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Agung Dwi Budiarto
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Sistem Rekomendasi Pemilihan Benih Varietas Unggul Padi Menggunakan Metode Fuzzy Analitycal Hierarchy Process - Simple Additive Weighting Agung Dwi Budiarto; Edy Santoso; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The continuously increasing number of Indonesian population each year is directly proportional to the increase in national food needs. The increase in this demand is not matched by an increase in agricultural production in the country, so the government is constantly imports to meet their food needs. It takes effort to increase production, especially rice which is considered as a major food ingredient majority of the public. One of the solutions is by activating seeding rice varieties. However, the number of criteria considered making farmers had difficulty in determining their choice. Judging from the problems that arise, there are a number of methods that can be implemented to solve the problems of farmers in decision-making, namely the presence of a recommendation system that is capable of solving the problems of multiple criteria using Fuzzy Analytical Hierarchy Process (Fuzzy AHP) to calculate the weight of the criteria and Simple Additive Weighting (SAW) method to measure the alternatives rank. Functional testing system generates a value of 100%, which means that the system is functioning properly in accordance with the design requirements. While the correlation testing using Spearman method produce the rank-order correlation coeficient of each variety, which coeficient of the INPARI varieties is 0,999, INPAGO is 1,000, INPARA is 1,000, and HIPA is 0,981. So, it can be concluded that the Fuzzy AHP-SAW methods on this system can be used for recommending selection of seed varieties of rice, because it has a positive relationship that approach perfectly with the expert's rank data.
Co-Authors Edy Santoso Muhammad Aminul Akbar