Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal INTEKNA Journal of Informatics Management and Information Technology
Ramadana, Rica
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Informatics Management and Information Technology

 1 
Analisis Backpropagation Dalam Menentukan Jumlah Perusahaan Industri Besar Dan Sedang (IBS) Di Indonesia Pramesti, Adinda Frizy; Ramadana, Rica; Beauti, Intan; Febiola, Adinda; Windarto, Agus Perdana
Journal of Informatics Management and Information Technology Vol. 4 No. 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v4i4.414

Abstract

Companies are economic actors whose main function is to produce goods and services needed by the community. However, in 2020, the COVID-19 pandemic had an impact on various economic activities, causing many workers to lose their jobs and the unavailability of new jobs, which led to an increase in unemployment in Indonesia. Therefore, strategic steps are needed to prevent an increase in the number of unemployed. One of them is to forecast the number of IBS companies for the next few years. Implementing early prevention as a step to identify new job opportunities in the industry. The forecast data is the number of IBS companies (large and medium industrial companies) collected by BPS for the period 2015-2022. The algorithm used for prediction is a backpropagation artificial neural network. This algorithm is able to remember what existed before and make generalizations from it. This backpropagation algorithm uses five architectural models including 6-10-1, 6-20-1, 6-35-1, 6-45-1, and 6-60-1. Of the five architectural models used, the best architecture was chosen, namely 6-35-1 which has an accuracy of 88%, MSE of 0.003821515 and the error rate used is 0.001-0.07. So this architectural model is good enough to predict the number of IBS companies.
Co-Authors Agus Perdana Windarto Beauti, Intan Febiola, Adinda Pramesti, Adinda Frizy Suhendro, Dedi