Perancangan Dashboard Mega Sales Center Berbasis Rapid Application Development (Rad) untuk Analisis dan Evaluasi Kinerja Sales dan Branch manager

Abstract

PT XYZ menghadapi kendala dalam pelaporan kinerja operasional karena proses pengolahan data KPI sales, KPI branch manager, dan data pelatihan masih dilakukan secara manual menggunakan file Microsoft Excel. Penelitian ini bertujuan merancang dan membangun dashboard Mega Sales Center (MSC) berbasis Rapid Application Development (RAD) sebagai media analisis dan evaluasi kinerja sales dan branch manager. Sistem dikembangkan menggunakan Python dengan modul otomatisasi preprocessing untuk melakukan validasi, pembersihan, standarisasi, dan penggabungan data sebelum disimpan ke database dan divisualisasikan dalam dashboard berbasis web. Evaluasi sistem dilakukan menggunakan Black Box Testing dengan teknik Use Case Testing, validasi data melalui perbandingan hasil preprocessing dengan data sumber, serta User Acceptance Test (UAT). Hasil pengujian menunjukkan seluruh fungsi sistem berjalan sesuai kebutuhan, hasil visualisasi konsisten dengan data sumber, dan UAT memperoleh nilai 93,08% dengan kategori Sangat Baik. Dashboard yang dihasilkan mampu mengotomatisasi pengolahan data dari beberapa file Excel serta mendukung proses analisis, evaluasi, dan pengambilan keputusan pada tim Sales Management.

PT XYZ faces challenges in operational performance reporting because KPI data for sales, Branch Managers, and training are still processed manually using Microsoft Excel files. This research aims to design and develop the Mega Sales Center (MSC) dashboard using the Rapid Application Development (RAD) method to support the analysis and evaluation of sales and Branch Manager performance. The system was developed using Python with an automated preprocessing module to validate, clean, standardize, and merge data before storing it in a database and presenting it through a web-based dashboard. System evaluation was conducted using Black box Testing with the Use Case Testing technique, data validation by comparing preprocessing results with the source data, and User Acceptance Testing (UAT). The results show that all system functions operated as expected, the visualized information was consistent with the source data, and the UAT achieved a score of 93.08%, indicating an excellent level of user acceptance. The developed dashboard successfully automates data processing from multiple Excel files and supports the analysis, evaluation, and decision-making processes of the Sales Management team.