Prediksi Aktivasi Irigasi Menggunakan Data Kelembapan Tanah Multi-Sensor Berbasis Machine Learning pada Sistem IoT

Authors

  • Ceorido Ghalib Wibowo Universitas Negeri Semarang, Jawa Tengah, Indonesia
  • Much Aziz Muslim Universitas Negeri Semarang, Jawa Tengah, Indonesia

DOI:

https://doi.org/10.62411/tc.v25i1.15517

Abstract

Efisiensi penggunaan air merupakan aspek krusial dalam pertanian modern, terutama di wilayah dengan keterbatasan sumber daya air. Penelitian ini bertujuan untuk memprediksi aktivasi irigasi menggunakan data kelembapan tanah multi-sensor berbasis Internet of Things (IoT) dengan pendekatan machine learning. Dataset terdiri dari lima sensor kelembapan tanah (moisture0–moisture4) beserta label aktivasi irigasi. Tahapan penelitian mencakup pembersihan data, normalisasi, rekayasa fitur temporal, serta pelatihan tiga algoritma klasifikasi: Logistic Regression, Random Forest, dan Gradient Boosting. Hasil evaluasi menunjukkan bahwa Random Forest memiliki performa terbaik dengan akurasi 0.997, precision 0.990, recall 0.986, dan F1-Score 0.988. Gradient Boosting memperoleh F1-Score 0.965, sedangkan Logistic Regression mencapai 0.921. Temuan ini menunjukkan bahwa model berbasis ensemble lebih mampu menangkap kompleksitas pola kelembapan tanah dibandingkan pendekatan linier. Penelitian ini berkontribusi pada pengembangan sistem irigasi cerdas yang adaptif, efisien, dan berbasis data dalam implementasi smart farming. Kata kunci - IoT, kelembapan tanah, irigasi cerdas, machine learning, multi-sensor, prediksi irigasi

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Published

2026-02-26

Issue

Vol. 25 No. 1 (2026): February 2026

Section

Articles

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Copyright (c) 2026 Ceorido Ghalib Wibowo, Much Aziz Muslim

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