IMPLEMENTASI FUZZY LOGIC PADA PRODUKSI RESEP PEMBAGIAN KOPI
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Keywords

Coffee beans
Fuzzy Mamdani
Simulation

How to Cite

Setyawan, H. P. ., Ahmad A, E. ., Andi S, A. ., Muharror, A. ., Aryanto, V. ., Mufti, D. ., Yudit Laksono, B. ., & Setyo Pambudi, W. . (2022). IMPLEMENTASI FUZZY LOGIC PADA PRODUKSI RESEP PEMBAGIAN KOPI. Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 6(1), 031–035. https://doi.org/10.29407/inotek.v6i1.2447

Abstract

Coffee beans have diversity characteristic in aroma and taste, makes coffee a popular drink. Indonesia has many coffee beans producing areas, such as Flores coffee beans, Java coffee beans and Aceh Gayo coffee beans. Combine several coffee beans can produce processed coffee products with different quality flavors. To help from blending coffee blends, fuzzy logic can be used to determine the choice of coffee produced from several coffee bean blends. In this study, the use of the Fuzzy Mamdani method was carried out in a simulation using visual studio. Fuzzy Mamdani logic uses three stages to determine the quality of a mixture of several coffee beans. Fuzzy Logic is uses three stages to determine the quality of a mixture of several coffee beans. The three stages are fuzzification, interference engine, and defuzzification. From the fuzzification process, three coffee bean variables will be taken, for interference the engine will set the rules for the several coffee mixtures after which they will enter the defuzzification process. From the results of defuzzification will determine the expected coffee yield. Coffee products made from three coffee beans are coffee with light, medium and heavy flavor.

https://doi.org/10.29407/inotek.v6i1.2447
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References

“jenis-jenis-kopi-nusantara @ ottencoffee.co.id.” [Online]. Available: https://ottencoffee.co.id/majalah/jenis-jenis-kopi-nusantara

F. A. Minarni, “Prediksi Jumlah Produksi Roti Menggunakan Metode Logika Fuzzy,” Teknoif, vol. 4, no. 2, pp. 59–65, 2016.

F. Rastic Andrari, M. Maimunah, and Nurmala Dewi Qadarsih, “Penerapan Metode Fuzzy Mamdani Dalam Menentukan Harga Jual Ponsel Pintar Bekas (Studi Kasus Pada Kayyis Cellular Depok),” Pixel J. Ilm. Komput. Graf., vol. 14, no. 2, pp. 253–262, 2021, doi: 10.51903/pixel.v14i2.585.

S. A. Dharma, T. J. Pattiasina, and E. M. Trianto, “Perancangan Aplikasi Rekomendasi Pemilihan Lokasi Rumah dengan Memanfaatkan Fuzzy Database Metode Tahani,” Teknika, vol. 4, no. 1, pp. 23–28, 2015, doi: 10.34148/teknika.v4i1.33.

R. Rahman, H. Wanto, and E. Haryanti, “Analisis Preferensi Konsumen Terhadap Kopi Lokal Jawa (Bromo Tengger) Di Kota Surabaya,” J. Chem. Inf. Model., vol. 53, no. 9, pp. 1689–1699, 1981.

H. Nasution, “Implementasi Logika Fuzzy pada Sistem Kecerdasan Buatan,” ELKHA J. Tek. Elektro, vol. 4, no. 2, pp. 4–8, 2020, [Online]. Available: https://jurnal.untan.ac.id/index.php/Elkha/article/view/512

Sutikno, “Perbandingan Metode Defuzzifikasi Aturan Mamdani Pada Sistem Kendali Logika Fuzzy ( Studi Kasus Pada Pengaturan Kecepatan Motor DC ),” Elektro, Jur. Tek. Tek. Fak. Semarang, Univ. Diponegoro, pp. 1–10, 2011.

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Copyright (c) 2022 Hendra Putra Setyawan; Emfa Ahmad A, Arrizal Andi S, Aunnurohman Muharror, Very Aryanto, Dalli Mufti, Bagus Yudit Laksono, Wahyu Setyo Pambudi

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