JSAI (Journal Scientific and Applied Informatics)

Sentiment Analysis of the MPStore Application Using Logistic Regression and LDA Algorithms

2025-12-09T15:28:34+08:00

The rapid growth of the digital economy encourages user satisfaction as the key to successful application innovation. Within technopreneurship, understanding user sentiment is essential for sustainable product development. This study aims to analyze sentiment and identify the deter-minants of user satisfaction regarding the MPStore application based on reviews from the Google Play Store. Review data were collected via scraping and analyzed using Logistic Regression (LR) for sentiment classification (positive, negative, neutral) also Latent Dirichlet Al-location (LDA) for satisfaction topic extraction. The result shows that the LR model achieved an accuracy of 88.5%. The LDA analysis also successfully revealed eight main topics, includ-ing ease of use, transaction speed, and technical obstacles (errors, login, balance issues). Over-all, a majority of users hold a positive perception of MPStore's efficiency and ease of transac-tions. This study concludes that the combination of sentiment analysis and topic modeling is effective for explaining the level of user satisfaction and providing a strategic foundation for digital application developers.

Retrieval-Augmented Generation Method in the Development of Large Language Model Chatbots for the Anambas Civil Registry Public Information Service

2025-12-15T14:16:10+08:00

Population administration services in the Anambas Islands Regency face significant challenges related to limited information access caused by geographical conditions. Service information on the official Disdukcapil website, which is passive, often makes it difficult for the public to obtain fast and relevant answers. This condition leads to service queue buildups and potentially decreases public satisfaction. As a solution, an intelligent chatbot application based on a Large Language Model (LLM) with a Retrieval-Augmented Generation (RAG) approach was developed. This method effectively combines precise information retrieval capabilities from a document database with the LLM's natural language understanding ability to produce contextual answers. The system's development process was carried out using the LangChain framework, Chroma vector store, and was integrated into a web interface as the frontend. Official Disdukcapil service information was processed through chunking, embedding, and RAG pipeline creation stages. The results showed that the chatbot was able to respond to inquiries about population services accurately and efficiently. Based on evaluations using the BERTScore metric, the system obtained average scores of 98,5% for Precision, 99,1% for Recall, and 98,8% for F1-Score. This system can be accessed from anywhere, greatly assisting people in remote areas, and serves as a potential initial prototype to support the digitization of public services in archipelago regions.

Information Technology, Social Media, and Digital Transformation on the Performance of Laundry MSMEs in Batam City

2025-12-15T14:10:30+08:00

This study examines the effects of information technology, social media, and digital transformation on the business performance of laundry MSMEs in Batam City using a quantitative associative approach. Data were collected from 94 owners or managers of laundry MSMEs through questionnaires and analyzed using IBM SPSS Statistics 25. Classical assumption tests indicated that the data were normally distributed and free from multicollinearity and heteroscedasticity. Simultaneous testing showed that information technology, social media, and digital transformation jointly have a significant effect on business performance (F = 4.588; p = 0.005). However, partial test results revealed that only social media has a positive and significant effect on business performance, while information technology and digital transformation do not show significant effects. These findings suggest that in small-scale service MSMEs, market-oriented digital tools are more effective in improving business performance than complex internal technology adoption.