Pengembangan Web Dashboard Monitoring Unit Layanan Modal Mikro dengan Metode Rapid Application Development

Abstract

Perkembangan teknologi informasi mendorong organisasi untuk mengelola data secara terintegrasi guna mendukung pengambilan keputusan. Pada PT Permodalan Nasional Madani, proses monitoring Unit Layanan Modal Mikro (ULaMM) masih dilakukan secara manual menggunakan Excel sehingga berpotensi menimbulkan ketidakkonsistenan dan kesalahan data. Penelitian ini bertujuan untuk merancang dashboard monitoring berbasis web menggunakan metode Rapid Application Development serta mengevaluasi kualitas sistem melalui Black-Box Testing, System Usability Scale, dan User Acceptance Testing. Sistem dikembangkan menggunakan React.js, Node.js, dan MySQL untuk menyajikan data dalam bentuk visualisasi yang terintegrasi dan mudah dipahami. Hasil penelitian menunjukkan bahwa sistem berhasil diimplementasikan dengan baik, memenuhi aspek fungsionalitas, memiliki tingkat usability yang tinggi, serta diterima dengan sangat baik oleh pengguna, sehingga mampu meningkatkan efisiensi monitoring dan mendukung pengambilan keputusan berbasis data.

Advances in information technology are driving organizations to manage data in an integrated manner to support decision-making. At PT Permodalan Nasional Madani, the monitoring process for the Micro Capital Service Units (ULaMM) is still conducted manually using Excel, which has the potential to cause inconsistencies and data errors. This study aims to design a web-based monitoring dashboard using the Rapid Application Development method and to evaluate the system’s quality through Black-Box Testing, the System Usability Scale, and User Acceptance Testing. The system was developed using React.js, Node.js, and MySQL to present data in the form of integrated and easily understandable visualizations. The results of the study indicate that the system was successfully implemented, meets functional requirements, has a high level of usability, and was very well received by users, thereby improving monitoring efficiency and supporting data-driven decision-making.