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All Journal Indonesian Journal of Electronics and Instrumentation Systems Indonesian Journal of Electrical Engineering and Computer Science
Ilona Usuman
Department of Computer Science and Electronics, Universitas Gadjah Mada
Electrical & Electronics Engineering

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Penerapan Sistem Integrasi Elektronik dan Pengamatan Perlakuan Sifat Jamur Berdasarkan Suhu dan Kelembaban Pada Ruang Tumbuh Jamur likasi RFID untuk Sistem Kuping (Auricularia Sp.) Ilona Usuman; Fitriyaningsih Fitriyaningsih
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 1, No 2 (2011): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.188 KB) | DOI: 10.22146/ijeis.1928

Abstract

AbstrakSalah satu jenis jamur yang dikenal selama ini adalah Jamur Kuping atau yang dalam bahasa latin disebut dengan Auricularia Sp. Jamur Kuping merupakan tanaman yang sangat sensitif terhadap suhu dan kelembaban lingkungan. Dengan alasan tersebut sehingga diterapkan suatu integrasi elektronik dan pengamatan terhadap perlakuan pertumbuhan jamur pada sistem pemantauan suhu dan kelembaban udara pada ruang pertumbuhan Jamur Kuping. Sistem ini dapat mengukur dan memantau suhu dan kelembaban suatu ruangan serta menampilkannya pada LCD Display. Sistem menggunakan mikrokontroller ATmega 8535. Sensor suhu, Sensor kelembaban yang digunakan yaitu seri SHT11, display menggunakan LCD 16x2 yang dilengkapi dengan keypad untuk memasukkan nilai suhu dan kelembaban yang akan ditentukan dan dilengkapi indikator berupa LED. Saat suhu hasil pembacaan aktual sensor lebih besar dari set point suhu maka LED kuning sebagai indicator suhu menyala, sedangkan jika kurang dari atau sama dengan set point maka LED kuning mati. Untuk Kelembaban, saat kelembaban hasil pembacaan aktual sensor lebih kecil dari set point kelembaban maka LED biru sebagai indikator kelembaban akan menyala, dan LED biru mati ketika kelembabannya kurang dari atau sama dengan set point kelembaban. Kata kunci— Jamur Kuping, Auricularia Sp, suhu, kelembaban, Mikrokontroller Atmega 8535, SHT 11 Abstract One type of fungus that is known for this fungus in the ear or the Latin language called Auricularia sp. Ear fungus is a plant that is very sensitive to temperature and humidity environment. For all these reasons that applied to an electronic integration and observations on the treatment of fungal growth on the system monitoring temperature and humidity on the growth of fungus ear space. This system can measure and monitor temperature and humidity of a room and display it on LCD Display. System using a microcontroller ATmega 8535. Temperature sensor, humidity sensor used is SHT11 series, using a 16x2 LCD display is equipped with a keypad to enter the temperature and humidity to be determined and furnished in the form of LED indicators. When the actual temperature sensor readings greater than the set point temperature of the LED lights yellow as a temperature indicator, whereas if it is less than or equal to the set point then the yellow LED die. For humidity, while the actual humidity sensor readings is smaller than the humidity set point as a blue LED indicator will light up the moisture and the blue LED die when the humidity is less than or equal to the set point humidity. Keywords— Ear fungus, Auricularia Sp, temperature, humidity, microcontroller Atmega 8535, SHT 11
Integrating random forest model and internet of things-based sensor for smart poultry farm monitoring system Imam Fahrurrozi; Wahyono Wahyono; Yunita Sari; Anny Kartika Sari; Ilona Usuman; Bambang Ariyadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp1283-1292

Abstract

The global poultry industry has encountered growing concerns related to foodborne illnesses, misuse of antibiotics, and environmental impacts. To tackle these issues, this study aims to develop an intelligent poultry farm with real-time environmental monitoring and predictive models. The primary objective is to combine a machine learning-based prediction model with internet of things (IoT) devices to gather and analyze environmental data, such as temperature, humidity, and ammonia levels, to forecast the conditions within poultry houses. These sensor data and additional information, such as feed consumption, water consumption, poultry weight, capacity, and poultry house dimensions will serve as inputs for supervised machine learning models. Among these models, the proposed random forest (RF) model, when augmented with timestamp features, achieves the highest accuracy rate of 96.665%, surpassing other models such as logistic regression (LR), k-nearest neighbor (KNN), decision tree (DT), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), support vector machine (SVM), and multi-layer perceptron (MLP) in identifying poultry house conditions. Additionally, this study demonstrates how the trained model can be effectively applied in a web-based monitoring system, delivering real-time data to farmers for well-informed decision-making and ultimately enhancing productivity in smart poultry farming.
Co-Authors Anny Kartika Sari Bambang Ariyadi Fitriyaningsih Fitriyaningsih Imam Fahrurrozi Wahyono Wahyono Yunita Sari