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All Journal Jiko (Jurnal Informatika dan komputer) IJISTECH (International Journal Of Information System & Technology) IJISTECH
Nur Ahlina Febriyati
UNIVERSITAS 45 SURABAYA
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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GRDP Growth Rate Clustering in Surabaya City uses the K-Means Algorithm Nur Ahlina Febriyati; Achmad Daengs GS; Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 3, No 2 (2020): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i2.60

Abstract

Gross Regional Domestic Product (GRDP) is an indicator used to measure economic performance in a period. GRDP is the amount of added value generated by all business units in a particular area. It can also be said to be the sum of the value of the final goods and services produced by all economic units. Therefore, this study aims to cluster the GRDP Growth Rate according to business fields in the city of Surabaya, so that it is known which sectors have high or low growth. The clustering algorithm used is K-Means. By using this method, the data will b,e grouped into several clusters, where the implementation of the K-Means Clustering process uses the Rapid Miner tools. The data used is the GRDP Growth Rate in Surabaya City by Business Field, 2010-2019 (Percent). The data is divided into 3 clusters: high, medium, and low. The results obtained are nine categories/sectors with high clusters, 5 categories / sectors with medium clusters, and three categories,s / sectors with low clusters. This can be input and information for the Surabaya City government to further maximize efforts to increase the GRDP Growth Rate in the area.
Analysis of Backpropagation Algorithm Using the Traingda Function for Export Prediction in East Java Nur Ahlina Febriyati; Achmad Daengs GS
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v4i1.95

Abstract

Exports are significant for a country's economic development, especially in regions that carry out export activities because not all countries and regions have the same natural and human resources. Therefore this study aims to predict the level export of oil, gas, and others in the province of East Java and understand the forecast for the number of exports in the coming year. This is important to provide information to the East Java provincial government so that it can make policies so that the export value can be increased, at least so that the export value remains stable. The prediction algorithm used is the Backpropagation Neural Network algorithm using the Gradient Descent training function with Adaptive Learning rate. The research data is data on the Export of oil, gas, and others in East Java Province from 2008 to 2019. The prediction process analysis uses 3 network architecture models, namely: 5-10-1, 5-15-1, and 5-20-1. Based on the analysis results, the 5-10-1 model is the best compared to the other two models with an accuracy rate of more than 90% and MSE testing 0.0012454304, which means that this model is good for predicting the export of oil, gas, and others.
PERANCANGAN SISTEM INFORMASI PENJUALAN ONLINE BERBASIS WEB PADA BATIK WIDI NUGRAHA NGAWI Nur Ahlina Febriyati; M. Yusuf Arnol
JIKO (Jurnal Informatika dan Komputer) Vol 3, No 3 (2020)
Publisher : Journal Of Informatics and Computer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v3i3.2270

Abstract

Salah satu rumah industri batik yang terkenal di kota Ngawi, Jawa Timur yaitu Batik Widi Nugraha. Unit usaha kecil menengah ini fokus memproduksi kain batik. Sistem Penjualan yang diterapkan pada unit usaha ini masih manual, belum memungkinkan untuk memperluas area pemasaran dan menjangkau semua wilayah, serta sulitnya memperoleh informasi mengenai produk Batik Widi Nugraha. Diperlukan suatu sistem penjualan online berbasis website yang dapat mempermudah dalam memasarkan dan menjual produk batik tersebut secara luas. Tujuan dari penelitian ini adalah untuk merancang sistem informasi penjualan online berbasis website yang terintegrasi. Metodologi yang digunakan untuk perancangan dan pengembangan sistem penjualan online ini, adalah metodologi terstruktur dengan model SDLC (System Development Life Cycle). Dengan adanya sistem informasi penjualan ini, masyarakat semakin mudah untuk mencari dan mendapatkan informasi tentang Batik Widi Nugraha Ngawi berupa informasi produk yang ditawarkan dan melakukan pembelian tanpa harus datang ke toko. Sistem informasi ini dirancang dengan menggunakan use case diagram. Dari hasil perancangan didapatkan bahwa perancangan sistem informasi berjalan terintegrasi dengan baik antara bagian administrator, pemilik toko dan pelanggan. Perancangan sistem informasi penjualan online berbasis website dapat membantu usaha Batik Widhi Nugraha untuk lebih berkembang dan meningkat hasil omset penjualannya sehingga dapat berimplikasi pada peningkatan pelayanan terhadap pelanggan (konsumen) dan manajemen administrasi.
Analysis of Backpropagation Algorithm Using the Traingda Function for Export Prediction in East Java Nur Ahlina Febriyati; Achmad Daengs GS
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (927.399 KB) | DOI: 10.30645/ijistech.v4i1.95

Abstract

Exports are significant for a country's economic development, especially in regions that carry out export activities because not all countries and regions have the same natural and human resources. Therefore this study aims to predict the level export of oil, gas, and others in the province of East Java and understand the forecast for the number of exports in the coming year. This is important to provide information to the East Java provincial government so that it can make policies so that the export value can be increased, at least so that the export value remains stable. The prediction algorithm used is the Backpropagation Neural Network algorithm using the Gradient Descent training function with Adaptive Learning rate. The research data is data on the Export of oil, gas, and others in East Java Province from 2008 to 2019. The prediction process analysis uses 3 network architecture models, namely: 5-10-1, 5-15-1, and 5-20-1. Based on the analysis results, the 5-10-1 model is the best compared to the other two models with an accuracy rate of more than 90% and MSE testing 0.0012454304, which means that this model is good for predicting the export of oil, gas, and others.
GRDP Growth Rate Clustering in Surabaya City uses the K-Means Algorithm Nur Ahlina Febriyati; Achmad Daengs GS; Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 3, No 2 (2020): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (780.092 KB) | DOI: 10.30645/ijistech.v3i2.60

Abstract

Gross Regional Domestic Product (GRDP) is an indicator used to measure economic performance in a period. GRDP is the amount of added value generated by all business units in a particular area. It can also be said to be the sum of the value of the final goods and services produced by all economic units. Therefore, this study aims to cluster the GRDP Growth Rate according to business fields in the city of Surabaya, so that it is known which sectors have high or low growth. The clustering algorithm used is K-Means. By using this method, the data will b,e grouped into several clusters, where the implementation of the K-Means Clustering process uses the Rapid Miner tools. The data used is the GRDP Growth Rate in Surabaya City by Business Field, 2010-2019 (Percent). The data is divided into 3 clusters: high, medium, and low. The results obtained are nine categories/sectors with high clusters, 5 categories / sectors with medium clusters, and three categories,s / sectors with low clusters. This can be input and information for the Surabaya City government to further maximize efforts to increase the GRDP Growth Rate in the area.
Co-Authors GS , Achmad Daengs M. Yusuf Arnol Wanto, Anjar