Rancang Bangun Pengendali Suhu Dan Intensitas Cahaya Pada Smart Farming System Tanaman Cabai Rawit Hidroponik Berbasis Interval Type-2 ANFIS.

Faudia, Nabila Putri (2026) Rancang Bangun Pengendali Suhu Dan Intensitas Cahaya Pada Smart Farming System Tanaman Cabai Rawit Hidroponik Berbasis Interval Type-2 ANFIS. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pengembangan smart farming menjadi salah satu upaya mendukung ketahanan pangan di tengah keterbatasan lahan yang sejalan dengan pencapaian SDGs 2 (Zero Hunger) melalui peningkatan produktivitas pertanian berbasis teknologi modern. Penelitian ini merancang greenhouse semi permanen berukuran 2,5 m × 2,5 m × 2,5 m yang dilengkapi sistem hidroponik NFT dan aeroponik sebagai media budidaya tanaman cabai rawit (Capsicum frutescens) yang dilengkapi dengan sistem pengendali suhu dan intensitas cahaya. Suhu dan intensitas cahaya dipilih sebagai parameter kendali karena keduanya sangat memengaruhi laju pertumbuhan tanaman dengan Set point masing-masing sebesar 27 °C dan 16.000 lux. Sistem kontrol yang digunakan yaitu Interval Type-2 Adaptive Neuro-Fuzzy Inference System (IT2-ANFIS) dengan sensor DHT22 dan BH1750 sebagai umpan balik serta kipas, lampu, dan motor DC penggerak paranet sebagai aktuator yang dikendalikan melalui sinyal PWM dan relay berbasis mikrokontroler ESP32. Performa sistem diuji secara closed-loop yang dianalisis dari karakteristik dinamik (delay time, rise time, settling time, Overshoot/ undershoot, steady-state error) serta metrik evaluasi (MSE, RMSE, MAE, MAPE). Hasil pengujian menunjukkan IT2-ANFIS mampu mengendalikan suhu menuju Set point 27 °C dengan steady-state error (ESS) sebesar 4,01% dan MAPE 7,6%, serta dapat mengendalikan intensitas cahaya menuju Set point 16.000 lux dengan ESS terbaik sebesar 0,05% pada kondisi paranet tertutup. Secara keseluruhan greenhouse yang dirancang mampu mendukung pertumbuhan tanaman cabai rawit pada sistem hidroponik NFT dan aeroponik serta sistem kendali IT2-ANFIS terbukti mampu menjaga suhu dan intensitas cahaya tetap stabil mendekati Set point tanpa Overshoot/undershoot yang berlebihan.
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The development of smart farming serves as a strategy to bolster food security amidst land constraints, aligning with the achievement of SDG 2 (Zero Hunger) by enhancing agricultural productivity through modern technology. This study involved the design of a semi-permanent greenhouse (2.5 m × 2.5 m × 2.5 m) equipped with NFT hydroponic and aeroponic systems for cultivating bird's eye chili (Capsicum frutescens), featuring temperature and light intensity control systems. Temperature and light intensity were selected as control parameters due to their significant impact on plant growth rates with Set points of 27°C and 16,000 lux, respectively. The control system employed an Interval Tipe-2 Adaptive Neuro-Fuzzy Inference System (IT2-ANFIS), utilizing DHT22 and BH1750 sensors for feedback, while fans, lights, and a DC motor for the shading net served as actuators controlled via PWM signals and relays driven by an ESP32 microcontroller. System performance was tested in a closed-loop configuration and analyzed based on dynamic characteristics (delay time, rise time, settling time, Overshoot/undershoot, steady-state error) and evaluation metrics (MSE, RMSE, MAE, MAPE). Test results demonstrated that the IT2-ANFIS successfully regulated temperature toward the 27°C Set point with a steady-state error (ESS) of 4.01% and MAPE of 7.6%, and controlled light intensity toward the 16,000 lux Set point with an optimal ESS of 0.05% when the shading net was closed. Overall, the designed greenhouse effectively supported bird's eye chili growth within the NFT hydroponic and aeroponic systems, and the IT2-ANFIS control system proved capable of maintaining stable temperature and light intensity levels close to the Set points without excessive Overshoot or undershoot.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	greenhouse, hidroponik, Interval Type-2 Adaptive Neuro-Fuzzy Inference System (IT2-ANFIS), suhu dan intensitas cahaya, SDGs 2 (Zero Hunger), greenhouse, hydroponics, Interval Type-2 Adaptive Neuro-Fuzzy Inference System (IT2-ANFIS), temperature and light intensity, SDGs 2 (Zero Hunger)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Nabila Putri Faudia
Date Deposited:	01 Aug 2026 03:32
Last Modified:	01 Aug 2026 03:32
URI:	http://repository.its.ac.id/id/eprint/141473

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