Haque, Marissa Grace (2024) Analisis Sentimen Terhadap Kontroversi Fatwa MUI Nomor 83 Tahun 2023 Tentang Pemboikotan Produk yang Terafiliasi Israel Muhammad Yasir1* , Marissa Grace Haque2 , Robertus Suraji3 , Istianingsih4 . 1Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia, muhammad.yasir@dsn.ubharajaya.ac.id, 2STIE Indonesia Banking School, Jakarta, Indonesia, marissa.haque@ibs.ac.id. 3Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia, robertus.suraji@dsn.ubharajaya.ac.id 4Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia, istianingsih@dsn.ubharajaya.ac.id *Corresponding Author: muhammad.yasir@dsn.ubharajaya.ac.id1. JEMSI (Jurnal Ekonomi Manajemen Sistem Informasi, 5 (4). 409 -422. ISSN e-ISSN: 2686 - 5238; p-ISSN: 2686 - 4916
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Abstract
The policy issued by MUI, specifically fatwa number 83 of 2023 that addresses the aspect of morality in supporting the palestinian cause, advocates avoiding transactions and the use of products related to Israel, especially countries that support colonization and Zionism as much as possible. This phenomenon has elicited various reaction responses and emerged as a trending subject of discourse across social media platforms including YouTube users. This research aims to develop a sentiment classification model using comparing five classification methods such as Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) to understand the responses to the fatwa. The tool used is Python Google Collab with the dataset coming from YouTube comments. The analysis results showed three sentiment classifications: agree, disagree, and neutral, with accuracy rates of Naive Bayes 75%, Decision Tree 65%, Random Forest 67%, SVM 63%, K-NN 53%. This research is expected to provide in-depth insight into the distribution of sentiments related to the fatwa, as well as a basis for further research in sentiment analysis and public opinion dynamics. Keywords: Sentiment Analysis, Classification, Product Boycott, MUI Fatwa Abstrak: Kebijakan yang dikeluarkan oleh MUI, khususnya fatwa nomor 83 tahun 2023 yang membahas aspek moralitas dalam mendukung perjuangan palestina, menganjurkan untuk menghindari transaksi dan penggunaan produk yang terkait dengan Israel, terutama negara�negara yang mendukung penjajahan dan Zionisme semaksimal mungkin. Fenomena ini telah memunculkan berbagai tanggapan reaksi dan muncul sebagai subjek wacana yang trending di seluruh platform media sosial termasuk pengguna YouTube. Penelitian ini bertujuan mengembangkan model klasifikasi sentimen menggunakan mengkomparasi lima metode klasifikasi seperti Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), dan K-Nearest Neighbor (KNN) untuk memahami respons terhadap fatwa tersebut. Alat yang digunakan adalah Python Google Collab dengan dataset berasal dari komentar YouTube. Hasil analisis menunjukkan tiga klasifikasi sentimen: setuju, tidak setuju, dan netral, https://dinastirev.org/JEMSI Vol. 5, No. 4, Maret 2024 410 | P a g e dengan tingkat akurasi Naive Bayes 75%, Decision Tree 65%, Random Forest 67%, SVM 63%, K-NN 53%. Penelitian ini diharapkan memberikan wawasan mendalam tentang distribusi sentimen terkait fatwa tersebut, serta menjadi dasar untuk penelitian lebih lanjut dalam analisis sentimen dan dinamika opini publik. Kata Kunci: Analisis Sentimen, Klasifikasi, Boikot Produk, Fatwa MU
| Item Type: | Article |
|---|---|
| Subjects: | Prodi S2 Magister Manajemen STIE Indonesia Banking School > Prodi S2 Magister Manajemen |
| Divisions: | Library of Congress Subject Areas > Prodi S2 Magister Manajemen Prodi S2 Magister Manajemen |
| Depositing User: | Mrs. Marissa Grace Haque |
| Date Deposited: | 20 Mar 2024 23:43 |
| Last Modified: | 20 Mar 2024 23:43 |
| URI: | http://repository.ibs.ac.id/id/eprint/7876 |
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