Implementation of Fuzzy Logic in Determining the Acceptance Status of Fresh Milk Based on pH and Density
DOI:
https://doi.org/10.62535/xvycaa24Keywords:
acceptance status, Density, fuzzy logic, Matlab, pHAbstract
Fuzzy logic, known as fuzzy set theory, has become widely used to deal with uncertainty in research data processing. Fuzzy logic methods are known for their ease of implementation in machine language environments and their effectiveness in combining machine language representations with human
language with an emphasis on meaning or importance. Fuzzy logic maps input space to output space, and this concept is closely related to dealing with uncertainty in data. In applying fuzzy logic in this study, the variables pH and density of milk are considered inputs whose value ranges are divided into low, medium, and high categories. The result of the fuzzy system is the acceptability state of fresh milk. By applying this method using MATLAB software, the simulation results show that at a milk pH of 6.2 and a specific gravity of 1.0320, the acceptability state of fresh milk is 30. After the defuzzification process and manual calculation, the final result is 29.30~30. From these results, fuzzy logic provides high accuracy to support progressive decision-making. This allows the system to consider the complexity of milk quality criteria that cannot always be measured in a binary way (e.g., good or bad), resulting in more precise and accurate decisions.
References
D., & Fitriyah, H. (2023). Klasifikasi Kelayakan Susu Sapi UHT berdasarkan PH , Warna , dan Aroma menggunakan Metode Naive Bayes berbasis Arduino. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 6(11), 5541–5548. https://doi.org/https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/11925
Pramesthi, R., Suprayogi, T. H., & Sudjatmogo. (2015). Total Bakteri dan pH Susu Segar Sapi Perah Friesian Holstein di Unit Pelaksana Teknis Daerah dan Pembibitan Ternak Unggul Mulyorejo Tengaran- Semarang. Animal Agriculture Journal, 4(1), 69–74. Retrieved from http://ejournal-s1.undip.ac.id/index.php/aaj%0ATOTAL
Priyo, W. T. (2017). Penerapan Logika Fuzzy dalam Optimasi Produksi Barang Menggunakan Metode Mamdani. Jurmal Ilmiah: Soulmath, 5(1), 14–21. https://doi.org/https://doi.org/10.25139/sm.v5i1.453
Qothrunnada, L., Yanti, I., & Pauzan, M. (2024). Implementasi Logika Fuzzy Pada Alat Pendeteksi Kualitas Minyak Goreng Berdasarkan pH dan Tingkat Kejernihan. Jurnal Teknologi Informasi Dan Ilmu Komputer, 11(1), 225–234. https://doi.org/10.25126/jtiik.20241118289
Ramadhani, Ramadhanu, & Hidayat, T. (2024). Exploratory Data Analysis ( EDA ) untuk Mengetahui Distribusi Data Kualitas Susu Sapi. Jurnal Sains Manajemen Informatika Dan Komputer, 23(1), 68–76. https://doi.org/10.53513/jis.v23i1.9500
Rizky, M., & Mulyoto, A. (2023). Sistem Pendukung Keputusan Pengangkatan Karyawan Tetap Pada PT . Tangguh Duta Merlin Menggunakan Metode Logika Fuzzy Tsukamoto. Jurnal Ilmu Komputer Dan Pendidikan, 2(1), 192–206. Retrieved from https://journal.mediapublikasi.id/index.php/logic
Safitri, W., & Abadi, A. M. (2015). Aplikasi Fuzzy Logic Dalam Pemilihan Makanan Mie Instan. 381–388.
Santosa, S. H., Hidayat, A. P., & Siskandar, R. (2021). SAFEA application design on determining the optimal order quantity of chicken eggs based on fuzzy logic. International Journal of Artificial Intelligence, 10(4), 858–871. https://doi.org/10.11591/ijai.v10.i4.pp858-871
Septiani, W., & Djatna, T. (2015). Rancangan Model Performansi Risiko Rantai Pasok Agroindustri Susu dengan Menggunakan Pendekatan Logika Fuzzy. Agritech, 35(1), 88–97. https://doi.org/https://doi.org/10.22146/agritech.9423
Setia, B., & Ramadhan, A. (2019). Penerapan Logika Fuzzy pada Sistem Cerdas. Jurnal Sistem Cerdas, 2(1), 61–66. https://doi.org/https://doi.org/10.37396/jsc.v2i1.18
Siskandar, R., Wiyoto, W., Santosa, S. H., Hidayat, A. P., Kusumah, B. R., & Darmawan, M. D. M. (2023). Prediction of Freshwater Fish Disease Severity Based on Fuzzy Logic Approach , Arduino IDE and Proteus ISIS Prediction of Freshwater Fish Disease Severity Based on Fuzzy Logic Approach , Arduino IDE and Proteus ISIS. Universal Journal of Agricultural Research, 11(6), 1089–1101. https://doi.org/10.13189/ujar.2023.110616
Sofia, W. A., & Juhari. (2021). Prosedur Fuzzy Tahani Menggunakan Fungsi Representatif Kurva Segitiga dan Trapesium. Jurnal Riset Mahasiswa Matematika, 1(1), 40–50. https://doi.org/https://doi.org/10.18860/jrmm.v1i1.13819
Sumiati, & Hadyanto. (2017). Penerapan Kendali Cerdas pada Penentuan Kualitas Produk 2-Ethyl Hexyl Acrylate Menggunakan Logika Fuzzy. Jurnal Pengembangan Riset Dan Observasi Sistem Komputer, 4(1), 26–29. https://doi.org/https://e-jurnal.lppmunsera.org/index.php/PROSISKO/article/view/143
Vinsensia, D. (2021). Analisis Kinerja Pelayanan Kesehatan Dengan Pendekatan Logika Fuzzy Sugeno. Jurnal Media Informatika, 2(2), 62–73. https://doi.org/https://doi.org/10.55338/jumin.v2i2.695
Wahyuningsih, & Pazra, D. F. (2022). Kualitas Fisik , Kimia , Mikrobiologi Susu Sapi pada Peternakan Sapi Perah di Kecamatan Caringin , Kabupaten Bogor. Jurnal Agroekoteknologi Dan Agribisnis, 6(1), 1–16. https://doi.org/https://doi.org/10.51852/jaa.v6i1.532
Wartono, F., Effendi, M. M., & Rivalni, E. (2019). Temperature Monitoring System to Maintain Foods Resistance towards Storage Rooms Using Fuzzy Logic Methode. Jurnal Ilmiah Informatika, Arsitektur Dan Lingkungan, 14(1), 38–47. https://doi.org/https://doi.org/10.37366/pelitatekno.v14i1.226
Wicaksana, A. P., Hastono, T., & Solikhah, M. S. (2024). Application of Fuzzy Logic of The Sugeno Method to Determine the Amount of Production of Dry Potato Sambal. Journal of Technology and Health, 2(1), 1–10. https://doi.org/https://doi.org/10.61677/jth.v2i1.121
Wicaksana, T., & Sunaryanto, L. T. (2021). Analisis Pengendalian Kualitas Produksi Susu Sapi dengan Metode Statistical Process Control (SC) di CV. Cita Nasional. Jurnal Ilmu Dan Teknologi Pertanian, 8(2), 2722–1881. https://doi.org/https://doi.org/10.37676/agritepa.v8i2.1515
Wulandari, Z., Taufik, E., & Syarif, M. (2017). Kajian Kualitas Produk Susu Pasteurisasi Hasil Penerapan Rantai Pendingin. Jurnal Ilmu Produksi Dan Teknologi Hasil Peternakan, 05(3), 94–100. https://doi.org/https://doi.org/10.29244/jipthp.5.3.94-100
Yusuf, A., Kentjonowaty, I., & Humaidah, N. (2021). Pengaruh Hygiene Pemerahan terhadap Jumlah Mikroba dan pH Susu Sapi Perah. Jurnal Dinamika Rekasatwa, 4(1), 12–17. Retrieved from https://jim.unisma.ac.id/index.php/fapet/article/view/10154
[SNI] Standar Nasional Indonesia 3141.1: 2011. 2011




