Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal Journal of Intelligent Computing and Health Informatics (JICHI) Journal of Data Insights
Asyfani, Yusrisma
Unknown Affiliation
Computer Science & IT Dentistry Electrical & Electronics Engineering Mathematics Medicine & Pharmacology Public Health

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal of Data Insights

 1 
A Pengelompokan Kabupaten/Kota di Jawa Tengah Berdasarkan Kepadatan Penduduk Menggunakan Metode Hierarchical Clustering Asyfani, Yusrisma; Manfaati Nur, Indah; Fathoni Amri, Ihsan; Yunanita, Novia; Anggun Lestari , Febi; Aura Hisani, Zahra; Hikmah Nur Rohim, Febrian
Journal of Data Insights Vol 2 No 1 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i1.158

Abstract

Jawa Tengah merupakan provinsi dengan urutan kelima di Indonesia berdasarkan kepadatan penduduk pada tahun 2020 sebanyak 1.113 jiwa/km2. Pengaruh kepadatan penduduk yang tinggi dapat menyebabkan berbagai masalah diantaranya kemacetan,pengangguran,kesehatan,kriminalitas serta permasalahan serius lainnya. Kepadatan penduduk dipengaruhi oleh angka kelahiran,angka kematian serta laju pertumbuhan, Untuk mengevaluasi kepadatan penduduk di provinsi Jawa Tengah, kita perlu mengklasifikasikan/mengelompokkan kabupaten/kota yang berada didalamnya. Pengelompokan ini bertujuan agar kebijakan yang dibuat oleh pemerintah dapat tepat sasaran. Metode yang dapat digunakan untuk pengelompokkan kabupaten.kota di provinsi Jawa Tengah berdasarkan kepadatan penduduknya yaitu Clustering Hierarchical Ward. Dari hasil analisis pengelompokan tersebut kabupaten/kota di provinsi Jawa Tengah dibagi menjadi empat kelompok berdasarkan kepadatan penduduknya.
Implementation of Hierarchical Clustering for Grouping Economic Development Indicators in Central Java Province: Penggunaan Clustering Hierarki Untuk Pengelompokan Indikator Pembangunan Ekonomi di Provinsi Jawa Tengah Salmaa; Asyfani, Yusrisma; Manfaati Nur, Indah
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.298

Abstract

In the midst of global economic shifts, the economy in Indonesia must continue to improve. To help economic recovery after the contraction caused by the COVID-19 pandemic, the Indonesian government has implemented various policies. One way is through the process of increasing per capita income over a long period of time, known as economic development, provided that the number of people living below the absolute poverty line does not increase and income distribution does not decrease. Other efforts can be made by analyzing economic development indicators. One method that can be used is hierarchical cluster analysis to group economic development indicators in Central Java province. Average linkage is used as an approach method after carrying out correlation analysis of the five approaches in hierarchical analysis because the correlation value is the highest. From this analysis two clusters were produced with the first cluster having higher characteristic values compared to the second cluster.
Co-Authors Anggun Lestari , Febi Aura Hisani, Zahra Eny Winaryati Fathoni Amri, Ihsan Hidayat, Muhamad Arif Hikmah Nur Rohim, Febrian M. Al Haris Manfaati Nur, Indah SALMAA Septia, Siti Fajar Yunanita, Novia