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All Journal Jurnal Manajemen & Keuangan Jurnal EMT KITA Jurnal Sains Sosio Humaniora Jurnal Ekonomi dan Kebijakan Publik Indonesia Jurnal Penelitian Ekonomi Akuntansi (JENSI) Jurnal Samudra Ekonomika Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Prosiding Seminar Nasional Universitas Serambi Mekkah Akuntansi: Jurnal Riset Ilmu Akuntansi
Martahadi Mardhani
Faculty Of Economics, Universitas Samudra (UNSAM), Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Mechanical Engineering Social Sciences Other

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Journal : Jurnal Sains Sosio Humaniora

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Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis Nurhasanah Nurhasanah; Nany Salwa; Lyra Ornila; Amiruddin Hasan; Martahadi Mardhani
Jurnal Sains Sosio Humaniora Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Desember 2021
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jssh.v5i2.15801

Abstract

The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.
The impact of foreign direct investment and government expenditure on economic growth: Empirical evidence from Indonesian economy Ratna Mutia; Khairul Aswadi; Martahadi Mardhani; Amiruddin Hasan; Amrusi Amrusi
Jurnal Sains Sosio Humaniora Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Desember 2021
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This paper examines the impact of economic growth through foreign direct investment and government expenditure for 2000-2020 on the Indonesian economy. We have applied an ordinary least squares regression (OLS) approach to estimate these parameters. Our findings show that government expenditure and foreign direct investment (FDI) positively and significantly impact economic growth. Further research using disaggregated data is needed to determine the more profound impact on economic growth.
Classifying Regencies and Cities on Human Development Index Dimensions: Application of K-means Cluster Analysis Nurhasanah Nurhasanah; Nany Salwa; Lyra Ornila; Amiruddin Hasan; Martahadi Mardhani
Jurnal Sains Sosio Humaniora Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Desember 2021
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jssh.v5i2.15753

Abstract

The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators
Co-Authors A. Razak Amiruddin Hasan Amrusi Asmaul Husna Debi Febriana Br Siregar Elidar Elidar Gusti Pratiwi Khairul Aswadi Lyra Ornila Lyra Ornila Miranda Ariska Nany Salwa Nany Salwa Nurhasanah Nurhasanah Nurhasanah Nurhasanah, Nurhasanah Nurlaila Hanum Ratna Mutia Ratna Mutia Ratna Mutia Rizal Yani Safuridar, Safuridar Suri Amilia Syardiansah, Syardiansah