About Journal

Focus and Scope

Eksakta: Journal of Sciences and Data Analysis covers some topics in mathematics, statistics and natural science including

Mathematics theory and applications
Statistics in industry, statistical modelling and other applications
Physic
Chemistry: organic, inorganic, physical chemistry, analytical chemistry, biochemistry, environmental chemistry
Pharmacy: analysis, synthesis and analysis of drug, biomolecules, active compouns isolation, purification, modification and their applications
Analytical method fabrication, development and validation
other collaboration and related topics in mathematics and natural sciences

Peer Review Process

Submitted articles will be first review by the editor for the topic and writing style according to the guidelines. The articles will then blind-review by editor selected reviewers according to the topic specialist.

Open Access Policy

EKSAKTA provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. It means that all articles are available on the internet to all users immediately upon publication. Non-commercial use and distribution in any medium are permitted.

Benefits of open access for authors are :

Free access for all users worldwide
Authors retain copyright to their work
Increased visibility and readership
No spatial constraints

There is no submission fee.

Journal History

The journal was first published in 2010 as Eksakta: Jurnal Ilmu-Ilmu MIPA (e-ISSN 2503-2364 and p-ISSN 1411-1047),

which then changed to EKSKATA: Journal of Science and Data Analysis since February 2020 (e-ISSN 2720-9326 and p-ISSN 2716-0459)

Journal Publication

The journal publishes 2 issues in one volume each year. Starting publication in 2024, the journal will be published in April and October.

Purwaningsih, Tuti, Program Studi Statistika, Universitas Islam Indonesia, Indonesia

EKSAKTA: Journal of Sciences and Data Analysis VOLUME 15, ISSUE 1-2, 2015 - Research Articles
Penerapan Regresi Logistik Biner Terboboti Geografi dengan Pembobot Fixed Bi-Square (Geographically Weighted Binary Logistic Regression with Fixed Bi-Square Weight)
Abstract PDF