PREDIKSI POLUSI UDARA BERDASARKAN TINGKAT CURAH HUJAN MENGGUNAKAN MODEL LSTM, BILSTM DAN PROPHET
DOI:
https://doi.org/10.54314/jssr.v8i4.5764Abstract
Abstract: The city of Jakarta, as the center of Indonesia's economic life and growth, continues to experience an astonishing population surge, reaching 11,248,839 people by 2024. However, this growth is inseparable from negative consequences, such as increased activity and modernization, which significantly affect air quality. Air pollution, as a direct impact of these changes, has exceeded national air quality standards, endangering human, animal, and plant health. Understanding the relationship between air pollution and weather conditions is crucial in determining future control measures. In this study, we used the LSTM, BiLSTM, and Prophet models on air pollution data. The results show that the single BiLSTM model and the BiLSTM-Prophet hybrid model provide the best performance, with accuracy levels reaching 99.32% and 99.31%, respectively. These findings provide a solid basis for forecasting and controlling potential future air pollution levels, as well as identifying key factors contributing to air quality in the capital city. . Keyword: Air Pollution, LSTM, BiLSTM, Prophet, Rainfall Abstrak: Kota Jakarta, sebagai pusat kehidupan dan pertumbuhan ekonomi Indonesia, terus mengalami lonjakan penduduk yang menakjubkan, mencapai 11.248.839 orang pada tahun 2024. Namun, pertumbuhan ini tidak terlepas dari konsekuensi negatif, seperti peningkatan aktivitas dan modernisasi, yang secara signifikan mempengaruhi kualitas udara. Polusi udara, sebagai dampak langsung dari perubahan ini, telah melampaui standar kualitas udara nasional, membahayakan kesehatan manusia, hewan, dan tumbuhan. Memahami hubungan antara polusi udara dan kondisi cuaca sangat penting dalam menentukan langkah-langkah pengendalian di masa depan. Dalam penelitian ini, kami menggunakan model LSTM, BiLSTM, dan Prophet pada data polusi udara. Hasil penelitian menunjukkan bahwa model tunggal BiLSTM dan model hybrid BiLSTM-Prophet memberikan kinerja terbaik, dengan tingkat akurasi masing-masing mencapai 99,32% dan 99,31%. Temuan ini memberikan dasar yang kuat untuk memperkirakan dan mengendalikan potensi tingkat polusi udara di masa depan, serta mengidentifikasi faktor-faktor kunci yang berkontribusi terhadap kualitas udara di ibu kota. Kata kunci: Polusi udara, LSTM, BiLSTM, Prophet, Curah hujanDownloads
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