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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Mathematics and Scientific Computing With Applications
Faigle, Ulrich
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Mathematics

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Criteria for Publishing in Reputable International Journals: An Analytical Hierarchy Process Decision Model Husein, Ismail; Zein, Achyar; Faigle, Ulrich
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.30903

Abstract

The problem faced by researchers, in this case lecturers at universities, after carrying out research and making research reports is deciding where to publish the results of their research. Analytic Hierarchy Process is an effective method for ranking alternative journals. This helps ensure that their research is published in a reputable journal that will reach the appropriate audience and have a positive impact on their career. The data collection method in this research was first sourced from books, the internet, and previously a study of articles and journals; secondly, create a checklist of criteria and sub-criteria from 20 (twenty) articles, namely 4 articles from Elsevier, 4 articles from Springer Nature, 4 articles from Taylor Francis, 4 articles from Wiley-Blackwell, and 4 articles from Sage. Article selection was carried out randomly. The results of distributing questionnaires were analyzed using the Analytic Hierarchy Process Online System designed by Klaus D. Goepel. The main aim of this study was to determine the appropriate weighting of several criteria that explain why previously published manuscripts are submitted to their intended publication. The criteria for accepting article manuscripts in reputable international journals using the Analytical Hierarchy Process model (standard Analytic Hierarchy Process linear scale methods) is that the first priority is the "novelty" criterion with a weight of 0.502. The second priority is the "scientific" criterion with a weight of 0.201. Furthermore, the third and fourth priorities are "manuscript" and "content" respectively with weights of 0.142 and 0.078. Meanwhile, the last priority is "Interesting" with a weight of 0.076.
IMPLEMENTATION OF PRINCIPAL COMPONENT ANALYSIS (PCA) IN DIMENSION REDUCTION BASED ON INDONESIAN HEALTH DATA Rangkuti, Siti Rafiah; Fadhillah, Nurul; Sari, Rita Novita; Faigle, Ulrich
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i2.1313

Abstract

Indonesian health data for 2024 has multidimensional characteristics with a large number of interconnected variables, leading to high complexity in the analysis and visualization process. This complexity poses a challenge in generating information that is easy to understand and can support data-driven decision-making. This research aims to implement the Principal Component Analysis (PCA) method as a technique for dimension reduction and visualization of Indonesian health data. The research method used is a quantitative approach with descriptive-exploratory secondary data analysis. The research stages include data pre-processing, PCA implementation, principal component determination, variable contribution analysis, and data visualization using scatter plots and biplots. The research results show that PCA is able to significantly reduce the number of variables while still retaining most of the main information contained in the data. Principal component analysis-based visualization produces clearer and more easily interpretable patterns and structures in health data. Thus, PCA has proven effective in simplifying the complexity of national health data and supporting the presentation of more informative and actionable information for decision-making in the health sector.
Co-Authors Achyar Zein, Achyar Fadhillah, Nurul Ismail Husein, Ismail Rangkuti, Siti Rafiah Sari, Rita Novita