Repository Universitas PakuanPrediksi Harga Daging Ayam Ras Menggunakan Long Short-Term Memory (LSTM)Muhamad HaikalFirdausauthorPrediksi Harga Daging Ayam Ras Menggunakan Long Short-Term Memory (LSTM). Di bawah bimbingan Dr. Eneng Tita Tosida, S.Tp., M.Si., M.Kom. dan Syarif Hidayatullah, M.Kom. Harga daging ayam ras di Kota Bogor kerap berfluktuasi tajam sehingga me�nyulitkan peternak, pedagang, dan pemangku kebijakan dalam mitigasi risiko pasar. Penelitian ini bertujuan membangun model prediksi harga harian ayam ras menggunakan Multivariate Long Short-Term Memory (LSTM), dengan menginte�grasikan harga pakan jagung pipilan, indikator hari libur, dan efek Lebaran. Pengem�bangan sistem mengikuti kerangka Knowledge Discovery in Databases (KDD) dan diimplementasikan sebagai aplikasi web berbasis Streamlit. Pada tahap pra-pem�rosesan, data harga ayam mentah dikoreksi dari pola stagnasi (Last Observation Car�ried Forward) menjadi interpolasi linear selektif, sementara hubungan harga ayam dan pakan diuji melalui korelasi Pearson dan Granger Causality Test. Hyperparame�ter tuning menghasilkan konfigurasi akhir window lookback 14 hari dengan arsi�tektur LSTM (32)→Dropout→LSTM(16)→ Dropout→Dense(16)→ Dense(1). Hasil evaluasi pada data uji menunjukkan MAE Rp180, RMSE Rp441, dan MAPE 0,45%, tergolong sangat akurat. Sistem juga mampu menyimulasikan skenario peru�bahan harga pakan secara interaktif, dengan proyeksi harga ayam merespons pro�porsional dan searah, sehingga dapat digunakan sebagai instrumen pendukung kepu�tusan bagi peternak, pedagang, dan pemangku kebijakan di Kota Bogor. Kata Kunci: Deep Learning, Long Short-Term Memory, Multivariate Time Series, Prediksi Harga, Daging Ayam Ras, Knowledge Discovery in Databases.Ilmu Komputer2026-07-20Universitas Pakuan;Fakultas Matematika dan Pengetahuan AlamThesis

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