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All Journal Kalbiscientia Jurnal Sains dan Teknologi Jurnal Ilmu-Ilmu Kehutanan Safari : Jurnal Pengabdian Masyarakat Indonesia Prosiding Seminar Nasional Pendidikan, Bahasa, Sastra, Seni, dan Budaya Bhinneka: Jurnal Bintang Pendidikan dan Bahasa JURNAL SAINS dan INOVASI PERIKANAN PENG: Jurnal Ekonomi dan Manajemen Pemuliaan Keadilan JKM-Bid: Jurnal Kesehatan Masyarakat kebidanan IPSSJ INTERACTION: Jurnal Pendidikan Bahasa
Putri Cahyani
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Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Kalbiscientia Jurnal Sains dan Teknologi

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Perbandingan Performa Algoritma Naïve Bayes, SVM dan Random Forest Studi Kasus Analisis Sentimen Pengguna Sosial Media X Putri Cahyani; Lufty Abdillah
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 11 No. 02 (2024): Jurnal Sains dan Teknologi
Publisher : Research and Community Service INSTITUT TEKNOLOGI DAN BISNIS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbiscientia.v11i02.3624

Abstract

Sentiment analysis was explored to understand social media users' opinions towards the Indonesian Capital City (IKN) through the X platform with machine learning and lexicon-based algorithms. This research uses three algorithms: Naïve Bayes, Support Vector Machine (SVM), and Random Forest. The aim of this research is to test and compare the performance of the three algorithms to determine the best in classifying sentiment data from the X platform. The data consists of 10,000 tweets collected using the crawling method with the Python Harvest Library and Node.js, using keywords related to IKN. Based on the algorithm performance test, it was concluded that SVM had the highest performance compared to Naïve Bayes and Random Forest, producing an accuracy of 87%, precision 87%, recall 87%, and f-1 score 87%. This research uses the CRISP-DM Data Mining framework to ensure a structured and systematic approach to the analysis process.
Perbandingan Performa Algoritma Naïve Bayes, SVM dan Random Forest Studi Kasus Analisis Sentimen Pengguna Sosial Media X Putri Cahyani; Lufty Abdillah
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 11 No. 02 (2024): Jurnal Sains dan Teknologi
Publisher : Research and Community Service UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbiscientia.v11i02.3624

Abstract

Sentiment analysis was explored to understand social media users' opinions towards the Indonesian Capital City (IKN) through the X platform with machine learning and lexicon-based algorithms. This research uses three algorithms: Naïve Bayes, Support Vector Machine (SVM), and Random Forest. The aim of this research is to test and compare the performance of the three algorithms to determine the best in classifying sentiment data from the X platform. The data consists of 10,000 tweets collected using the crawling method with the Python Harvest Library and Node.js, using keywords related to IKN. Based on the algorithm performance test, it was concluded that SVM had the highest performance compared to Naïve Bayes and Random Forest, producing an accuracy of 87%, precision 87%, recall 87%, and f-1 score 87%. This research uses the CRISP-DM Data Mining framework to ensure a structured and systematic approach to the analysis process.
Co-Authors Aditya Hikmat Nugraha Aldy Reynaldy Leuwyh Budiharjo Budiharjo Dedy Khaerudin Emma Yunika Puspasari Ewi Irfani Ganjar Sidik Ganjara Hasan Eldin Adimu Hasidu, La Ode Abdul Fajar Ika Lestari Ilham Antariksa Tasabaramo Innes Annisa’ Istiqomah La Sunra Lufty Abdillah Maharani Mubarak Muhammad Afuza Fauzan Adhim Muhammad Mardhiansyah Muhammad Ridho Fudoil Ndorotul Ainy, Fadya Niskan Walid Masruri Nur Fajrie Nurbaety Pebriandi, Pebriandi Puspita Anggi Kurnianita Riska Sahril Nur Sri Astuti Sumaryanto Zulkarnain