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All Journal SmartComp Journal of Applied Informatics Science
Dega Surono Wibowo
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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APLIKASI PENJUALAN PADA CAFE KAMIZUKA KOTA TEGAL DENGAN MENGGUNAKAN VISUAL BASIC 6.0 Ginanjar Wiro Sasmito; Dega Surono Wibowo
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 4, No 2 (2015)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v4i2.287

Abstract

Aplikasi sebagai basis data transaksi penjualan pada Café Kamizuka yang dibuat dalam penelitian ilmiah inimerupakan aplikasi yang bertujuan untuk memudahkan dalam memasukan data, pencarian data, pembuatanlaporan serta memperlancar dan mempercepat proses transaksi pada café tersebut. Dalam penyusunan penulisanlaporan ini menggunakan flowchart dan DFD guna membangun struktur aplikasi data basis data. Dalampembuatan aplikasi ini menggunakan Microsoft Visual Basic 6.0 dan Microsoft Access 2007 yang digunakan.Kata kunci: Aplikasi, Penjualan, Microsoft Visual Basic 6.0, Microsoft Access 2007.
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 Group

Show Abstract | Download Original | Original Source | Check in Google Scholar

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 Ginanjar Wiro Sasmito Rama Oktabara