Sistem Informasi Geografis Potensi Pertanian GISELA Menggunakan Arcgis
-
Muhammad Alil Mafahir
*
Universitas Billfath Lamongan, Lamongan,
Indonesia
- Rokhmad Eko Cahyono Universitas Billfath Lamongan, Lamongan, Indonesia
- Ah. Afif Ridlwan Universitas Billfath Lamongan, Lamongan, Indonesia (*) Corresponding Author
Abstract
Lamongan Regency is a district where the majority of the population is engaged in farming, making it the largest agricultural area located in East Java. As an agrarian region, the main livelihood of its residents is in the agricultural sector. Development in the agricultural sector is primarily aimed at meeting the needs of the community, given the diversity of food sources which presents a significant potential for land use. Lamongan Regency was divided into two categories: agricultural areas and non-agricultural areas. The Food Security and Agriculture Service of Lamongan Regency in 2023 divided land into 2 criteria, namely agricultural areas and non-agricultural areas. Agricultural areas consisting of rice fields, fields, and plantations covering an area of 95,460.35 hectares. While non-agricultural areas consist of settlements, industry, rivers, swamps, and forests covering an area of 8,022.85 hectares [1].Currently, the main issue is the lack of agricultural information available to the public, making it difficult for residents to access information about agriculture in Lamongan Regency. Therefore, there is a need for a geographic information system that can provide information about agricultural land potential and maps of agricultural opportunities in Lamongan Regency, enabling residents to quickly and easily obtain information about the agricultural land potential in their area.The research methodology used in developing the Gisela application is the waterfall method. Agriculture impacts the community of Lamongan Regency by providing quick and easy access to information about the agricultural land potential in the region. This application features an interface that is easy for the public to understand. Additionally, it can generate recommendations for determining suitable crops to plant and establish as leading commodities in their respective areas.
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