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All Journal KOMPUTIKA - Jurnal Sistem Komputer Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat SmartComp Jurnal Informatika: Jurnal Pengembangan IT Journal of Applied Informatics Science
Ginanjar Wiro Sasmito
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Nursing

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Journal : Journal of Applied Informatics Science

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Drug Data Management Application at Telu Tegal Pharmacy Using Website-Based K-Means Algorithm Rafidatus Salsabilah Qosimah; Ginanjar Wiro Sasmito; Dyah Apriliani
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.34

Abstract

The rapid development of information technology provides great opportunities in increasing the efficiency and accuracy of data management, including in the pharmaceutical sector. Apotek Telu as one of the health service providers requires a system that is able to manage drug sales data effectively and provide useful insights in decision making. This study aims to build a website-based application that not only handles drug data management and sales transactions, but is also equipped with a disease trend analysis feature using the K-Means Clustering algorithm. This method is used to group drug purchase data based on patient purchase patterns, so that it can identify disease trends that often occur in a certain period. This application is built using the Laravel framework for the backend and Blade as the frontend templating system. The test results show that the application is able to manage data efficiently and display the results of disease trend analysis in the form of informative graphic visualizations, so that it can help pharmacies in planning stock and providing more targeted services.
Web-Based Electronic Medical Record System with Patient Activity Recommendation Using K-Nearest Neighbor Algorithm Rama Oktabara; Ginanjar Wiro Sasmito; Dega Surono Wibowo
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.36

Abstract

In the digital era, the use of information technology in the health sector continues to grow, one of which is through the implementation of Electronic Medical Records (EMR). This study develops a web-based EMR system equipped with an automatic patient activity recommendation feature using the K-Nearest Neighbor (KNN) algorithm. Data from 550 patients from Dr. Viandini Clinic, Halo doc, and the internet were used with attributes of disease, age, blood pressure, and activity recommendations. The development process includes data collection, labeling, preprocessing, training and evaluation of the KNN model using the Accuracy@1 and Accuracy@5 metrics. The system is implemented with Laravel Filament and Python-Flask for the recommendation API. The test results show that the system is able to provide relevant recommendations with Accuracy@1 of 90.83% and Accuracy@5 of 95.31%. The application of KNN to this system supports automation, efficiency, and improvement of service quality in clinics and is the basis for the development of more personalized and data-driven digital health services.
Co-Authors Adi Siswanto Dega Surono Wibowo Dyah Apriliani Elang Bimantoro Muhammad Fikri Hidayattullah Musnadil Firdaus Nur Halimatussa'diyah Rafidatus Salsabilah Qosimah Rama Oktabara Yustia Hapsari