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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Inotera Joined Journal (Journal of Informatics Education Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Social Responsibility Projects by Higher Education Forum Jurnal Sosial dan Abdimas Medika Trada Jurnal Masyarakat Madani Indonesia Journal of Medives: Journal of Mathematics Education IKIP Veteran Semarang MANGGALI Joong-Ki
Lingga Kurnia Ramadhani
Universitas Ivet
Religion Aerospace Engineering 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 Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Jurnal Inotera

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Analisis Sentimen terhadap Isu Agama Berdasarkan Komentar Netizen di Instagram Presiden Jokowi Dengan Metode Naive Bayes Classifier Lingga Kurnia Ramadhani; Bajeng Nurul Widyaningrum
Jurnal Inotera Vol. 9 No. 1 (2024): January-June 2024
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol9.Iss1.2024.ID296

Abstract

The presence of Instagram is one of the most popular social media platforms. Make people make a habit of posting photo and video content. In this way, Instagram can become a source of public opinion and sentiment data, which data can be used for social studies. Social studies is still a crucial issue for countries today, including Indonesia, is a matter of religion. Apart from problems regarding religion, public sentiment can be researched from Instagram. The sentiment dataset related to religion is taken from public comments from President Joko Widodo's content regarding Merry Christmas Greetings and Visits to Churches. The analysis system will use sentiment analysis using a method from machine learning, namely the naive Bayes classifier to determine positive & negative sentiments. The comment dataset is 2,600 in which the positive and negative sentiment class datasets are determined manually by experts in the field of linguistics or communication totaling 1,309 to be used as training data. the results of testing the Naïve Bayes classifier training data with a total of 1309 obtained an accuracy prediction of 97.63% and test data where positive & negative sentiment classes had not been determined before hand amounted to 1291 in sentiment analysis obtained positive sentiment 70.56% & negative sentiment 29.44%.
Co-Authors Akhmad Nayazik Andry Irdyansah Bajeng Nurul Widyaningrum Bayu Ariwibowo, Bayu Budiyanto Budiyanto Budiyanto Budiyanto Condro Pargianto Dewi Purnamasari Dewi Purnamasari Didin Herlinudinhaji Didin Herlinudinkhaji, Didin Fitriyani, Anggun Fuad Abdillah Harini Harini Hidayah, Silfiana Lili Marliyah Masruroh, Nila Masalikul Maya Rani, Destri Nila Masalikul Nindita Erwanti Setyaningsih, Sri Sifa, Muhammad Sulchan, Sulchan Yunila Putri Dwi Ariyanti Zusrotin, Zusrotin