Developing a precision spatial information system of smallholder oil palm plantations for sustainable rural development

Abstract

Oil-palm products are contributes significantly to economic growth, creating jobs and government revenue. Of the 14 million ha of Indonesian oil palm plantation, 40% are smallholder farming characterized by low productivity, irregular distribution, and fragmented. The lack of smallholder farming traceability information is one of the main issues for product certification, which make it difficult to access the international markets and is an obstacle to increasing productivity and developing rural-based processing. The OPTIMAL-IPB technology using Artificial Intelligence (AI) approach provides precise spatial information. The objectives of this research, which were carried out in Jambi Province are to detect precisely: (1) the positions, numbers, and areas of smallholder oil palm plantation in the village with precision; (2) the suitability of the spatial distribution of oil palm plantations compared to the spatial plan (RTRW); (3) potential income of farmers and land tax at village level based on production estimates. The study significantly increased the accuracy and detailed information of palm oil farming data, providing essential information for land use control and the traceability of oil palm products. Village and regency governments can utilize this spatial information system for income tax calculations, preparing various production, and income improvement programs.