Implementation of the Fuzzy Mamdani Method in Decisions on Light Intensity in Plant Seed Research Rooms
Implementasi Metode Fuzzy Mamdani dalam Keputusan Intensitas Cahaya Ruangan Penelitian Benih Tumbuhan
DOI:
https://doi.org/10.56667/jveit.v4i1.953Abstract
This research is motivated by the assignment requirements of the intelligent systems course. Meanwhile, the title selection was based on the need for automatic regulation of the light intensity of the research lab room. The problem faced is that practitioners cannot regulate the light intensity at all times when there are changes in air temperature and humidity, then during the growth period the seeds must receive sufficient light so that seed growth can be maximized and can be predicted and managed well. This problem can be overcome one way by using the Fuzzy Mamdani method. The fuzzy mamdani method uses 3 variables, namely, input data, data rules, and output. The fuzzy input used in this research is the temperature and humidity values. The fuzzy rules applied are how the input value influences the output that will be produced. The output in this research is the size of the light intensity value. The use of the fuzzy application method is assisted by MATLAB Production Server R2015a 2.1 software. The fuzzy logic in the plant research room was successfully implemented and developed and produced accurate light intensity output, thereby helping practitioners to obtain optimal seeds. In this research, the Fuzzy Mamdani Method was used.
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References
Kusumadewi, S. dan Hari P, 2004, “Aplikasi Logika Fuzzy Untuk Pendukung Keputusan”, Penerbit Graha Ilmu, Yogyakarta.
Nasution MD, Nasution E, Haryati F. 2018. Pengembangan Bahan Ajar Metode Numerik Dengan Pendekatan Metakognitif Berbantuan Matlab. Mosharafa: Jurnal Pendidikan Matematika. 6(1):69–80. DOI:10.31980/mosharafa.v6i1.295
Taufiq G. 2016. Implementasi Logika Fuzzy Tahani Untuk Model Sistem Pendukung Keputusan Evaluasi Kinerja Karyawan. Jurnal Pilar Nusa Mandiri. XII(1):12–20.
Nabilah QJ, Puspaningrum EY, Syaifullah W, Saputra J. 2020. Otomatisasi Pengatur Intensitas Cahaya Ruang Menggunakan Logika Fuzzy. Jurnal Informatika dan Sistem Informasi (JIFoSI). 1(2):362–37.
Singgih Satrio Pamungkas C, Joseph Manehat D, Daeng Bakka Mau S. 2019. Aplikasi Fuzzy Logic Memprediksi Intensitas Cahaya Lampu Pada Kandang Ternak Ayam Broiler. J. Komput. Terap. 5(1):1–9. doi:10.35143/jkt.v5i1.2137.
Maghfiroh J. 2017. Pengaruh Intensitas Cahaya Terhadap Pertumbuhan Tanaman. Prosiding Seminar Nasional Pendidikan Biologi dan Biologi. 51–58.
Nasution VM, Prakarsa G. 2020. Optimasi Produksi Barang Menggunakan Logika Fuzzy Metode Mamdani. Jurnal Media Informatika Budidarma. 4(1):129. DOI:10.30865/mib.v4i1.1719
Dewi K, Listyati D, Penelitian B, Rempah T, Industri T. 2009. INTENSITAS PENYINARAN UNTUK PERTUMBUHAN BENIH. 105–108.
Friadi R, Junadhi J. 2019. Sistem Kontrol Intensitas Cahaya, Suhu dan Kelembaban Udara Pada Greenhouse Berbasis Raspberry PI. Journal of Technopreneurship and Information System (JTIS). 2(1):30–37. DOI:10.36085/jtis.v2i1.217
Angger Setyo Kusumo. 2022. Sistem Kontrol Intensitas Cahaya Lampu Aquascape Menggunakan Fuzzy Logic Controller Berbasis Arduino. Jurnal Teknik Elektro. 11:322–331.
