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Journal of Analytical Uncertainty
Published by Yayasan Winaya Inspirasi Nusantara
ISSN : 31246818     EISSN : 31246818     DOI : https://doi.org/10.63924/jau
Core Subject : Science, Education, Engineering,
Computer Science & IT Engineering Mathematics
The Journal of Analytical Uncertainty (JAU) is an international, peer-reviewed, multidisciplinary journal devoted to advancing theoretical, computational, and applied research applied research on randomness and uncertainty in decision-making. The journal provides a platform for researchers, academicians, and practitioners working in the diverse domains of mathematics, statistics, and fuzzy sciences to exchange innovative ideas and findings addressing the complexities of uncertain, imprecise, and vague information. The JAU aims to promote the integration of analytical modeling, statistical inference, and uncertainty quantification for enhanced decision-making across various fields including economics, finance, engineering, healthcare, environmental studies, and social sciences. The journal welcomes contributions that develop new methods, propose models, or present applications in which uncertainty plays a critical role in decision processes.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 5 Documents
 1 
Shortest Path Problem in Network with Quadripartitioned Neutrosophic Arc Length Broumi Said; Yuhao Su; M. Parimala; Yekini Shehu
Journal of Analytical Uncertainty Vol. 1 No. 1 (2025): JAU: December 2025
Publisher : Winaya Inspirasi Nusantara Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63924/jau.v1i1.262

Abstract

Many extensions and generalizations of neutrosophic sets have been introduced and studied in the literature. Quadripartitioned single valued neutrosophic set becomes an important tool in solving various types of decision making problems, medical diagnosis problems, clustering,... etc. The neutrosophic graph has still been a powerful tool for modeling and designing indeterminate networks. Quadripartitioned single valued neutrosophic graph is a generalization of single valued neutrosophic graph. In this chaptre, we formulate the shortest path (SP) problem in Quadripartitioned single valued neutrosophic environment. Here, the costs related to arcs are taken in the form of Quadripartitioned single valued neutrosophic numbers (QSVNNs). A numerical example also included illustrating our proposed method for finding the neutrosophic shortest path.
Super Rhotrix Driven Multi-criteria Decision Making R. Priya; Nivetha Martin; Florentine Smarandache
Journal of Analytical Uncertainty Vol. 1 No. 1 (2025): JAU: December 2025
Publisher : Winaya Inspirasi Nusantara Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63924/jau.v1i1.263

Abstract

This study introduces the theoretical conceptualization of Super Rhotrix and its applications in multi-criteria decision making. The properties, operations and classifications of Super Rhotrix are discoursed in this work. The geometrical interpretation of the structures of rhotrix and super rhotrix are described in the context of applications to decision-making. The rigidity and compatibility of super rhotrix is well -substantiated and demonstrated with the illustration of supplier selection problem. The merits and limitations of the proposed decision-making approach is also discussed.
A Variable-Indeterminacy Weighted Correlation Framework in Neutrosophic Statistics Prasanta Kumar Raut
Journal of Analytical Uncertainty Vol. 1 No. 1 (2025): JAU: December 2025
Publisher : Winaya Inspirasi Nusantara Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63924/jau.v1i1.264

Abstract

Correlation analysis under uncertain and imperfect information remains a fundamental challenge in statistical modeling. Although neutrosophic statistics provides a flexible framework for handling truth, falsity, and indeterminacy simultaneously, most existing neutrosophic correlation measures treat the indeterminacy component as uniform across observations. Such an assumption may oversimplify real data, where uncertainty often varies due to measurement errors, subjective assessments, or incomplete knowledge. In this paper, a weighted neutrosophic correlation framework with observation-dependent indeterminacy is developed. The proposed model allows each data point to possess its own indeterminacy level and incorporates weighting parameters to reflect the relative reliability or importance of observations. Based on these considerations, a new weighted neutrosophic correlation coefficient is formulated using neutrosophic means, variances, and covariance. Fundamental statistical properties of the proposed coefficient, including boundedness, symmetry, and invariance under linear transformations, are rigorously established. A detailed numerical illustration is provided to demonstrate the computational procedure and to show how variable indeterminacy and weighting influence the strength of association between variables. The proposed approach offers a more realistic and adaptable tool for analyzing relationships in uncertain environments and may serve as a useful foundation for further developments in neutrosophic data analysis and decision-making applications.
Multi-Criteria Decision Making for Smart City Implementation Using Fuzzy Soft Maut Method Adem Yolcu; Taha Yasin Öztürk
Journal of Analytical Uncertainty Vol. 1 No. 1 (2025): JAU: December 2025
Publisher : Winaya Inspirasi Nusantara Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63924/jau.v1i1.269

Abstract

Smart city development requires making choices based on multiple and competing criteria. Thus, in these kinds of environment, the opinions of experts are often given in terms of vague language rather than specific numbers. This paper investigates this challenge by developing a Fuzzy Soft Multi-Attribute Utility Theory (MAUT) system for assessing the readiness of metropolitan municipalities to implement a smart city. This is a hybrid method which integrates the parameter-based structured approach of soft sets with the ability to model uncertainty in fuzzy sets and usefulness aggregation rules of MAUT. Triangular fuzzy numbers are employed for the representation of an expert’s judgment. A procedure is followed in order to aggregate, normalize the assessments, and then combine them in an overall utility score. The model is developed to help decision-makers in creating a transparent and flexible method to address numerous criteria in uncertain situations in the context of urban and smart city planning.
Multiple-Attribute Decision-Making Based on AHP-TOPSIS for Gas Station Site Selection Problem Muhammad Nabil Maulana; Kikye Martiwi Sukiakhy; Rini Deviani; Sri Azizah Nazhifah; Husaini Husaini; Irvanizam Irvanizam
Journal of Analytical Uncertainty Vol. 1 No. 1 (2025): JAU: December 2025
Publisher : Winaya Inspirasi Nusantara Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63924/jau.v1i1.270

Abstract

The continuous growth of private vehicle usage in Indonesia has led to a significant increase in fuel demand, making the strategic placement of gas stations a critical issue for transportation infrastructure planning. However, inappropriate site selection may result in uneven service coverage, affecting increased operational costs and reduced accessibility for road users. Therefore, a systematic and objective decision-making approach is required to support gas station location planning. Motivated by this challenge, this study develops an integrated decision-support framework to evaluate and select strategic gas station sites based on multiple criteria. The framework combines the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The AHP method is employed in the first stage to determine the relative importance weights of the evaluation criteria based on expert judgments. In the second stage, the TOPSIS method is implemented to rank candidate locations and identify the alternative closest to the ideal solution. To validate the proposed framework, a case study involving multiple candidate locations is experimented with. Experimental results demonstrate that the proposed AHP–TOPSIS approach is a practical tool for selecting gas station site location, with location L3 identified as the most strategic site for gas station construction.

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