COMPARISON OF SUGENO AND MAMDANI FUZZY SYSTEM PERFORMANCE IN PREDICTING THE AMOUNT OF VIRGIN COCONUT OIL (VCO) PRODUCTION

Doms Upuy; Arlene Henny Hiariey

doi:10.33387/jiko.v6i3.7051

COMPARISON OF SUGENO AND MAMDANI FUZZY SYSTEM PERFORMANCE IN PREDICTING THE AMOUNT OF VIRGIN COCONUT OIL (VCO) PRODUCTION

Doms Upuy, Arlene Henny Hiariey

Abstract

In the future, a tight industrial competition.The professional manage companies become crucial to successful so competitive on the global market.One of the key figure in production is the ability to plan and optimize goods production process. To face fluctuations of consumer demand without adding existing facilities, The company can use fuzzy mammal and sugeno methods to determine the amount of production of voc (virgin organic coconut) based on supply and demand data in the wotay coconut (main business area). process involving 18 fuzzy rules using AND and OR operators on each fuzzy set and IF-THEN rules for each input variable demand (little, medium, a lot), inventory (little, medium, a lot), output (little, medium , Lots). The thing that strengthens the conclusion that fuzzy sugeno is better than fuzzy mamdani with this data is that the MAPE for fuzzy sugeno has a value of 36.11% with a truth level of 63.89%, while for fuzzy mamdani the MAPE value is 38.77%, with a truth level 61.23 %. With the MAPE value obtained from Fuzzy Mamdani and Sugeno, the forecast for VOC production at KBU is predicted. Wootay Coconut is worth using with fuzzy sugeno.

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References

Rusnani, Enita, Tukidi, and E. Haryanto, “Journal of Scientech Research and Development,” J. Sci. Res. Dev., vol. 3, no. 1, pp. 24–32, 2021.

D. Upuy, F. Leunupun, Y. A. Lesnussa, Z. A. Leleury, and A. H. Hiariey, “Application of Fuzzy Logic to Find Out the Amount of Spending Money at the Bank,” Formosa J. Comput. Inf. Sci., vol. 1, no. 2, pp. 133–142, 2022.

D. P. P. Astuti and Mashuri, “Penerapan Metode Fuzzy Tsukamoto dan Fuzzy Sugeno Dalam Penentuan Harga Jual Sepeda Motor,” UNNES J. Math., vol. 1, no. 2252, pp. 75–84, 2020.

A. Rahman Hakim, “Penerapan Logika Fuzzy Untuk Menentukan Harga Jual Tas Fashion Menggunakan Metode Sugeno,” J. Desain Dan Anal. Teknol., vol. 2, no. 1, pp. 84–91, 2023.

D. Upuy and K. Kunci, “IMPLEMENTASI QUERY FUZZY PADA BASIS DATA RELASIONAL DOMS UPUY, Drs. Retantyo Wardoyo, M.Sc., Ph.D,” 2017.

R. E. Subarja and B. Hendrik, “Research Article Padangsidimpuan Utara Menggunakan Pendektan Fuzzy Inference,” vol. 1, pp. 90–95, 2023.

S. Auliana and U. Mansyuri, “Penggunaan Metoda Fuzzy Tsukamoto Untuk Menentukan Produksi Barang Elektronik 1,” J. Simasi J. Ilm. Sist. Inf., vol. 2, no. 2, pp. 123–129, 2022.

L. Susanti, “Analisis Kepuasan Pelanggan terhadap Kualitas Produk dan Pelayanan dengan Menggunakan Komparasi Fuzzy Inference System,” J. Sos. Teknol., vol. 2, no. 4, pp. 378–386, 2022.

N. Setyanugraha, S. Al Aziz, I. W. Harmoko, and F. Fianti, “Study of a Weather Prediction System Based on Fuzzy Logic Using Mamdani and Sugeno Methods,” Phys. Commun., vol. 6, no. 2, pp. 61–70, 2022.

D. Rifai and F. Fitriyadi, “Penerapan Logika Fuzzy Sugeno dalam Keputusan Jumlah Produksi Berbasis Website,” Hello World J. Ilmu Komput., vol. 2, no. 2, pp. 102–109, 2023.

R. Adrial, “Fuzzy Logic Modeling Metode Sugeno Pada Penentuan Tipe Diabetes Melitus Menggunakan MATLAB,” J. Ilm. Inform., vol. 6, no. 1, pp. 62–68, 2018.

A. Siti, “Analisis komparasi metode tsukamoto dan sugeno dalam prediksi jumlah siswa baru,” J. Teknol. Inf. dan Komun., vol. 8, no. 2, pp. 57–63, 2016.

A. Puspitasari and H. Zakaria, “Sistem Informasi Aplikasi Penentuan Jurusan Yang Sesuai Dengan Minat Menggunakan Pendekatan Fuzzy Sugeno ( Studi Kasus : SMK Fadilah ),” vol. 1, no. 3, pp. 630–642, 2023.

DOI: https://doi.org/10.33387/jiko.v6i3.7051

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