Pengembangan Sistem Business Intelligence pada Divisi Key Account PT LiuGong Machinery Indonesia.

Abstract

Proses pelaporan penjualan pada Divisi Key Account PT LiuGong Machinery Indonesia masih menggunakan spreadsheet terpisah yang menyebabkan fragmentasi data, risiko human error, dan keterlambatan informasi. Penelitian ini bertujuan mengembangkan prototipe sistem Business Intelligence untuk mengonsolidasikan data operasional dan mendukung pelaporan serta pengambilan keputusan berbasis data. Penelitian menggunakan metode Design Thinking melalui tahap Empathize, Define, Ideate, Prototype, dan Test. Sistem dikembangkan menggunakan pendekatan low-code melalui Google Sheets dengan mengonsolidasikan data operasional dari sumber yang terpisah ke dalam basis data terpusat, menerapkan validasi data, serta menyajikan informasi melalui Cloud Dashboard. Pengujian dilakukan melalui Black Box Testing dan User Acceptance Testing menggunakan metode End User Computing Satisfaction (EUCS). Hasil penelitian menunjukkan seluruh fungsi sistem berjalan sesuai kebutuhan pengguna dengan skor rata-rata penerimaan sebesar 4,6 dari 5. Prototipe yang dikembangkan mendukung pengelolaan data operasional dan pengambilan keputusan secara lebih efisien.

The sales reporting process in the Key Account Division of PT LiuGong Machinery Indonesia still relies on separate spreadsheets, resulting in data fragmentation, human error risks, and delayed information. This study aimed to develop a Business Intelligence system prototype to consolidate operational data and support reporting and data-driven decision-making. The study employed the Design Thinking method through the Empathize, Define, Ideate, Prototype, and Test stages. The system was developed using a low-code approach through Google Sheets by consolidating operational data from separate sources into a centralized database, applying data validation, and presenting information through a Cloud Dashboard. System evaluation was conducted through Black Box Testing and User Acceptance Testing using the End User Computing Satisfaction (EUCS) method. The results showed that all system functions operated according to user requirements, with an average user acceptance score of 4.6 out of 5. The developed prototype supports more efficient operational data management and decision making.