Comparison of SAW and WP methods to determine the best agricultural land

Sigit Susanto Putro, Firmansyah Adiputra, Eka Mala Sari Rochman, Aeri Rachmad, Muhammad Ali Syakur, Satria Bayu Seta

Abstract


Rice is a cultivated plant that is very important for human life because it produces rice in making rice. The need for food always increases this is due to the increasing human population. Therefore, rice cultivation must be maximized. Agricultural land used to grow rice greatly affects the production produced. Different characteristics in each region should be considered in selecting suitable agricultural land. The purpose of this research is to determine and map the suitable areas for rice farming in order to obtain maximum production results. The determination of the feasibility of the location of the farm is based on the assessment of the criteria owned by each region. These criteria include soil type, slope, land area, rainfall, and irrigation or water. The criteria for each area will be processed using the Simple Additive Weighting (SAW) and Weighted Product (WP) methods, the process in this method is to find the weight value for each attribute, then a ranking process is carried out which will produce an optimal alternative, namely a suitable area for agriculture. The contribution of this research is to know the comparison of the SAW method with the WP in the process of determining the best agricultural area for rice plants. In this system using the SAW method, resulting in an accuracy rate of 72%. This is better than using the WP method which only produces an accuracy rate of 50%.

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Published: 2021-06-03

How to Cite this Article:

Sigit Susanto Putro, Firmansyah Adiputra, Eka Mala Sari Rochman, Aeri Rachmad, Muhammad Ali Syakur, Satria Bayu Seta, Comparison of SAW and WP methods to determine the best agricultural land, Commun. Math. Biol. Neurosci., 2021 (2021), Article ID 49

Copyright © 2021 Sigit Susanto Putro, Firmansyah Adiputra, Eka Mala Sari Rochman, Aeri Rachmad, Muhammad Ali Syakur, Satria Bayu Seta. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Commun. Math. Biol. Neurosci.

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