Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Al Hakim, Muchammad Gamma
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
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.
Analisis Sentimen Terhadap Ulasan Pengguna Pada Aplikasi BCA Mobile Menggunakan Metode Naïve Bayes Al Hakim, Muchammad Gamma; Irwiensyah, Faldy
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5343

Abstract

Technological developments have made the payment process easier, which has resulted in a plethora of smartphone applications. As mobile phones become more prevalent, commercial and public organizations are looking to improve the services they provide by implementing mobile-based solutions. The banking industry has seen tremendous expansion, as evidenced by the use of mobile banking solutions by companies such as BCA Bank. Especially in the midst of the pandemic, the BCA Mobile app is an important advancement in online banking that provides benefits and convenience to individuals who frequently transact online. Bank BCA can continue to offer the most useful features to customers while proactively improving services that are currently lacking. This study emphasizes the importance of improving sentiment analysis techniques to understand customer feedback more fully and provide better mobile banking services. This study uses the Naïve Bayes approach to analyze user sentiment towards the BCA Mobile application on the Google Play Store by finding and categorizing user reviews based on the sentiment they exhibit i.e. positive, negative, or neutral is the objective of this study. Through online data mining, 2000 user review data were collected on January 11, 2024, resulting in 1173 sentiments, 163 positive reviews and 1010 negative reviews in total. The Naïve Bayes algorithm produced an accuracy of 86.83%, precision of 52.78%, and recall of 46.91%.
Co-Authors Faldy Irwiensyah, Faldy