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All Journal Arcitech: Journal of Computer Science and Artificial Intelligence
Sukia, Sukia
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Computer Science & IT

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Decision Support System for Plantation Land Suitability Assessment Using A Combination of AHP (Analytical Hierarchy Process) and Profile Matching Method Sahputra, Ilham; Fitria, Rahma; Sukia, Sukia
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 4 No. 2 (2024): December 2024
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v4i2.11957

Abstract

Determining the suitability of plantation land is a crucial factor in enhancing productivity and sustainability in the agricultural sector. However, existing studies often lack comprehensive approaches that integrate both the prioritization of criteria and precise evaluation of land suitability. This study addresses this gap by developing a decision support system (DSS) for plantation land suitability using a combination of the Profile Matching and Analytic Hierarchy Process (AHP) methods. The AHP method is employed to assign weights to various criteria based on their relative importance, while the Profile Matching method evaluates land suitability based on the generated profiles.  The results indicate that this integrated approach provides accurate and detailed land suitability recommendations. Specifically, Buket Rata land is suitable for Clove (preference score: 3.821), Oil Palm, and Tea (3.596); Reulet land is suitable for Cocoa (3.22) and Coconut (3.16); Geulanggang Kulam land is suitable for Clove (3.41), Cocoa (3.35), and Oil Palm (3.29); Sawang land is suitable for Clove (3.41), Oil Palm (3.17), and Cocoa (2.99); and Pesisir Laut land is suitable for Sugarcane (3.353) and Clove (3.173). This DSS not only aids decision-makers in optimizing land use and managing sustainable plantations but also contributes to the broader field of agricultural decision-making by demonstrating the effectiveness of combining AHP and Profile Matching methods.
Co-Authors Rahma Fitria, Rahma Sahputra, Ilham