Jurnal Statistika Universitas Muhammadiyah Semarang

 

Journal Title: Jurnal Statistika Universitas Muhammadiyah Semarang
Print ISSN: 2338-3216
Online ISSN: 2528-1070
Publication schedule: 2 issues per year (May and November)
Editor-in-chief: Fatkhurokhman Fauzi, S.Si., M.Stat
Language: English
Publisher: Department of Statistics UNIMUS
   Universitas Muhammadiyah Semarang
Organized: Department of Statistics UNIMUS
   Universitas Muhammadiyah Semarang
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The main aim of the Jurnal Statistika [ISSN 2338-3216 (Print); 2528-1070 (Online)] is to publish refereed, well-written original research articles, and studies that describe the latest research and developments in the area of applied statistics and mathematics. This is a broad-based journal covering all branches of statistics, mathematics, and interdisciplinary applied Statistics. Jurnal Statistika is a peer-reviewed journal and published two times a year by Universitas Muhammadiyah Semarang.


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Announcements

 

Latest Journal Template

  
Jurnal Statistika Universitas Muhammadiyah Semarang starting volume 10 No. 2 of 2022 will change the template. Download the latest templates [here] or in the sidebar.  
Posted: 2022-09-01
 
More Announcements...

Vol 12, No 1 (2024): Jurnal Statistika Universitass Muhammadiyah Semarang (In progress)

Table of Contents

Articles

CLUSTERING DISTRICT/CITY IN WEST KALIMANTAN BASED ON FACTORS CAUSING STUNTING USING K-HARMONIC MEANS METHOD
Rahmania Andarini Hatti Imanni, Evy Sulistianingsih, Hendra Perdana
DOI : 10.26714/jsunimus.12.1.2024.%p
Abstract view : 301 times
PDF
1-9
Determining Sister City Regency/City Non-Sample Cost of Living Survey (SBH) and Clustering Analysis of Consumption Patterns in West Java using the Machine Learning Method
Raditya Novidianto, Erwin Tanur, Andrea Tri Rian Dani, Fachrian Bimantoro Putra
DOI : 10.26714/jsunimus.12.1.2024.%p
Abstract view : 174 times
PDF
10-23
FORECASTING THE OCCUPANCY RATE OF STAR HOTELS IN BALI USING THE XGBOOST AND SVR METHODS
Aviolla Terza Damaliana, Amri Muhaimin, Dwi Arman Prasetya
DOI : 10.26714/jsunimus.12.1.2024.24-33
Abstract view : 227 times
PDF
24-33
THE PERFORMANCE ANALYSIS OF THE BEST MACHINE LEARNING MODEL FOR SULFUR DIOXIDE IN DKI JAKARTA
Panji Kuswanaji
DOI : 10.26714/jsunimus.12.1.2024.34-47
Abstract view : 123 times
PDF
34-47