiansyah Hamimuddin, Moch Hilmi Ammar I Ketut Sudaryana, I Ketut Indriani Indriani Intan Murniasih Intan Murniasih Irwansyah Irwansyah Irwansyah Irwansyah Irwansyah Irwansyah iswahyudi Iswahyudi Iswahyudi Jazuli, Umar Jefri Kusuma Rambe M, Tupan Tri MA'MUN, AKHMAD HAQIQI Makmun, Akhmad Haqiqi Maulana, Ninda Baitza Meitiyani, Meitiyani Miftahuddin Miftahuddin Mirza Sutrisno Muhamad Fadilah Rafli Muhammad Efrizal Febriyan Muhammad Erik Muhammad Fariz Muhammad Iqbal Muhammad Yusuf Siregar Mukhtar, Ahmad Amirrudin Murniasih, Intan Muryono, Tupan Tri Mutiarawan, Rezza Anugrah Ninda Baitza Maulana Nunik Pratiwi Pinardi, Sofia Pratiwi, Nunik Rabbani, Abrar Dyah Rachman, Hafid Sulistyo Rafie Rafie Rahardjo, Rafi Diandra Dani Rahmi Imanda Ramza, Harry Rayhan Suwito Rezza Anugrah Mutiarawan Ridha Faiz Ananda Rima Tamara Aldisa Rima Tamara Aldisa Riyan Ariyansah Riza Alamsyah Rizal Rizal Rizki Adi Saputra Rosalina Rosalina Rudy Ansari Saefulloh, Mochamad Saifudin, Yazid Saryanto, Hendi Sinduningrum, Estu soleman soleman Soleman, Soleman Sulistiawati Sulistiawati Syakura, Rais Abdan Widodo, Muh. Adnan Widodo, Muhammad Adnan Wulansari, Aprilya Siti Zulhamdani Zulhamdani