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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
M. Afdal
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Perbandingan Algoritma Naïve Bayes Classifier Dan K-Nearest Neighbor Pada Sentimen Review Aplikasi Mobile JKN Citra Annisa; M. Afdal; Tengku Khairil Ahsyar
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6242

Abstract

BPJS Health must provide health services for the people of Indonesia. With the availability of the Mobile JKN application, it is useful to facilitate services for participants of the National Health Insurance-Indonesian Health Card (JKN-KIS). Mobile JKN is an innovation in electronic government health insurance services, making it easier for the public to access services and information quickly in the palm of their hand. With this innovation, many pros and cons flowed from the community, various comments appeared in the Play Store review column, sentiment analysis could be used to assess and rate applications. Therefore, these sentiments can be analyzed into information that can be used as material for evaluation and consideration by BPJS Kesehatan regarding Mobile JKN. This study aims to look at the results of the accuracy comparison between the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms on the sentiment review of the Mobile JKN application on the Play Store. This study used the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) methods with data scrapping techniques to collect Play Store data for the past year, namely 2,847 data and divided into 3 classes, namely positive, neutral and negative. Distribution of data using 10 K-Fold Cross Validation so that a comparison of the accuracy level of the Naïve Bayes Classifier (NBC) is 61.15%, while the accuracy level of K-Nearest Neighbor (KNN) is 87.59%.
Analisis Sentimen Layanan J&T Express pada Sosial Media X Menggunakan Algoritma Naïve Bayes Clasifier dan K-Nearest Neighbor Muhamad Ilham Priady; M. Afdal; Inggih Permana; Zarnelly Zarnelly
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7721

Abstract

The demand for goods delivery services is increasing along with the widespread use of e-commerce platforms for buying and selling. One of the popular and frequently used delivery service providers is J&T Express. Until now, J&T has had a wide service coverage. However, various customers also have complaints that are often conveyed through social media X. For this reason, this study conducted a sentiment analysis of J&T Express user opinions on social media X using the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms. Data collection was carried out through scraping over a time span from January 1, 2023 to December 1, 2024, resulting in a total of 1,000 data points. The modeling results show that the NBC algorithm outperforms KNN, achieving an accuracy of 72.30%, a precision of 74.76%, and a recall of 72.30%. Meanwhile, the KNN algorithm with the best parameters (K = 9) only has an accuracy of 67.29%, precision of 69.46%, and recall of 67.29%. Then the results of the analysis show that J&T user opinions are dominated by negative sentiment (42.20%), followed by positive sentiment (38.70%) and neutral sentiment (19.10%). Further analysis based on five variables was also conducted and an understanding of J&T's weaknesses, namely in the service aspect, with the highest negative sentiment (21.0%). On the other hand, the user experience aspect is an advantage with the most positive sentiment (16.8%). The data visualization results also indicate that there are dominant customer complaints about the delay in the delivery process. However, customers also appreciate the speed and security of the delivery of goods. These findings provide valuable insights for J&T Express to conduct evaluations and improvements, especially in the service aspect, to improve overall customer satisfaction and experience.
Co-Authors Citra Annisa Inggih Permana Muhamad Ilham Priady Tengku Khairil Ahsyar Zarnelly Zarnelly