Implementasi Logika Fuzzy Untuk Pendukung Keputusan Sistem Penyiraman Otomatis Tanaman Anthurium

 (*)Dina Meliana Saragi Mail (Telkom University, Bandung, Indonesia)
 Faqih Hamami (Telkom University, Bandung, Indonesia)
 Tatang Mulyana (Telkom University, Bandung, Indonesia)

(*) Corresponding Author

Submitted: September 26, 2022; Published: September 30, 2022

Abstract

Anthurium is a class of ornamental plants that are admired by many lovers of ornamental plants, this plant is cultivated on a wide scale in the floriculture industry. There are factors that support the current high price of anthurium plants, first, a unique species with a ratio of 10% of anthurium seeds that grow exactly the same as the parent. In addition, anthurium growth is very slow and difficult to care for. Other factors must be considered in the cultivation of anthurium plants, namely air temperature, humidity, sunlight, acidity (pH) and water requirements. This anthurium plant is a plant that is sensitive to water so it requires supervision of regular watering so that the plant does not die. Farmers need advanced expert knowledge in making different decisions related to agriculture, especially in dosing and timing of crop watering. Therefore, in this study, researchers designed fuzzy logic according to the needs of anthurium plants with a rule base that can change IoT sensor data in the form of DHT11 sensors and Soil Moisture Sensors FC-28 into the output of a decision on the duration of plant watering. In this stage, the process of fuzzification, inference and defuzzification. The results obtained during this research are comparative testing of 15 values from the output devices that are taken at random approximately closer to the values from the simulation with MATLAB with a total difference of 8.61% due to the difference in calculations between IoT devices and simulations with MATLAB, but this can still be categorized accurately because the output results of the MATLAB tool and simulation are still within the range of membership function values.

Keywords


Anthurium; IoT; Decision Support; Fuzzy Logic; Smart Farming

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References

K. S. R. S. S. Dirgantari Putri, “Faktor-Faktor Yang Mempengaruhi Permintaan Tanaman Hias di Desa Bangun Sari Kecamatan Tanjung Morawa Kabupaten Deli Serdang,” Jurnal Ilmiah Pertanian, p. 3, 2019.

R. Agromedia, “Agar Daun Anthurium Tampil Menawan,” dalam Agar Daun Anthurium Tampil Menawan, Agromedia, 2007, pp. 10-15.

K. Junaedhie, “Pesona Anhurium Daun,” dalam Pesona Anhurium Daun, Agromedia, 2006, pp. 15-18.

A. H. R. W. S. H. Sri Kusumadewi, “Fuzzy multi-attribute decision making (fuzzy madm),” Fuzzy multi-attribute decision making (fuzzy madm), vol. 74, p. 5, 2006.

M. S. Asih, “SISTEM PENDUKUNG KEPUTUSAN FUZZY MAMDANI PADA ALAT PENYIRAMAN TANAMAN OTOMATIS,” Jurnal Sistem Informasi, vol. 02, p. 7, 2018.

S. T. M. J. P. a. S. R. Alan R. Hevner, “Design Science in Information Systems Research,” JSTOR, vol. 28, p. 3, 2004.

F. A. R. M. Nadya Febriany, “Aplikasi metode fuzzy mamdani dalam penentuan status gizi dan kebutuhan kalori harian balita menggunakan software MATLAB,” Jurnal EurekaMatika, vol. 5, pp. 84-96, 2017.

H. Nasution, “Implementasi Logika Fuzzy pada Sistem Kecerdasan Buatan,” Fakultas Teknik Universitas Tanjungpura Pontianak, p. 3, 2013.

M. I. J. J. Laras Purwati Ayuningtias, “Analisa Perbandingan Logic Fuzzy Metode Tsukamoto, Sugeno, Dan Mamdani (Studi Kasus : Prediksi Jumlah Pendaftar Mahasiswa Baru Fakultas Sains Dan Teknologi Universitas Islam Negeri Sunan Gunung Djati Bandung),” Jurnal Teknik Informatika UIN Syarif Hidayatullah, p. 7, 2017.

Mukaromah, “Penerapan Metode Fuzzy Sugeno Untuk Menentukan Jalur Terbaik Menuju Lokasi Wisata di Surabaya,” Jurnal Matematika Sains dan Teknologi, p. 5, 2019.

S. K. I. V. P. Retno Dina Ariyanti, “Beck Depression Inventory Test Assessment Using Fuzzy Inference System,” IEEE, p. 6, 2010.

A. D. Muhammad ARHAMI, “Pemrograman Matlab,” Yogyakarta: Andi, p. 7, 2005.

A.-K. M. T. R. C. R. &. L. P. Jan Behmann, “A review of advanced machine learning methods for the detection of biotic stress in precision crop protection,” SpringerLink, p. 6, 2015.

X. M. L. S. Ye Liu dan A. M. A.-M. Gerhard Petrus Hancke, “From Industry 4.0 to Agriculture 4.0: Current Status, Enabling Technologies, and Research Challenges,” IEEE, p. 5, 2020.

A. Prasetyo, “Pengertian Flowchart Beserta Fungsi dan Simbol-simbol Flowchart yang Paling Umum Digunakan,” Jurnal EDU, 2019.

S. Panigrahi, “Cultivation of Anthurium in Polyhouse,” Reserchgate, pp. 25-60, 2020.

I. Suwaldi, “Budidaya tanaman hias Anthurium hookeri,” dalam Budidaya tanaman hias Anthurium hookeri, Surabaya, UNS, 2009, p. 30.

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Copyright (c) 2022 Dina Meliana Saragi, Faqih Hamami, Tatang Mulyana

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