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Application of SMART Method and Dashboard Visualization for Student Code of Conduct Violations Devega, Mariza; Darmayunata, Yuvi; yuhelmi, Yuhelmi
Sistemasi: Jurnal Sistem Informasi Vol 13, No 5 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i5.4593

Abstract

In order to handle student discipline infractions at school, this project intends to design a decision support system (DSS) based on the Simple Multi-Attribute Rating Technique (SMART) technique integrated with a graphical dashboard. A variety of visual tools, such as scatter plots, heatmaps, pie charts, bar charts, and line charts, are used to evaluate and display violation data. This integration's primary goals are to make monitoring and analysis faster and more efficient and to support decision-making with regard to student infractions. The findings demonstrate how the SMART approach and visualization dashboard can be used to manage violation data more effectively, provide a better knowledge, and speed up reactions to infractions. This technique makes it easier for schools to spot trends in infractions, choose the best course of action for corrective measures, and enhance overall student discipline. It is anticipated that this system will enable discipline management in a learning environment in an efficient manner.
ANALISIS SENTIMEN TERHADAP PENGGUNAAN APLIKASI MOBILE JKN DENGAN PENDEKATAN RANDOM FOREST CLASSIFIER Sri Febrianti, Zahra; Devega, Mariza
ZONAsi: Jurnal Sistem Informasi Vol. 7 No. 3 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode September 2025
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/gf3ekc32

Abstract

Health is a fundamental need for all people. In an effort to ensure equitable access to health insurance services in Indonesia, the government has assigned BPJS Kesehatan as the national health insurance provider. As part of its digital innovation, BPJS Kesehatan introduced the Mobile JKN application to make it easier for the public to access healthcare services online. However, the implementation of this application still raises various complaints, such as login difficulties, update disruptions, and limited features, as reflected in predominantly negative user reviews. To objectively assess public perception, this study conducted sentiment analysis on 5,000 user reviews of Mobile JKN obtained from the Google Play Store. The analysis process included cleaning, tokenizing, stopword removal, stemming, labeling, and word weighting using TF-IDF. Classification was performed using the Random Forest Classifier algorithm. The results showed that out of 976 test data, 883 were correctly predicted and 93 were misclassified, with an accuracy of 90.47%, precision of 90.15%, recall of 90.47%, and an F1-score of 89.90%. These findings demonstrate that Random Forest is effective in identifying both positive and negative sentiments and can serve as a basis for the future development of the Mobile JKN application