PREDIKSI WATER QUALITY INDEX (WQI) MENGGUNAKAN ALGORITMA REGRESSI DENGAN HYPER-PARAMETER TUNING
DOI:
https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v5i1.2492Keywords:
Machine Learning, Hyper-Parameter Tuning, Water Potability, Regression AlgorithmAbstract
Air merupakan salah satu sumber daya alam esensial untuk kelangsungan hidup seluruh makhluk hidup di dunia ini. Kita memerlukan air untuk kebutuhan kita sehari-hari, begitu juga dengan tanaman dan hewan yang memerlukan air untuk kelangsungan hidupnya. Indeks Kualitas Air (Water Quality Index/WQI) merupakan satuan untuk mengetahui apakah air dapat dinyatakan layak minum (Potable) atau tidak. Pada penelitian ini, untuk membuat prediksi nilai WQI lebih akurat dan memiliki tingkat akurasi model yang lebih tinggi, dirancang sebuah algoritma regresi yang kemudian akan dikonfigurasi kembali dengan tuning algoritma. Model machine learning yang telah dibuat memiliki nilai yang berbeda, namun pada penelitian ini telah ditentukan bahwasanya model Linear Regression yang dipakai sebagai model utama karena memiliki nilai R2 lebih tinggi (0.9965 / 96,5%). Sesuai dengan hasil plotting dari Linear Regression, data diprediksi dengan baik dan persebaran data masih berdekatan dengan prediksi model (robust).
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