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All Journal Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Kursor TEKNOLOGI INFORMASI Sistemasi: Jurnal Sistem Informasi SMARTICS Journal Jurnal TAM (Technology Acceptance Model) INOVTEK Polbeng - Seri Informatika PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Teknologi Terapan J-Dinamika: Jurnal Pengabdian Kepada Masyarakat EDUMATIC: Jurnal Pendidikan Informatika MULTINETICS Jurnal Pengabdian Polinema Kepada Masyarakat Buguh: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi Paradigma Jurnal ELTEK Jurnal Teknik Ilmu dan Aplikasi Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Informatika Polinema (JIP) Jurnal TAM (Technology Acceptance Model) Jurnal Komtika (Komputasi dan Informatika)
Imam Fahrur Rozi
Politeknik Negeri Malang
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture 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 Library & Information Science Mechanical Engineering Public Health Social Sciences

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Journal : Jurnal Ilmiah Kursor

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Comparison of Feature Extraction in Support Vector Machine (SVM) Based Sentiment Analysis System Rozi, Imam Fahrur; Maulidia, Irma; Hani’ah, Mamluatul; Arianto, Rakhmat; Yunianto, Dika Rizky; Ananta, Ahmadi Yuli
Jurnal Ilmiah Kursor Vol. 13 No. 1 (2025)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v13i1.417

Abstract

Sentiment analysis plays a crucial role in natural language processing by identifying and categorizing opinions or emotions conveyed in textual data. It is widely applied across diverse fields such as product review analysis, social media monitoring, and market research. To enhance the accuracy and reliability of sentiment classification, various methods and feature extraction techniques have been explored. This study investigates the use of Support Vector Machine (SVM) for sentiment analysis, comparing three feature extraction techniques: Term Frequency-Inverse Document Frequency (TF-IDF), Bag of Words (BoW), and Word2Vec. Our findings indicate that SVM performs effectively with all three feature extraction methods, with TF-IDF yielding the highest accuracy at 0.79. Although the BoW method showed competitive results, it slightly trailed TF-IDF in k-fold validation. Word2Vec, however, exhibited the lowest performance, achieving a maximum accuracy of 0.69. A comparative analysis of accuracy, precision, recall, and F1-score highlight the superiority of TF-IDF in delivering consistent and accurate results. Further statistical analysis using ANOVA revealed no significant differences between the models across any of the evaluation metrics. Additionally, the evaluation was conducted under several scenarios, including tests on balanced and imbalanced datasets, varying dataset sizes, and different CCC parameter values for SVM. These scenarios provided deeper insights into the factors influencing the system's performance, reinforcing that TF-IDF combined with SVM remains the most effective approach in this study.
Co-Authors Abdul Muhsyi Agung Nugroho Ahmad Adil Faruqi Al Huda, Muhammad Iqbaluddin Ali Rahman Wibisana, Hafid Amalia, Astrifidha Rahma Ananta, Ahmadi Yuli Angga Aditya Indra Wiratmaka Anggraini, Serly Anita Ivianti Annisa Taufika Firdausi Annisa Taufika Firdausi Arief Prasetyo Arifin, Muh. Syamsul Atiqah Nurul Asri Batubulan, Kadek Suarjuna Budiarti, Arry Budiarti, Mahanani Nur Bulan, Novita Putri Dianti, Amelia Dika Rizky Yunianto Dimas Firman AL-Hafiidh Donavan, Khasadika Dwi Puspitasari Ekojono Ekojono Ekojono, Ekojono Elok Nur Hamdana Endah Septa Sintiya Erfan Rohadi Fahmy Ainun Nazilla Faisal Rahutomo Faishal Rahutomo Farida Ulfa Faruqi, Ahmad Adil Gaghana, Geo Alfriza Hakim, Muhammad Ilham El Hapsari, Ratih Indri Haris Setiyono Ika Kusumaning Putri Indra Wiratmaka, Angga Aditya Iqbal Alfahmi, Muhammad Balya Irawan, Ferry Buyung Bakhtiar Irvan Wahyu Nurdian Islamiyah, Khalimatul Ivianti, Anita Khalimatul Islamiyah Khansa, M. Roid Billy Khasadika Donavan Mahanani Nur Budiarti Mamluatul Hani’ah Mardiana, Aida Milati Maulidia, Irma Millenia Rusbandi Moch. Sholeh, Moch. Mochamad Panggih Nirwanto Mufidah, Nursita Al Muhammad Afif Hendrawan Muhammad Alfahmi Nazilla, Fahmy Ainun Nirwanto, Mochamad Panggih Novia Puspitasari Nugraeni, Arin Kistia Nur Khozin Nurdian, Irvan Wahyu Nursita Al Mufidah Nurudin Santoso Odhitya Desta Odhitya Desta Triswidrananta Odhitya Desta Triswidrananta Pangestu Nur Mirzha Pramana Yoga Saputra Pramudhita, Agung Nugroho Purnomo, Fadjar Rahmad, Cahya Rahmadhany, Tahta Reza Rahman, Muhammad Arif Rakhmat Arianto Ridwan Rismanto Rokhman, Syaiful Rosa Andrie Asmara Rudy Arianto, Rudy Rudy Ariyanto Rudy Ariyanto Rusbandi, Millenia Santoso, Nurudin Saputra, Zainal Ulu Prima Sholiha, Afifah Syaiful Rokhman Tahta Reza Rahmadhany Taufika Firdausi, Annisa Thalia Amira Rifda Usman Nurhasan Vipkas Al Hadid Firdaus Vivi Nur Wijayaningrum Vivin Ayu Lestari Viyus, Vinan Wibowo, Rahmat Catur Widito, Sasmojo Wijanarko, Eko Setio Yan Watequlis Syaifudin Yogi Kurniawan Yoppy Yunhasnawa Yuri Ariyanto Yushintia Pramitarini Zakaria, Arief Syukron Zanuar Hanif Rachmat Adi