Pengembangan dan Evaluasi Fitur Estimasi Harga Jual pada Modul Frontend Web Aplikasi Manajemen Ternak Sapi Pintar (MATASAPI)

Abstract

Penentuan harga jual sapi di Indonesia umumnya masih dilakukan secara tradisional tanpa memperhitungkan biaya pemeliharaan secara menyeluruh sehingga keuntungan peternak kurang optimal. Penelitian ini mengembangkan modul front-end pada website Manajemen Ternak Sapi Pintar (MATASAPI) dengan penambahan fitur estimasi harga jual sapi sebagai dukungan digitalisasi sektor peternakan. Metode pengembangan menggunakan pendekatan Scrum yang terdiri dari lima sprint, meliputi perancangan model UML, desain antarmuka, penyusunan parameter dan rumus perhitungan, pengembangan fitur perhitungan harga, history, log perubahan, simulasi, serta integrasi otomatis data biaya berdasarkan pencatatan peternak. Fitur harga jual memperhitungkan komponen biaya pakan, kesehatan, kandang, tenaga kerja, listrik dan air, biaya tambahan, serta margin dan inflasi sebagai rekomendasi harga jual. Pengujian dilakukan melalui User Acceptance Testing menggunakan metode black box testing pada peran peternak dan tamu. Hasil pengujian menunjukkan seluruh fungsionalitas berjalan sesuai kebutuhan dengan tingkat keberhasilan mencapai 97% dan perbaikan minor pada rumus perhitungan. Dengan demikian, website MATASAPI dengan fitur estimasi harga jual berhasil dikembangkan.

The determination of cattle selling prices in Indonesia is generally still conducted using traditional methods without comprehensively accounting for maintenance costs, resulting in suboptimal profits for farmers. This research developed a front-end module on the Smart Cattle Management website (MATASAPI) with the addition of a cattle selling price estimation feature as a form of digital support for the livestock sector. The development process employed the Scrum approach over five sprints, covering UML modeling, interface design, parameter and formula configuration, development of price calculation, history, change log, and simulation features, as well as automatic cost data integration based on farmers’ records. The selling price feature considers feed, health, housing, labor, electricity and water, additional costs, and applies margin and inflation to generate price recommendations. Testing was carried out through User Acceptance Testing using the black box testing method for both farmer and guest roles. The results show that all functionalities operated as required, achieving a success rate of 97% with minor improvements needed in the calculation formula. Therefore, the MATASAPI website with the price estimation feature was successfully developed.