Evaluasi Prediksi Harga Komoditas Pangan Berbasis Recurrent Neural Network, Long Short-Term Memory, Dan Transformer

• NIKI AWALL OEDIN
• 14002441

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ABSTRAK

ABSTRAK

Nama              : Niki Awalloedin

NIM                 : 14002441

Program Studi : Ilmu Komputer

Jenjang            : Strata Dua (S2)

Konsentrasi      : Data Mining

Judul Tesis  : Evaluasi Prediksi Harga Komoditas Pangan Berbasis Recurrent Neural Network, Long Short-Term Memory, Dan Transformer

Penelitian ini penulis mencoba menerapkan algoritma RNN, LSTM, BILSTM dan Transformer dalam memprediksi harga komoditas pangan (Beras, Daging Ayam, Telur Ayam). Prediksi harga pangan akan sangat bermanfaat bagi konsumen maupun produsen, untuk pemerintah hal ini dapat menjadi penunjang keputusan dalam mengambil langkah yang tepat untuk menjamin harga pangan tetap terjangkau oleh masyarakat. Dalam penelitian ini menggunakan data history time series tahun 2017 – 2023 yang terdapat pada situs Pusat Informasi Harga Pangan Strategis Nasional (PIHPSN) pada alamat website https://hargapangan.id/, dalam website terbut terdapat daftar komoditas pangan strategis diantaranya yaitu Beras, Daging Ayam, Telur. Data tersebut akan digunakan sebagai data dasar dalam penelitian ini. Data series pangan tersebut akan diproses menggunakan algoritma RNN, LSTM , BiLSTM. Dan Transformer

KATA KUNCI

Data Mining,Time Series,RNN,LSTM,BiLSTM

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DAFTAR PUSTAKA

DAFTAR PUSTAKA

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