Analysis of the Supply Chain and Design of an Android-Based Robusta Coffee Traceability System

Abstract

Robusta coffee is the most widely cultivated coffee commodity in Indonesia. in East Bolaang Mongondow Regency, the problem at the suplier level is limited market information, which makes the quality of the coffee beans produced inconsistent, which impacts the price and product quality image. The research aims to identify models and members of structure, added value, performance efficiency, and a traceability system to support product quality validation. Robusta coffee supply chain participants and their interactions was identified at the Modayag coffee plantation in East Bolaang Mongondow. Data was collected through observation, interviews, and field studies. Supply chain analysis was performed using the Vorst method, while added value was calculated using the Hayami method, and supply chain performance was assessed using the SCOR-AHP method. The traceability system design followed the SDLC method. The findings indicate that the Robusta coffee supply chain in East Bolaang Mongondow Regency includes farmers, collectors, processing plants, the retail industry, coffee roatery and consumers. Post-harvest handling involves harvesting, sorting, drying, peeling dry coffee skin, and roasting. The results of the added value show that farmers receive more profits when selling mixed coffee beans that have been processed into dry coffee (greenbeans) 67.1%, the profit ratio for collectors is 20.7%, Kopine Isco 26.3%, D&L coffee 84.5% and Robusta Gunung Ambang 63.9%. The supply chain performance measurements showed 51.2% at the farmer level, 57.7% for collectors, and 63.8% for processing plants. A traceability system named Kinton was successfully developed and integrated with the Firebase database to store all information.