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All Journal Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Royali, Rainer Maghma
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Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science

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Sistem Kendali Mikroklimat Greenhouse Cerdas Berbasis Hybrid GA-LSTM dan Fuzzy Logic Controller Royali, Rainer Maghma; Ariatmanto, Dhani
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 2 (2026): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i2.1798

Abstract

Controlling temperature and humidity in greenhouses is a complex challenge due to its non-linear nature and dependence on external weather conditions. Conventional control methods often experience energy inefficiency and delayed responses to drastic changes. This study proposes a hybrid approach by combining Long Short-Term Memory (LSTM) optimized using Genetic Algorithm (GA) for temperature prediction, and Fuzzy Logic Controller (FLC) for actuator decision-making. Genetic Algorithm is employed to find optimal hyperparameters (number of neurons and batch size) in the LSTM architecture. Experimental results demonstrate the GA-LSTM model's capability in predicting temperature with high accuracy, yielding an R² score of 0.9881 and Root Mean Square Error (RMSE) of 1.1273°C. These accurate predictions are subsequently used as input to the FLC to regulate exhaust fan speed and mist pump status. Simulations demonstrate the system's capability in making energy-efficient decisions—activating actuators only when conditions are predicted to deviate from ideal values—while remaining responsive to extreme temperature anomalies.
Co-Authors DHANI ARIATMANTO