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All Journal International Journal of Evaluation and Research in Education (IJERE) Cakrawala Pendidikan Jurnal Buana Informatika Kubik Jurnal Sains Matematika dan Statistika Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal JRPM (Jurnal Review Pembelajaran Matematika) Jurnal Matematika: MANTIK Al-MARSHAD: Jurnal Astronomi Islam dan Ilmu-Ilmu Berkaitan BAREKENG: Jurnal Ilmu Matematika dan Terapan Mathvision : Jurnal Matematika Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Journal of Mathematics Education and Science Leibniz: Jurnal Matematika Jurnal Matematika Integratif Engagement: Jurnal Pengabdian Kepada Masyarakat International Journal of Computing Science and Applied Mathematics-IJCSAM
Ahmad Hanif Asyhar
UIN Sunan Ampel Surabaya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Jurnal Buana Informatika

 1 
Analisis Sentimen Ulasan Aplikasi Jamsostek Mobile Menggunakan Metode Support Vector Machine Vina Fitriyana; Lutfi Hakim; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar
Jurnal Buana Informatika Vol. 14 No. 01 (2023): Jurnal Buana Informatika, Volume 14, Nomor 1, April 2023
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v14i01.6909

Abstract

Sentiment Analysis of Jamsostek Mobile Application Reviews Using the Support Vector Machine Method. Today's technology is evolving quickly, leading to new developments that have helped produce JMO and other mobile applications that can be useful to Indonesians. The reviews or comments in the JMO can be used as a gauge for quality and user satisfaction. This study aims to analyze the quality of JMO applications and classify reviews or opinions into positive, negative, and neutral categories through sentiment analysis. The Support Vector Machine method is used in this analysis process with a linear kernel approach to determine the level of accuracy of classifying JMO application reviews. Research shows that classifying the SVM method against sentiment analysis of reviews or JMO application reviews produces the best accuracy scores, obtaining results with accuracy of 96%, precision of 92%, recall of 96%, and f1-score of 94%, while for the results of most reviews are positive category reviews with a total of 17.571.Keywords: sentiment analysis, JMO, SVM, linear kernel   Perkembangan pesat teknologi saat ini memunculkan inovasi baru untuk menciptakan berbagai aplikasi mobile yang dapat memberi kemudahan bagi masyarakat Indonesia, salah satunya yaitu JMO. Penelitian ini bertujuan untuk menganalisis kualitas aplikasi JMO dan mengklasifikasikan ulasan atau opini kedalam kategori positif, negatif dan netral melalui analisis sentimen. Metode Support Vector Machine digunakan pada proses analisis ini dengan pendekatan kernel linear untuk mengetahui tingkat akurasi dari pengklasifikasian ulasan aplikasi JMO tersebut. Penelitian menunjukkan bahwa pengklasifikasian metode SVM terhadap analisis sentimen ulasan atau review aplikasi JMO menghasilkan nilai akurasi terbaik, didapatkan hasil dengan accuracy 96%, precision 92%, recall 96%, dan f1-score 94%, sedangkan untuk hasil ulasan terbanyak adalah ulasan berkategori positif dengan jumlah 17.571.Kata Kunci: analisis sentimen, JMO, SVM, kernel linear
Co-Authors Abdulloh Hamid Abdulloh Hamid Adikuasa, M. Biyadihie Adyanti, Deasy Adyanti, Deasy Alfiah Ahmad Hidayatullah Ahmad Umar Ahmad Zaenal Arifin Ahmad Zoebad Foeady Ali Ridho Anistya, Mery Arifin, Ahmad Zaenal Deasy Adyanti Deasy Alfiah Adyanti Dian C. Rini Novitasari Dian Yuliati Dian Yuliati Fajar Darwis Dzikril Hakimi FAJAR SETIAWAN Fajar Setiawan Fanani, Aris Farida, Yuniar Firmansjah, Muhammad Fitria Febrianti Foeady, Ahmad Zoebad Fransisca, Velicia Gita Purnamasari R Hani Khaulasari Hidayati, Syahrotul Hilmi, Moh. Aditya Sirojul ian Candra Rini Novitasari Krisnawan, Alvin Kusaeri Kusaeri Lia Puspita Sari Lubab, Ahmad Lutfi Hakim Lutfi Hakim M. Hasan Bisri Maulidya, Rahmania Moch. Noor Affan Anshori Moh. Hafiyusholeh Muhammad Busyro Karim Muhammad Busyro Karim, Muhammad Busyro Muhammad Fahrur Rozi Muhammad Iqbal Widiaputra Muhammad Thohir Mukti, Audyra Dewi Puspa Nanang Widodo Nisa, Titin Faridatun Novitasari , Dian Candra Rini Novitasari, Dian C Rini Nur Aulia, Shofinatul Wahdah Nurissaidah Ulinnuha Putri Oktavia, Nabiilah Putri, Anindya Maya Putri, Risma Madurahma Putroue Keumala Intan Rifa Atul Hasanah Rini Novitasari, ian Candra Ririn Komaria Rozi, Muhammad Fahrur Sari, Dian Candra Rini Novita Sari, Firda Yunita Setiawan, Fajar Suwanto Suwanto Utami, Wika Dianita Vina Fitriyana Wahyudi, Sharenada Norisdita Widiaputra, Muhammad Iqbal Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wiratama, Aqshal Tegar Yuliati, Dian Yuliati, Dian Yusuf, Ahmad Yuyun Monita Zainullah Zuhri