Determining the Grade of Robusta Coffee Beans of Lampung, Bengkulu, and South Sumatra Provinces by Using the Analytical Hierarchy Process (AHP)

Yodhi Yuniarthe - Indonesia Mitra University, Indonesia
Admi Syarif - Lampung University, Indonesia
Sumaryo Gitosaputro - Lampung University, Indonesia
Warsito Warsito - Lampung University, Indonesia


Citation Format:



DOI: http://dx.doi.org/10.62527/joiv.9.1.2667

Abstract


Coffee is an important commodity for the world business community. One of the world's leading coffee producers is Indonesia. In Indonesia, several provinces produce coffee beans, especially in Sumatra island. They generally cultivate robusta-type coffee. The determination of coffee quality here is still done manually. Recently, along with the increasing recognition of computers, several decision-support system approaches have been introduced, including the Analytical Hierarchy Process (AHP). This research aims to implement the AHP to assess Indonesian robusta coffee beans (Lampung, Bengkulu, and South Sumatra). The researchers use a systematic process, including the preparation stage, data collection using datasets, determination of criteria and alternatives, hierarchical structure, creation of matrices to compare pairs, calculation of priority vectors and eigenvector values, and accuracy testing. This research uses six criteria with 19 sub-criteria and seven alternatives. From the rankings calculated using the AHP method for coffee production areas, the best quality coffee bean is in West Lampung, with the highest value of  0.28. The results of this study are compared with those given by an expert. The results show the MAPE error of 4.42%, a very accurate category.  Thus, it is shown that this method provides excellent results. Future research can be conducted to develop a more sophisticated and efficient AHP method for multi-criteria decision-making in various fields such as business management, engineering, environment, and health.

Keywords


Indonesia; Robusta Coffee; Artificial intelligence (AI); Analytical Hierarchy Process(AHP);.

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References


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