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All Journal EQIEN - JURNAL EKONOMI DAN BISNIS International Transactions on Education Technology (ITEE)
Anggi Rachmawati
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Control & Systems Engineering Decision Sciences, Operations Research & Management Social Sciences

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ANALISIS MODAL MANUSIA TERHADAP PERTUMBUHAN EKONOMI ANTAR PROPINSI DI PULAU JAWA Herman Sambodo; Anggi Rachmawati; Nunik Kadarwati; Oke Setiarso
Eqien - Jurnal Ekonomi dan Bisnis Vol 11 No 1 (2022): EQIEN- JURNAL EKONOMI DAN BISNIS
Publisher : Sekolah Tinggi Ilmu Ekonomi Dr Kh Ez Mutaqien

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (268.083 KB) | DOI: 10.34308/eqien.v11i1.819

Abstract

Economic growth is the main condition for increasing the standard of living of a country. Economic growth of a region is not only seen from the Gross Regional Domestic Product (GRDP) as a reference for regional welfare, it is also seen from the Human Development Index (HDI). The Human Development Index is an indicator that covers several qualities of human life, namely education, health and the laborforce. The purpose of this study was to analyze the effect of education, health and labor force variables on economic growth in Java Island. The analytical technique used in this study is a multiple liner regression analysis. The data used in this study is panel data, namely by combining time series and cross section data from 2010 to 2019 and 6 provinces in Java Island. The results showed that all the independent variables, namely education, health and the labor force together had a positive effect on economic growth. While the most influential variable on economic growth is education. Education is considered to have the most important role in determining human quality. The higher the education level of the labor, the higher the productivity and the higher the economic growth of a country.
Analysis of Machine Learning Systems for Cyber Physical Systems Anggi Rachmawati; Yossaepurrohman
International Transactions on Education Technology (ITEE) Vol. 1 No. 1 (2022): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v1i1.170

Abstract

This study summarizes major literature reviews on machine learning systems for network analysis and intrusion detection. Furthermore, it provides a brief lesson description of each machine learning approach. Because data is so important in machine learning methods, this study The primary tools for assessing network traffic and spotting anomalies are machine learning approaches, and the study focuses on the datasets utilized in these techniques. This research examine the multiple advantages (reasonable use) that machine learning has made possible, particularly for security and cyber-physical systems, including enhanced intrusion detection techniques and judgment accuracy. Additionally, this study discusses the difficulties of utilizing machine learning for cybersecurity and offers suggestions for further study.
Co-Authors Nunik Kadarwati Oke Setiarso Sambodo, Herman Yossaepurrohman