About the Journal

ONLINE ISSN : 2615-1367

PRINT ISSN : 2086-4132

Jurnal Aplikasi Statistika & Komputasi Statistik (JASKS) is an official publication of Politeknik Statistika STIS. JASKS is dedicated to publishing original research in applied statistics and statistical computing. This journal was first published in 2009. The publication schedule is two times a year, in June and December.



Original journal title Jurnal Aplikasi Statistika & Komputasi Statistik
English journal title Journal of Applied Statistics & Statistical Computing
Short Title JASKS
Country Indonesia
Subject Official statistics, Statistical methodology, Applied statistics in economics, social and population studies, Data science, Statistical Computing
Language English
ISSN 2615-1367 (online), 2086-4132 (print)
Frequency 2 issues per year (June and December)
DOI Prefix 10.34123/ Crossref
Accreditation SINTA 4, Decree Number: 0547/E5/DT.05.00/2024, 15th May 2024
Editor-in-Chief Setia Pramana [Sinta] [Scopus] [Google Scholar]
Publisher Politeknik Statistika STIS
Citation Analysis Garuda | Google Scholar

The journal consists of two refereed sections, Applied Statistics and Statistical Computing, that are divided into the following subject areas that are related to statistics applications and their computation:

  • Official statistics – Manuscripts dealing with survey design, questionnaire design and evaluation, measurement error, estimation and inference using frequentist or Bayesian, data collection, analytical uses of data, imputation, quality aspects of official statistics production, total survey error, systems and architectures for statistics production, evaluation and identification of statistical needs, small area estimation, and other subject related to official statistics.
  • Statistical Methodology – Manuscripts dealing with new and innovative data analysis techniques and methodologies include, but are not limited to: bootstrapping, classification techniques, design of experiments, parametric and nonparametric methods, statistical genetics, outlier detection, cross-validation, functional data, fuzzy statistical analysis, mixture models, model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, and robust procedures.
  • Applied Statistics in Economics, Social and Population Studies – Manuscript dealing with econometrics, demography, spatial analysis, time series analysis, longitudinal analysis, multilevel analysis, spatio-temporal analysis, and other subjects related to Applied Statistics in Economics, Social, and Population Studies.
  • Data Science – Manuscript dealing with big data, data mining, data science, data engineering, data visualization, machine learning, and data exploration.
  • Statistical Computing – Manuscripts dealing with the use of computing in statistical methodology (e.g., statistical databases, statistical information systems, Bayesian computation, computer-intensive inferential methods, numerical and optimization methods, parallel computing), and the development, evaluation, and validation of statistical software and algorithms.

Jurnal Aplikasi Statistika & Komputasi Statistik:

2024, JASKS was accredited Sinta 4 by Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi (Ministry of Education, Culture, Research and Technology). (Link SK)

2018, JASKS was accredited Sinta 2 by Kementerian Riset dan Teknologi/ Badan Riset dan Inovasi Nasional. (Link SK)

2016, Based on the LIPI No.747 / Akred / P2MI-LIPI / 04/2016, ASKS Journal was accredited by LIPI.

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Current Issue

Vol. 17 No. 1 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik
View Vol. 17 No. 1 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik

This issue features seven articles contributed by 27 authors affiliated with various institutions from Indonesia, Japan, China, and Singapore. The contributing institutions include IAIN Palangka Raya, Universitas Palangka Raya, Politeknik Statistika STIS, BPS-Statistics from various regional offices, the National Team for the Acceleration of Poverty Reduction, Universitas Islam Jakarta, PKN STAN, and the Center for Industrial, Services, and Trade Research under the National Research and Innovation Agency (Indonesia), alongside international collaborators from the University of Tsukuba (Japan), Jiangsu University (China), and Nanyang Technological University (Singapore). The research presented spans a diverse range of topics, including survival support vector machine analysis on separated couples during the COVID-19 outbreak, LLM implementation in survey interviews, quantile regression with constrained B-splines for modeling schooling and household expenditure, binary and traditional partial least squares structural equation modeling for poverty dimensions and social protection, geospatial analysis on hotel occupancy rates, partial proportional odds model application for household food insecurity in Papua, and the estimation of gross regional domestic product per capita using machine learning and geospatial data.

Published: 2025-07-16

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