Article Per Year (5 Year)
p-Index From 2021 - 2026
1.789
P-Index
This Author published in this journals
All Journal INFORMAL: Informatics Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Network Engineering Research Operation [NERO] JUTIK : Jurnal Teknologi Informasi dan Komputer International Journal of Community Service Learning Building of Informatics, Technology and Science Jurnal Mantik Indonesian Journal of Data and Science Jurnal Info Sains : Informatika dan Sains JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Ariana, Anak Agung Gede Bagus
Program Studi Sistem Komputer, STMIK STIKOM Indonesia Jl Tukad Pakerisan No. 97, Denpasar, Bali
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Mantik

 1 
Sentiment analysis of mobile jkn application reviews using the multinomial naïve bayes algorithm Paratama, I Putu Dedy Eka; Bagus Ariana, Anak Agung Gede; Labasariyani, Ni Luh Putu; Rahayu G, Ni Luh Wiwik Sri
Jurnal Mantik Vol. 9 No. 1 (2025): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i5.6221

Abstract

Digital transformation in healthcare services has significantly improved public access to information. The Mobile JKN (National Health Insurance) application was developed to facilitate easier access to healthcare services. However, its effectiveness needs to be evaluated through sentiment analysis of user reviews on the Google Play Store. This study aims to determine user sentiment toward the Mobile JKN application using the Multinomial Naïve Bayes method, a commonly used classification technique in machine learning. The data was collected through web scraping and processed through several stages, including tokenization, stopword removal, and text normalization. Sentiment labels were then assigned using a lexicon-based approach, specifically the INSET lexicon, before classification. The analysis revealed that the majority of reviews expressed negative sentiment, particularly concerning application performance, technical issues, and healthcare service quality. The results also showed that the Multinomial Naïve Bayes model was able to classify the data with an accuracy of 81%. Therefore, the Mobile JKN application still requires technical improvements and service enhancements to provide a better user experience. This study offers valuable insights for developers and can serve as a foundation for policy-making to improve the quality of digital healthcare services
Co-Authors Agus Perdana Windarto Anak Agung Gde Ekayana Andika, I Gede Christina Purnama Yanti Desak Putu Parmiti Dewa Gede Agus Putra Prabawa Evi Dwi Krisna . Gde Andrayuga Pramaditha Tenaya I Dewa Made Adi Baskara Joni I Gede Adnyana I Gede Adnyana I Gede Handi Raharja I Gede Iwan Sudipa I Gede Rian Lanang Oka I Gusti Made Ngurah Desnanjaya I Kadek Dwi Gandika Supartha I ketut Gede Darma Putra I Nyoman Buda Hartawan I Nyoman Jayanegara I Putu Adi Pratama, I Putu Adi I Wayan Ardana I WAYAN SUDIARSA Linawati Linawati Merta, I Kadek Priyana Adi NI LUH PUTU LABASARIYANI Ni Luh Wiwik Sri Rahayu Ginantra Ni Made Mila Rosa Desmayani, Ni Made Mila Rosa Ni Wayan Suniasih Njoera, Yahya Alexander Djo Paratama, I Putu Dedy Eka Putri, Ida Ayu Putu Calista Kencana Putu Risanti Iswardani Rahayu G, Ni Luh Wiwik Sri Ridho, Ihda Innar Sutarwiyasa, I Ketut Wayan Sauri Peradhayana Wiyata Putra, I Dewa Putu Gede