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All Journal Jurnal Informatika Ekonomi Bisnis Jurnal Pustaka Robot Sister
Aulya, Nurul
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Mathematics Mechanical Engineering

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Prediksi Kunjungan Wisata Kota Payakumbuh Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Aulya, Nurul
Jurnal Informatika Ekonomi Bisnis Vol. 4, No. 4 (December 2022)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (582.455 KB) | DOI: 10.37034/infeb.v4i4.157

Abstract

Tourism is a whole related elements which consist of tourists, tourist destinations, travel, industry and so on which are tourism activities and abundant natural wealth. The tourism sector is a very important service-based sector. Tourism is the fastest growing, vibrant and strong economic sector development, it also contributes to Gross Domestic Product (GDP), job creation, social and economic development. Artificial Neural Networks are computer programs that can imitate thought processes and knowledge to solve a specific problem. One of which is applied by the Artificial Neural Network to predict tourist visits. By using the Backpropagation method, it will be known the prediction of the number of tourist visits. The Backpropagation method is very useful for Artificial Neural Networks predicting the number of tourist visits the following year. The data processed in this study were 12 data sourced from the tourism section of the Payakumbuh City Youth and Sports Tourism Office. Furthermore, the data is processed using Matlab software. The stages of backpropagation are initialization, activation, training and iteration. The calculation of the network pattern used and the accuracy level of the expected error is continued. The result of testing this method is that it can predict tourist visits. So the level of accuracy is 95%. The prediction process has been carried out to predict tourist visits to the city of Payakumbuh. With the level of accuracy obtained is met, it can be used to help the Payakumbuh City Tourism Office increase the number of tourist visits in the future and further improve tourism management.
Implementasi Hybrid Data Mining Menggunakan DBSCAN, FP-Growth, dan Random Forest pada Analisis Penjualan Soraya Bedsheet di Shopee Mulyanda, Sandy; Aulya, Nurul; Gusrianty, Gusrianty
Jurnal Pustaka Robot Sister (Jurnal Pusat Akses Kajian Robotika, Sistem Tertanam, dan Sistem Terdistribusi) Vol 4 No 2 (2026): Jurnal Pustaka Robot Sister (Pusat Akses Kajian Robotika, Sistem Tertanam, dan Si
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakarobotsister.v4i2.2139

Abstract

Pertumbuhan marketplace dalam beberapa tahun terakhir telah menghasilkan data transaksi dalam jumlah besar yang berpotensi dimanfaatkan sebagai sumber informasi bagi pelaku usaha. Namun, sebagian besar data penjualan masih digunakan sebatas laporan operasional sehingga informasi yang ada di dalamnya belum dimanfaatkan dengan optimal. Adapun tujuannya dari penelitian ini guna menganalisa karakteristik penjualan dan memprediksi performa penjualan produk Soraya Bedsheet pada Shopee melalui pendekatan hybrid data mining. Metode yang digunakan mengombinasikan DBSCAN untuk segmentasi produk, FP-Growth untuk analisis asosiasi antarproduk, dan Random Forest untuk prediksi penjualan. Dataset penelitian terdiri atas 120 data produk, jumlah stok, jumlah produk terjual, dan harga awal produk. Tahapan penelitian meliputi pengumpulan data, preprocessing, implementasi model, serta evaluasi dengan digunakannya RapidMiner. Temuan ini mengungkapkan bahwasanya  DBSCAN mampu mengklasifikasikan produk sebagaimana karakteristik penjualannya, FP-Growth berhasil menemukan pola keterkaitan antarproduk dalam transaksi, dan Random Forest memperoleh rata-rata accuracy sebesar 91,67% melalui 10-fold Cross Validation. Hasil penelitian menunjukkan bahwasanya pendekatan hybrid data mining mampu menghasilkan informasi yang mendukung pengelolaan stok, penyusunan strategi promosi, dan pengambilan keputusan bisnis secara lebih efektif pada marketplace Shopee.
Co-Authors Gusrianty, Gusrianty Mulyanda, Sandy