Yovi Apridiansyah, Marhalim, Ujang Juhardi, Fikri Ikbal

DESIGN OF A WEB-BASED POSYANDU DATA MANAGEMENT APPLICATION WITH QR CODE SCANNING FOR PATIENT DATA IDENTIFICATION

Introduction

Design of a web-based posyandu data management application with qr code scanning for patient data identification. Desain aplikasi manajemen data Posyandu berbasis web dengan pemindaian QR Code untuk identifikasi pasien. Meningkatkan efisiensi dan akurasi layanan kesehatan.

Abstract

This study discusses the design and development of a web-based Posyandu data management application integrated with QR Code scanning technology for patient data identification. The research background stems from data management problems in Posyandu that still rely on manual methods, leading to delays in data retrieval, duplication, recording errors, and information loss. The proposed solution is to build an integrated information system that utilizes QR Codes to accelerate patient identification processes and a centralized database to improve accuracy and efficiency in information management. The system development methodology includes requirements analysis, design using UML (Use Case, Activity, Sequence, and Class Diagrams), web-based application implementation, QR Code scanning integration, and functional testing using black box testing. Implementation results demonstrate that the system can facilitate rapid and structured management of child, pregnant mother, elderly, immunization, and visit data. The use of QR Codes has proven to accelerate data retrieval processes and reduce input errors, thereby improving the quality of health services in Posyandu. Black box testing results show all system features function with "Valid" status, confirming successful system implementation in meeting the operational needs of Posyandu Bungin Tambun, South Bengkulu.

Review

This paper presents a timely and relevant study on the design and development of a web-based Posyandu data management application, strategically integrated with QR Code scanning for enhanced patient identification. The authors effectively highlight a critical real-world problem: the inefficiencies inherent in manual data management within Posyandu centers, which lead to significant issues such as data delays, duplication, errors, and loss of vital information. The proposed solution—an integrated information system leveraging QR Codes for rapid patient identification and a centralized database for improved data accuracy and efficiency—is well-conceived and directly addresses these pressing challenges, demonstrating a clear understanding of the operational needs of public health services. The methodological approach adopted, encompassing requirements analysis, detailed design using UML diagrams (Use Case, Activity, Sequence, and Class Diagrams), and subsequent web-based application implementation with QR Code integration, appears robust and systematic. The abstract reports successful functional testing via black box methods, indicating that all system features operate with "Valid" status, which is a positive indicator of system integrity. Crucially, the implementation results underscore the system's capacity to facilitate rapid and structured management of diverse health data, including child, pregnant mother, elderly, immunization, and visit records. The documented acceleration of data retrieval and reduction in input errors through QR Code utilization are significant practical benefits that enhance the quality of health services, as demonstrated at Posyandu Bungin Tambun, South Bengkulu. This study makes a valuable contribution to improving health information systems at the community level. The developed application holds significant potential for enhancing the efficiency and accuracy of data management in Posyandu settings, offering a scalable model for other similar health initiatives. While the abstract confidently reports on functional success, future work could further explore the system's long-term operational sustainability, user acceptance by healthcare staff, and the quantitative impact on health outcomes beyond just data management metrics. Additionally, discussing potential challenges during implementation or considerations for wider deployment across various Posyandu centers could enrich the practical insights. Overall, this paper presents a practical and well-executed solution to a pertinent problem in public health data management.

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