Article Per Year (5 Year)
p-Index From 2021 - 2026
1.547
P-Index
This Author published in this journals
All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Infotech: Journal of Technology Information AMMA : Jurnal Pengabdian Masyarakat Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Faldy Irwiensyah, Faldy
Departemen Obstetri & Ginekologi FKUI Rumah Sakit Cipto Mangunkusumo (RSCM) - Jakarta
Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Building of Informatics, Technology and Science

 1 
Analisis Sentimen Terkait Konflik Palestina-Israel Pada Media Sosial X Menggunakan Algoritma Naïve Bayes Classifier Simamora, Silvia Damayanti; Irwiensyah, Faldy; Hasan, Firman Noor
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5344

Abstract

The conflict between Palestine and Israel has been ongoing for approximately 76 years, during which the Zionist movement has attempted to establish a Jewish homeland in Palestinian territory. In October 2023, news about this conflict resurfaced and has continued up until June 2024. This issue has drawn global attention, including from the Indonesian public. On the social media platform X, numerous comments and posts both negative and positive regarding the Palestine-Israel conflict have appeared as a result of the ongoing challenges faced by Palestine. This study aims to analyze the sentiment expressed on the social media platform X regarding the Palestine-Israel conflict. The data collected focuses solely on comments and posts from Indonesia, totaling 1,715 entries. The study employs the Naïve Bayes Classifier algorithm, with an 80% to 20% ratio of training data to test data, following a pre-processing phase. The results of this study indicate an accuracy of 94%, precision of 91%, recall of 100%, and an F1-Score of 95%. The analysis reveals a positive sentiment, suggesting that the Indonesian public's response on the social media platform X predominantly shows positive support towards Palestine
Analisis Sentimen Terhadap Ulasan Pengguna Pada Aplikasi Traveloka Menggunakan Metode Naïve Al Hakim, Muchammad Gamma; Irwiensyah, Faldy
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6119

Abstract

The proliferation of user-generated reviews on digital platforms provides in-depth information to improve services. The purpose of this study is to apply the Naïve Bayes approach to analyze the sentiment of user evaluations of the Traveloka application sourced from the Google Play Store. Through online search, 10,000 evaluations were collected. Case folding, stopword elimination, tokenizing, and stemming are some of the pre-processing techniques used. Based on the review scores, the sentiment data was classified into two groups: positive and negative. Furthermore, the Naïve Bayes model was used for classification, and a confusion matrix was used to assess the results. The results showed an accuracy of 89.35%, precision of 88.44%, recall of 95.05%, and F1-Score of 91.62%. These results demonstrate the effectiveness of the Naïve Bayes approach in categorizing user reviews, providing Traveloka with important information about customer perceptions and how to improve their service quality. The findings from this study are expected to be the basis for future advancements in sentiment analysis on travel and accommodation-related applications.
Co-Authors Al Hakim, Muchammad Gamma Febriandirza, Arafat Firman Noor Hasan Pratama, Ridho Danang Budi Putri Lestari, Putri Rahman, Rafi Fadhlur Simamora, Silvia Damayanti Sunata, Muhamad Hafidz Ardian