Application of Fuzzy Logic in Tempe Production Using the Tsukamoto Algorithm
DOI:
https://doi.org/10.62535/aygmd359Keywords:
analysis, fuzzy logic, Tsukamoto methodAbstract
Fuzzy logic is widely used in various fields to formalize human behavior by considering inaccurate or partial reasoning. This study implements the Tsukamoto fuzzy logic method to analyze tempe production based on demand and inventory data. The research utilizes library research methods and data analysis using MATLAB (Matrix Laboratory). The Tsukamoto method was chosen for its high tolerance for data and flexibility. The system uses two input variables: demand and inventory, with output being production quantity. The fuzzy sets for demand are categorized as "Decrease" and "Increase" with a domain of [1000; 2000], inventory as "Few" and "Many" with a domain of [100; 600], and production as "Decrease" and "Increase" with a domain of [1520; 2100]. Using four fuzzy rules and the defuzzification process, the system can predict optimal production quantities. For example, with a demand of 1500 and inventory of 400, the system calculates a production quantity of 1823 units. This implementation demonstrates the effectiveness of the Tsukamoto method in automating production decisions based on demand and inventory variables.
References
Anggriani, T. N., Samosir, R. A., Saputri, E. C., Windarto, A. P. (2020, Februari). Fuzzy Inferensi System Pada Produksi Tempe Dengan Algoritma Tsukamoto. Seminar Nasional Teknologi Komputer & Sains (SAINTEKS). Prosiding Seminar. https://prosiding.seminar-id.com/index.php/sainteks.
Asbur, Y., & Khairunnisyah. (2021). Tempe as a source of antioxidants: A Review. Jurnal Ilmu Pertanian, 9(3), 183-192. https://jurnal.uisu.ac.id/index.php/agriland.
Basriati, S., Safitri, E., Nofridayani, P. (2020). Penerapan Metode Fuzzy Tsukamoto dalam Menentukan Jumlah Produksi Tahu. J Sains, Teknol dan Ind, 18(1), 120-125. doi:10.24014/sitekin.v18i1.11022.
Damanik, R. S., Ichsan, M. H. H., Akbar, S. R. (2022). Analisis Metode Fuzzy Tsukamoto Dan Floyd-Warshall Untuk Pencarian Rute Terbaik Pada Wireless Sensor Network Berbasis Matlab. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer [diakses pada 2024 Okt 26]; 6(9), 4188-4195. https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/download/11533/5116/81187.
Ferdiansyah, Y., Hidayat, N. (2018). Implementasi Metode Fuzzy-Tsukamoto Untuk Diagnosis Penyakit Pada Kelamin Laki Laki. Jurnal l Pengembangan Teknologi Informasi dan Ilmu Komputer [diakses 27 Okt 2024]; 2(12), 7516-7520. https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/3994.
Pasaribu, N. S., Hardinata, J. T, Qurniawan, H. (2021). Application Of The Fuzzy Tsukamoto Method In Determining Household Industry Products. Journal of Artificial Intelligence and Engineering Applications, 1(1), 71-75. https://doi.org/10.59934/jaiea.v1i1.57
Rifanti, U. M., Pujiharsono, H., Pradana, Z. H. (2023). Implementasi Logika Fuzzy Pada Penilaian Kegiatan Merdeka Belajar Kampus Merdeka (MBKM). JST (Jurnal Sains dan Tekno), 12(1), 250–260. https://10.23887/jstundiksha.v12i1.50057.
Samudra, T., Juhardi, U., Rifqo, M. H., Darmi, Y. (2024). Implementasi Algoritma Fuzzy Tsukamoto Dalam Menentukan Harga Jual Udang Pada Tambak Udang Desa Linau Kabupaten Kaur. J. Media Infotama [diakses 2024 Okt 26]; 20(1), 371–377. https://jurnal.unived.ac.id/index.php/jmi/article/download/5874/4312/
Sari, M., Asmendri. (2017). Penelitian Kepustakaan (Library Research) dalam Penelitian Pendidikan IPA. Jurnal Penelitian Bidang dan Pendidikan IPA [diakses 2024 Okt 28]; 6(1), 41-53. https://core.ac.uk/download/pdf/335289208.
Setiyawan, D., Arbansyah, A., Latipah, A. J. (2023). Fuzzy Inference System Metode Tsukamoto Untuk Penentuan Program Studi Fakultas Sains Dan Teknologi Di Universitas Muhammadiyah Kalimantan Timur. JIKO (Jurnal Inform dan Komputer), 7(1), 23. https://doi.org/10.26798/jiko.v7i1.657.
Siswoyo, B., Zaenal, A. (2018). Model Peramalan Fuzzy Logic. Jurnal Manajemen Informatika, 8(1), 1-14. https://doi.org/10.34010/jamika.v8i1.897.
