Peramalan Jumlah Kunjungan Wisatawan Mancanegara Ke Bali dengan Jaringan Saraf Tiruan Backpropagation
(1) STIMIK STIKOM Indonesia
(2) STIMIK STIKOM Indonesia
(*) Corresponding Author
Abstract
Full Text:
PDFReferences
C. J. Lin and T. S. Lee, “Tourism Demand Forecasting: Econometric Model based on Multivariate Adaptive Regression Splines, Artificial Neural Network and Support Vector Regression,” Adv. Manag. Appl. Econ., 2013.
S. Wardah and I. Iskandar, “Analisis Peramalan Penjualan Produk Keripik Pisang Kemasan Bungkus (Studi Kasus : Home Industry Arwana Food Tembilahan),” J@ti Undip J. Tek. Ind., 2017.
S. Herawati, “Peramalan Kunjungan Wisatawan Mancanegara Menggunakan Generalized Regression Neural Networks,” J. INFOTEL - Inform. Telekomun. Elektron., 2016.
M. Agustin and T. Prahasto, “Penggunaan Jaringan Syaraf Tiruan Backpropagation Untuk Seleksi Penerimaan Mahasiswa Baru Pada Jurusan Teknik Komputer Di Politeknik Negeri Sriwijaya,” J. Sist. Inf. BISNIS, 2012.
Badan Pusat Statistik, “Jumlah Kunjungan Wisatawan Mancanegara per Bulan ke Indonesia Menurut Pintu Masuk,” 2019. [Online]. Available: https://www.bps.go.id/dynamictable/2018/04/05 00:00:00/1296/jumlah-kunjungan-wisatawan-mancanegara-per-bulan-ke-indonesia-menurut-pintu-masuk-2017-2019.html. [Accessed: 24-Jan-2020].
M. D. Wuryandari and I. Afrianto, “Perbandingan Metode Jaringan Syaraf Tiruan Backpropagation Dan Learning Vector Quantization Pada Pengenalan Wajah,” Komputa, 2012.
A. P. Hadi and E. Riksakomara, “Artificial Neural Malang Ann Method Implementation To Predict Rainfall in Case of Dengue Fever Anticipation in Malang District,” Institut Teknologi Surabaya, Surabaya, 2018.
S. Kuninti and S. Rooban, “Backpropagation Algorithm and its Hardware Implementations: A Review,” J. Phys. Conf. Ser., vol. 1804, no. 1, 2021.
J. Renteria-Cedano, J. Rivera, F. Sandoval-Ibarra, S. Ortega-Cisneros, and R. Loo-Yau, “Soc design based on a FPGA for a configurable neural network trained by means of an EKF,” Electron., vol. 8, no. 7, pp. 1–19, 2019.
Nasri, “Kecerdasan buatan ( Artificial Intelligence ),” Artif. Intell., 2014.
G. Amaral et al., Time Series Analysis Forecasting and Control, vol. 369, no. 1. 2013.
L. S. Lubis and A. Buono, “Pemodelan Jaringan Syaraf Tiruan Untuk Memprediksi Awal Musim Hujan Berdasarkan Suhu Permukaan Laut Artificial Neural Network Modeling To Predict The Beginning of Rainy Season Based On Sea Surface Temperature,” J. ilmu Komput. Agri-inforatika, vol. 1, pp. 52–61, 2012.
M. N. D. Sawitri, I. W. Sumarjaya, and N. K. T. Tastrawati, “Peramalan Menggunakan Metode Backpropagation Neural Network,” E-Jurnal Mat., vol. 7, no. 3, pp. 264–270, Sep. 2018.
A. Sudarsono, “Jaringan Syaraf Tiruan Untuk Memprediksi Laju Pertumbuhan Penduduk Menggunakan Metode,” Media Infotama, 2016.
T. W. Khusniyah and S. Sutikno, “Prediksi Nilai Tukar Petani Menggunakan Jaringan Syaraf Tiruan Backpropagation,” Sci. J. Informatics, vol. 3, no. 1, pp. 11–18, 2016.
D. Monika, A. Ahmad, S. Wardani, and Solikhun, “Model Jaringan Syaraf Tiruan Dalam Memprediksi Ketersediaan Cabai Berdasarkan Provinsi,” Teknika, vol. 8, no. 1, pp. 17–24, 2019.
S. P. Sinaga, A. Wanto, and S. Solikhun, “Implementasi Jaringan Syaraf Tiruan Resilient Backpropagation dalam Memprediksi Angka Harapan Hidup Masyarakat Sumatera Utara,” Infomedia, vol. 4, no. 2, pp. 81–88, 2019.
S. Setti and A. Wanto, “Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World,” J. Online Inform., vol. 3, no. 2, p. 110, 2019.
DOI: http://dx.doi.org/10.30645/j-sakti.v6i1.464
Refbacks
- There are currently no refbacks.
J-SAKTI (Jurnal Sains Komputer & Informatika)
Published Papers Indexed/Abstracted By:
Jumlah Kunjungan :