Optimalisasi Rekonstruksi Data Hilang untuk Meningkatkan Presisi Prediksi Waktu Salat Berbasis GRU di Wilayah Empat Musim
Adelia Khansa Ristiaputri(1); Aji Prasetya Wibawa(2*); Adhelia Wida Khaidir(3); Dhia Rafifah Thifal(4); Adelia Desyana Eka Putri(5); Agung Bella Putra Utama(6);
(1) Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia
(2) Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia
(3) Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia
(4) Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia
(5) Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia
(6) Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia
(*) Corresponding Author
AbstractPeramalan waktu sholat di wilayah empat musim menghadapi tantangan besar akibat variabilitas musiman ekstrem dan risiko ketidaklengkapan data sensorik yang mengganggu kontinuitas informasi. Penelitian ini bertujuan untuk mengevaluasi pengaruh berbagai metode imputasi terhadap kinerja model peramalan GRU pada data deret waktu yang merepresentasikan dinamika astronomi dan meteorologi. Metodologi penelitian melibatkan pengujian enam teknik imputasi pada tiga dataset dengan karakteristik berbeda, yaitu variabilitas musiman jangka panjang, pola siklik non-linear, dan dinamika jangka pendek resolusi tinggi. Model GRU dioptimasi menggunakan PSO untuk memastikan akurasi parameter yang maksimal. Hasil eksperimen menunjukkan bahwa model GRU secara konsisten mengungguli LSTM, Bi-LSTM, dan RNN, ditunjukkan oleh nilai MAPE dan RMSE yang lebih rendah serta R² yang lebih tinggi. Metode imputasi sederhana seperti Mean dan LOCF terbukti lebih efektif dibandingkan KNN dan MICE dalam menjaga struktur temporal data. Pada Dataset 1, kombinasi Mean–GRU menghasilkan MAPE 0,74074, RMSE 3,25932, dan R² 0,92828; pada Dataset 2, LOCF mencapai kinerja terbaik dengan MAPE 1,36115, RMSE 16,22207, dan R² 0,93766; sedangkan pada Dataset 3, Median menunjukkan performa optimal dengan MAPE 0,34435, RMSE 1,18365, dan R² 0,98420. Temuan ini menegaskan bahwa preservasi integritas temporal melalui strategi imputasi yang tepat berperan penting dalam meningkatkan kinerja model peramalan waktu sholat.
KeywordsGated Recurrent Unit; Imputasi Data; Peramalan Deret Waktu; Waktu Sholat; Optimasi Particle Swarm
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