IJASEIT

International Journal on Advanced Science, Engineering and Information Technology, Vol. 9 (2019) No. 4, pages: 1357-1363, DOI:10.18517/ijaseit.9.4.8389

Agricultural Extension Planning Pattern at Level of Nagari (Minangkabau Traditional Village) Based on Bonding Capital in Group of Farmers in Lima Puluh Kota District, Indonesia

Muhamad Reza, Melinda Noer, - Yonariza, - Asmawi

Abstract

The process of agricultural extension planning through participatory approach prioritizes the involvement of farmers to set the planning decision. Such condition was found in area where farmers join in bond basis association. Through a qualitative approach with case study method, this research aims to describe and explain the pattern of agricultural extension planning process innagari (a term of local village) that involve farmers from fellow farmers group and see its discrepancy against the legal rules. The research was conducted in Nagari Balai Panjang, Tanjuang Gadang and Batu Balang for 6 months, starting from April to October 2016. There are 14 informants, consisting of three field facilitators and 11 of farmer group administrators supported this research. The focus of the data were preparation stages and formulation implementation of the condition, goal setting, obstacles / constraints to achieve the goal and extension action plans, finalization of agricultural extension planning documentsin nagari. Data collection techniques applied were interviewing, documentating and observing. Through descriptive qualitative data analysis techniques with synthesis methods as analysis toolsand interpretating along with assessment methods to the content of the document as the secondary data, it can be concluded that there are two patterns in the nagari agricultural extension planning process by bringing up the principles of participation. The differences found of the two patterns were only on methods to obtain the data and information of nagari as a circumstances determination, which is the initial year of field facilitator innagari using PRA methods, while the next year using secondary data, observation and data cross-check.