Classification of Farmer Groups Using the Fuzzy Analytic Hierarchy Process Method
Muhammad Ali Syakur, Eka Mala Sari Rochman, Aeri Rachmad,Ryan Adhitama

Departement of Informatics,Faculty of Engineering, University of Trunojoyo Madura, Bangkalan, Indonesia

Abstract

Abstract, Agriculture is a sector that has an important role in the economy in Indonesia. The location of the State of Indonesia itself is on the equator which makes the land fertile and suitable as agricultural land. To increase agricultural productivity, the role of farmer groups is needed. Farmer groups with a high class have the opportunity to produce high productivity as well. Farmer group classes are divided into four, namely beginner, advanced, intermediate, main. To determine the class of each farmer group, it is necessary to select from the Department of Agriculture with assessment indicators, namely planning, organizing, implementing activities, evaluating and reporting as well as leadership. With so many indicators used, the Fuzzy Analytic Hierarchy Process method was chosen as the weighting and checking of weight consistency. The results of this study are a system that can measure the performance of farmer groups based on existing criteria and produce a final score which will be a benchmark in determining the class of the farmer group to be beginner, advanced, intermediate and primary. Out of a total of 131 farmer groups, 5.3% were in the beginner class, 26.7% in the advanced class, 66.4% in the middle class and 1.5% in the main class. This system also produces a fairly high accuracy value of 94.65%.

Keywords: Classification, Farmer Group Performance Transfer, Fuzzy AnalyticHierarchy Process

Topic: Machine Learning and Deep Learning