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All Journal JSR : Jaringan Sistem Informasi Robotik Jurnal Komtekinfo Knowbase : International Journal of Knowledge in Database Smart Humanity: Jurnal Pengabdian Masyarakat
Ideal, M. Agung Vafky
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Journal : Knowbase : International Journal of Knowledge in Database

 1 
Utilization of The Qr-Code on The Santri Id-Card as The Santri’s Personal Data Code Ideal, M. Agung Vafky
Knowbase : International Journal of Knowledge in Database Vol. 2 No. 2 (2022): December 2022
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v2i2.6018

Abstract

Data management has always been a challenge in all aspects, including the management of students' personal information. Building an information system capable of producing student Id-cards equipped with a QR-code enables the use of the QR-code on the student Id-card as a student personal data code. This study aims to build a system to make it easier to make student ID-cards, store personal data, and data on student semester scores. The QR-code on the student's ID card serves as a medium for quickly conveying information encoded with Uniform Resource Locators (URL). Santri can scan the QR-Code with a smartphone device that has a QR-code scanning app installed. The Research and Development (RnD) version of ADDIE was used in this study (Analyze, Design, Develop, Implement, Disseminate). The application was created with the sublimetext software, the codeigniter framework, and CSS bootstrap as the front end. For the validity test, Aiken's "V" formula was used, as was the Moment kappa Formula for the practicality test, and the Gain Score formula for the effectiveness test. Based on the results of the three tests, the product is valid with a score of 0.9, practical with a score of 0.94, and effective with a score of 1.
Implementation of a K-Means-Based Intelligent Patient Complaint Clustering System to Identify Handling Priorities Ideal, M. Agung vafky; Nurfiah; Idir Fitriyanto
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 1 (2025): June 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i1.9529

Abstract

Patient complaints are the body’s response to health disturbances, triggered by internal factors such as genetics or external ones like the living environment. Understanding these causes allows community health centers (puskesmas) to take more effective preventive measures and design more targeted services. This study utilizes patient complaint data sourced from medical records, which include biodata and medical history, as well as complaint details that form the research subject. The main goal of this study is to develop an intelligent system that can generate clusters of patient complaints using the K-Means Clustering algorithm. The system is developed using the Research and Development (RnD) method. The clustering process applies a data mining approach, producing clusters based on patient complaints. A total of 600 complaint records, categorized into 72 distinct types, were used. The output consists of three clusters: C1 (high intensity) with 24 categories, C2 (moderate intensity) with 14 categories, and C3 (low intensity) with 34 categories. A practicality test yielded a score of 0.81, indicating the system is highly practical, while an effectiveness test by medical staff scored 0.88, showing the system is highly effective. This system enables health centers to identify trending complaints in the community and develop more focused prevention and treatment strategies. The clustering results also serve as a valuable foundation for strategic decision-making in disease control.
Co-Authors Afrianto, Nurdi Idir Fitriyanto Idir Nurfiah Rasyid, M Yuda, Fitra