Penerapan Metode Fuzzy Mamdani Dalam Menentukan Suhu Optimal Pada Pendingin Ruangan (AC) Di Ruang Kelas
Keywords:
Sistem Pengambilan Keputusan, Logika Fuzzy Mamdani, MATLAB, SuhuAbstract
The Mamdani fuzzy method can be used to address decision-making resolutions, such as in determining the optimal temperature for air conditioning (AC) in classrooms. The right temperature is highly dependent on several factors, such as the number of people in it, the outdoor temperature and the length of time the room is used, as well as other environmental factors. In this study, the Mamdani fuzzy method is used to model and determine the appropriate temperature for a classroom that has input variables in the form of the number of people and the outdoor temperature. By using a fuzzy system, it is expected to achieve a more efficient and comfortable temperature setting, as well as reduce energy waste in the use of AC. This study aims to provide a more adaptive and responsive solution to changing conditions in the classroom, by utilizing the power of fuzzy logic to support more precise decisions in AC temperature settings.
References
I. Putri, I. Nurfajriyani, and Q. Fadilatussaniatun, “Pengaruh Suhu Ruangan Kelas Terhadap Konsentrasi Belajar Mahasiswa Pendidikan Biologi Semester Vii (B),” BIO Educ. (The J. Sci. Biol. Educ., vol. 5, no. 1, pp. 11–15, 2020, doi: 10.31949/be.v5i1.1744.
Adrianus Raffel and Yoga Alif Kurnia Utama, “Penerapan Logika Fuzzy untuk Kendali Suhu Ruangan dengan Air Conditioner pada Rumah dan Kantor,” Electr. J. Rekayasa dan Teknol. Elektro, vol. 17, no. 3, pp. 298–308, 2023, doi: 10.23960/elc.v17n3.2536.
Y. D. Aryandhi and W. Talakua, “Penerapan Inferensi Fuzzy Untuk Pengendali Suhu Ruangan Secara Otomatis Pada Air Conditioner (AC),” Pros. FMIPA Univ. Pattimura, pp. 177–184, 2013.
M. Abrori and A. H. Prihamayu, “Aplikasi Logika Fuzzy Metode Mamdani Dalam Pengambilan Keputusan Penentuan Jumlah Produksi,” Kaunia, vol. XI, no. 2, pp. 91–99, 2015.
M. B. Ginting et al., “Sistem Kontrol dan Monitoring AC dengan Menggunakan Metode Fuzzy Mamdani Berbasis IoT,” vol. 6, no. 1, pp. 382–396, 2024, doi: 10.47065/josh.v6i1.5944.
A. S. K. R. Nasution, Gunadi Widi Nurcahyo, and Agung Ramadhanu, “Penerapan Metode Fuzzy Mamdani untuk Mengidentifikasi Kepribadian Siswa,” J. KomtekInfo, vol. 11, pp. 157–162, 2024, doi: 10.35134/komtekinfo.v11i3.567.
A. Dharmalau and I. Hiswara, “Implementasi Logika Fuzzy Mamdani pada Sistem Pendukung Keputusan Penentuan Jumlah Standar Karyawan Toko,” J. Teknol. Technoscientia, vol. 13, no. 2, pp. 152–157, 2021.
C. Pratiwi, E. Tarigan, N. Rivany, and S. Retno Andani, “Penentuan Standar Ukuran Pakaian Wanita DewasaMenggunakan Metode Fuzzy Mamdani,” J. JPILKOM, vol. 2, no. 2, pp. 3025–6887, 2024.
S. Sunanto, R. Firdaus, and Makmur Setiawan Siregar, “Implementasi Logika Fuzzy Mamdani Pada Kendali Suhu dan Kelembaban Ruang Server,” J. CoSciTech (Computer Sci. Inf. Technol., vol. 2, no. 2, pp. 128–136, 2021, doi: 10.37859/coscitech.v2i2.3362.
N. A. Siregar, R. Akram, and N. Fadillah, “Sistem Pakar Diagnosa Penyakit Pada Kucing Anggora Menggunakan Metode Fuzzy Mamdani Berbasis Website,” Chain J. …, vol. 1, no. 2, pp. 68–77, 2023, [Online]. Available: https://ejournal.techcart-press.com/index.php/chain/article/view/30%0Ahttps://ejournal.techcart-press.com/index.php/chain/article/download/30/24
S. Amalia, E. Saputra, and R. Syukriansah, “Pemodelan Sistem Pengontrolan Suhu Ruangan Berbasis Logika Fuzzy Mamdani,” J. Tek. Elektro Inst. Teknol. Padang, vol. 10, no. 1, pp. 31–36, 2021, [Online]. Available: https://jte.itp.ac.id/index.php/jte/article/view/294
P. F. Logic and U. Pengaturan, “Penerapan Fuzzy Logic Untuk Pengaturan Suhu Ruangan Pada Pendingin Ruangan ( Ac ) menguunakan Mamdani”.
S. Puji Astuti, “Pemanfaatan Software Matrix Laboratory (Matlab) Untuk Meningkatkan Minat Belajar Mahasiswa Dalam Pembelajaran Fisika Kinematika,” J. Pendidik. Berkarakter, vol. 3, no. 2, pp. 54–57, 2020, [Online]. Available: http://journal.ummat.ac.id/index.php/pendekar
A. Tjolleng, “Buku Pengantar pemrograman MATLAB: Panduan praktis belajar MATLAB,” ReasearchGate, no. August, pp. 1–6, 2018.
R. Husna, R. Lestari, and Y. Hendra, “Inventory model of goods availability with apriori algorithm,” J. Phys.: Conf. Ser., vol. 1317, no. 1, p. 012019, Oct. 2019, doi: 10.1088/1742-6596/1317/1/012019
M. Y. Simargolang and H. S. Tamba, “Sistem Pendukung Keputusan Menggunakan Metode Fuzzy Sugeno Untuk Menentukan Calon Presiden Mahasiswa Di Universitas Asahan,” J. Teknol. Inf., vol. 2, no. 2, p. 122, 2019, doi: 10.36294/jurti.v2i2.426.
S. Batubara, “Analisis Perbandingan Metode Fuzzy Mamdani Dan Fuzzy Sugeno Untuk Penentuan Kualitas Cor Beton Instan,” It J. Res. Dev., vol. 2, no. 1, pp. 1–11, 2017, doi: 10.25299/itjrd.2017.vol2(1).644.
R. Husna, Y. Hendra and M.I. Akbar (2019). Comparison Between Apriori and Fp-Growth Algorithms on Inventory Model of Item Availability. J. Ipte. Terap., vol. 14, no. 3, pp. 219–229, 2020, doi: https://doi.org/10.22216/jit.v14i3.100.
Hendra, Y. Sakinah, P. Thoriq, M. (2023). Evaluasi Kinerja Algoritma Apriori Dalam Pengelompokan Data Transaksi Penjualan Untuk Analisis Pola Pembelian. Journal of Student Development Information System (JoSDIS) 3 (2), 220-228.
Hendra, Y., Sakinah, P., Maulana, F., & Manurung, K. H. (2024). Integrasi model pembelajaran mesin dalam game menggunakan gerakan tangan. Informatika, 12(3), 617-625.
