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Analisis Pola Konsumsi Energi Listrik Rumah Tangga Berbasis Simulasi IoT Menggunakan Model Hybrid LSTM-Attention
Abstract
Pengelolaan energi listrik rumah tangga menjadi tantangan penting seiring meningkatnya kebutuhan energi
dan keterbatasan sumber daya. Penelitian ini mengusulkan pendekatan berbasis simulasi IoT untuk menganalisis pola konsumsi energi, mendeteksi anomali, dan memberikan rekomendasi efisiensi energi tanpa perangkat fisik, menggunakan model hybrid LSTM-Attention. Dataset simulasi (14.400 sampel) dibangun dengan
EnergyPlus, divalidasi terhadap data riil, dan diolah untuk mengevaluasi performa model. Hasil menunjukkan akurasi 96%, recall 0.95 untuk anomali, dan F1-score 0.96, melampaui baseline LSTM (91.5%). Mekanisme attention memprioritaskan power_usage_per_hour (bobot 0.47), meningkatkan deteksi anomali. Rekomendasi seperti penjadwalan ulang dan penggantian perangkat menghasilkan penghematan energi 20-40%. Dengan waktu pelatihan 1,5 jam pada Google Colab, pendekatan ini menawarkan solusi skalabel dan hemat biaya untuk pengelolaan energi berkelanjutan, dengan potensi pengujian riil dan peningkatan model di masa depan.
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DOI: http://dx.doi.org/10.26798/jiko.v9i2.1922
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