Sistem Fuzzy Logic Tertanam Pada Mikrokontroler Untuk Penyiraman Tanaman Pada Rumah Kaca

Farmadi, Andi; Nugrahadi, Dodon Turianto; Indriani, Fatma; Soesanto, Oni

doi:10.20527/klik.v4i2.121

Cited by 6 publications

(8 citation statements)

References 0 publications

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“…Penelitian kedua, menggunakan metode inferensi tsukamoto [6]. Memberikan kesimpulan bahwa metode yang digunakan mampu menjaga kelembaban tanah dengan menghasilkan presentase penyiraman sebanyak 5.26% penyiraman dan tidak melakukan penyiraman sebanyak 94.38%.…”

Section: Pendahuluanunclassified

Smart Farming Optimization of Phalaenopsis Orchids Growth By Utilizing Fuzzy Logic Control on IoT Architecture

Apriyani,

Prasetyo,

Aldila

2022

Telematika

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Tujuan: membangun sistem smart farming yang mampu memonitoring dan mengontrol kondisi serta perawatan terhadap tanaman secara otomatis. Penggunaan website sebagai monitoring dan sistem kontrol mikrokontroller secara realtime. Penyajian data dashboard dengan angka, tabel, dan grafik bergerak.Perancangan/metode/pendekatan: metode fuzzy sugenoHasil: sistem dapat bekerja secara otomatis maupun manual. Data yang dibaca dapat tampil secara realtime pada website dashboard. Sistem mampu mengkondisikan greenhouse sesuai dengan kondisi asli dari pembudidaya.Keaslian/ state of the art: penggunaan aplikasi dalam bentuk website yang dibuat sendiri dengan penyajian data-data secara realtime dalam bentuk angka, tabel, maupun grafik bergerak.

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Section: Pendahuluanunclassified

Smart Farming Optimization of Phalaenopsis Orchids Growth By Utilizing Fuzzy Logic Control on IoT Architecture

Apriyani,

Prasetyo,

Aldila

2022

Telematika

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“…Hasil tersebut ditampilkan melalui komputer dalam bentuk grafik yang tersedia dalam fuzzy logic. pemrograman sistem fuzzy dibangun menggunakan bahasa pemrograman C [7].…”

Section: Gambar 2 Skema Rangkaian Sistemunclassified

“…Pengujian yang dilakukan adalah uji kimia, fisik, biologi, atau uji kenampakan (bau dan warna). [7] Untuk mengetahui keakuratan sistem maka perlu mengetahui patokan kelayakan kualitas air. Patokan tersebut telah ditentukan oleh kementrian kesehatan yang dirangkum dalam tabel berikut.…”

Section: Pengujian Akurasi Sistemunclassified

Sistem Pendeteksi Kualitas Air Di Sekitar Pesisir Pantai Tondo Menggunakan Metode Fuzzy Logic

Sesengi¹,

Jumiyatun²,

Arifin³

et al. 2021

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The disaster that hit Palu City recently caused changes in the quality of water consumed by the community. To find out whether it is feasible or not, a method is needed to detect a water quality system that is easy to apply at an economical price so that people can know for sure the quality of the water they use for their daily needs. Therefore, a tool is designed to determine the quality of water, which samples are taken around the coast of Tondo by using the Fuzzy Logic method. This design was built using the Arduino module by combining four sensors, namely a pH sensor, a TDS sensor, a Turbidity sensor, and a temperature sensor. Water quality in this study was divided into three groups, namely drinking water (UM), water for washing (UC), and water not suitable for use (TL). While the water quality benchmarks are known from the incorporation of existing sensor readings, so that the value of water quality measured in the study is in the unsuitable category with a fuzzy value of 100 in sample 1, and to use washing with a fuzzy value of 45.68 in sample 2, and 26.4 in sample 3.

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“…Variabel input suhu dalam dan suhu luar ruangan dibuat dalam tiga kategori himpunan yaitu dingin, sedang dan panas dengan range kerja 0o C -50o C, sedangkan variabel kelembaban dalam dan kelembaban luar ruangan dibuat dalam 3 kategori himpunan yaitu basah, sedang dan kering pada range kerja 30 % -70 %. Untuk variabel output exhaust fan dibuat dalam 3 kondisi himpunan yaitu off (0) , lambat (1) dan cepat (2), variabel output kipas angin dibuat dalam 4 kondisi himpunan yaitu off (0), lambat (1), sedang (2), cepat (3). Rule base dijadikan dasar untuk cutomisasi kipas, ada 81 rule customisasi yang dibuat untuk otomatisasi kipas.…”

Section: Metodologi Penelitianunclassified

Sistem Fuzzy Inferensi Untuk Customise Fan Pada Sistem Rumah Cerdas

Farmadi

Kartini²,

Muliadi³

2020

klik

Self Cite

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AbstractSmart machine-based home development is becoming the current trend because the system can be controlled intelligently by machines. The air conditioning system without the use of air conditioning requires a type of fan to stabilize the temperature and humidity outside the house and inside the house using a blower fan or also called an exhaust fan, but this fan is only limited to circulating air circulation between the outside air and inside the house so that the tendency for the inside air adjust to the outside air, to control the air according to the user it will be manually customized by the user. And for fans in the home room a fan is used which blows air around the fan in circulation. The application of the fuzzy system can provide a fan rotation system that is done intelligently by the machine, which can adjust the balance between the outside air and indoor air to reach air confort or cool. Fuzzy system is applied using Sugeno fuzzy inference using 81 rules to customize the exhaust fan and fan in the room.Keywords: Fuzzy system, Smart home, Sugeno fuzzy.

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Sistem Fuzzy Logic Tertanam Pada Mikrokontroler Untuk Penyiraman Tanaman Pada Rumah Kaca

Abstract: Abstract

Cited by 6 publications

References 0 publications

Smart Farming Optimization of Phalaenopsis Orchids Growth By Utilizing Fuzzy Logic Control on IoT Architecture

Smart Farming Optimization of Phalaenopsis Orchids Growth By Utilizing Fuzzy Logic Control on IoT Architecture

Sistem Pendeteksi Kualitas Air Di Sekitar Pesisir Pantai Tondo Menggunakan Metode Fuzzy Logic

Sistem Fuzzy Inferensi Untuk Customise Fan Pada Sistem Rumah Cerdas

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