Model Neural Network Autoregressive untuk Prediksi Inflasi Bulanan di Kota Yogyakarta
نویسندگان
چکیده
AbstrakYogyakarta sebagai kota pelajar, pariwisata ataupun budaya sangatlah ramai aktifitas ekonominya karena banyak sekolah, universitas, tempat wisata dan juga yang tentunya mahasiswa, wisatawan dalam negeri maupun luar berkunjung ke tersebut. Aktifitas mahasiswa di Yogyakarta ini bisa meningkatkan perekonomian seperti kost, penginapan atau hotel serta tidak ketinggalan makan, belanja lain sebagainya. Penelitian mempunyai tujuan untuk memprediksi inflasi bulanan Data sekunder diperoleh dari BPS pusat. digunakan yaitu data mulai Januari 2006 sampai dengan Desember 2021, sebanyak 192 data. menggunakan model peramalan jaringan syaraf tiruan (JST) artificial neural network (ANN). Model JST ANN autoregressive (NNAR). NNAR algoritma backpropogation fungsi aktifasi sigmoid biner. Pengolahan pada penelitian R package statistics merupakan open source program. Hasil kesimpulan adalah terbaik NNAR(12,8) artinya input berupa lag-1 lag-12 koya single hiden layer 8 neuron. Akurasi ukur root mean square error (RMSE, sebesar 0.05962758), absolute (MASE, 0.1011443), percentage (MAPE, 28.32449). Saran lanjutan, hendaknya dibandingkan berbasis sistem cerdas (artificial intelegent, AI).
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ژورنال
عنوان ژورنال: Jurnal sistem dan teknologi informasi
سال: 2023
ISSN: ['2620-8989', '2460-3562']
DOI: https://doi.org/10.26418/justin.v11i2.54370