Implementasi Support Vector Machine pada Sistem Monitoring Kualitas Air Berbasis IoT
DOI:
https://doi.org/10.29407/yvg0v683Abstract
Kualitas air merupakan salah satu faktor penting yang memengaruhi kesehatan manusia dan kelestarian lingkungan. Pemantauan kualitas air secara konvensional masih memerlukan pengukuran manual yang kurang efisien untuk pengawasan berkelanjutan. Penelitian ini mengembangkan sistem monitoring kualitas air berbasis Internet of Things (IoT) yang terintegrasi dengan algoritma Support Vector Machine (SVM) untuk melakukan klasifikasi kualitas air secara realtime. Sistem menggunakan sensor pH, Total Dissolved Solids (TDS), dan turbidity yang terhubung dengan mikrokontroler ESP32. Data sensor dikirim melalui jaringan WiFi menuju server dan diproses menggunakan model SVM yang telah dioptimasi menggunakan GridSearchCV. Dataset yang digunakan terdiri dari 4.259 data dengan dua kelas yaitu normal dan tercemar. Hasil evaluasi menunjukkan bahwa model SVM memperoleh akurasi sebesar 99,65% pada data pengujian. Sistem yang dikembangkan berhasil menampilkan data sensor dan hasil klasifikasi secara realtime melalui dashboard berbasis web. Hasil penelitian menunjukkan bahwa integrasi IoT dan machine learning mampu menghasilkan sistem monitoring kualitas air yang efektif, otomatis, dan mudah diakses
Keywords:
GridSearchCV, Internet of Things, Kualitas Air, Support Vector Machine, Water Monitoring##plugins.themes.default.displayStats.downloads##
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