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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika TIERS Information Technology Journal
Chung, Meng-Yun
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Computer Science & IT

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KNN Approach to Evaluating the Feasibility of Using Scientific Publications as Final Projects Abror, Dzulchan; Nasyuha, Asyahri Hadi; Chung, Meng-Yun; Perangin-angin, Moch. Iswan
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14370

Abstract

This study aims to explore the feasibility of using scientific publications as a substitute for traditional final assignments in higher education by applying the K-Nearest Neighbors (K-NN) algorithm. Traditional final assessments, such as theses, are widely used in evaluating students, but with the increasing availability of peer-reviewed scientific publications, there is potential to use them as a more dynamic and relevant assessment tool. This study uses a dataset containing scientific publications and theses, with features such as research quality, relevance, methodology, and clarity. This study applies the K-NN algorithm to classify these materials and determine whether scientific publications can serve as an effective substitute. The results show that the K-NN algorithm, using k=4, achieved 95% accuracy, successfully distinguishing between scientific publications and theses. However, some misclassifications occurred, indicating areas for improvement, such as incorporating additional features such as citation counts or peer-review scores. These findings suggest that scientific publications, if properly classified, can indeed replace traditional final assignments, encouraging critical thinking and engagement with current research. Future research should refine the feature set and explore other machine learning models to improve accuracy. The practical implications of this research are the potential to develop more innovative and relevant approaches to assessment in higher education, which are more aligned with modern educational practice.
A Comparative Study of Three Decision Support Methods: Proving Consistency in Decision-Making with Identical Inputs Nasyuha, Asyahri Hadi; Dhuhita, Windha Mega Pradnya; Harmayani, Harmayani; Marwanta, Y. Yohakim; Chung, Meng-Yun; Ikhwan, Ali
TIERS Information Technology Journal Vol. 6 No. 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v6i1.6157

Abstract

Decision-making in complex environments often requires evaluating multiple alternatives against various criteria, which can sometimes result in inconsistent outcomes when different decision support methods are employed. Such inconsistencies pose significant challenges for decision-makers in determining the most reliable methodology. To address this gap, the present study examines whether three widely adopted decision support methods, Simple Additive Weighting (SAW), Simple Multi-Attribute Rating Technique (SMART), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), produce consistent results when applied to identical input values, criteria, and alternatives. The primary aim is to explicitly assess the consistency of decision-making outcomes across these methods under controlled conditions. The evaluation was conducted using a set of alternatives, with A1 consistently emerging as the top choice. Specifically, the SAW method produced a final score of 0.8998 for A5, the SMART method assigned a value of 0, and the TOPSIS method yielded a closeness coefficient of 0.826 for the same alternative. The unique contribution of this study lies in its systematic, side-by-side comparison of SAW, SMART, and TOPSIS using precisely the same dataset, an approach seldom addressed in prior research. By empirically demonstrating that these methods generate identical rankings under strictly controlled scenarios, this research provides new evidence supporting the methodological robustness and practical interchangeability of these widely used decision support techniques. The findings underscore the reliability of these methods in facilitating objective decision-making and offer valuable guidance for researchers and practitioners in selecting the most suitable DSS method without concern for inconsistent results.
Comparison of WSM and Weight Product Methods with WSM-Score and Vector Approaches Nasyuha, Asyahri Hadi; Tujantri , Harkam; Veza, Okta; Nurarif, Saiful; Chung, Meng-Yun
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14817

Abstract

Fertilizers are essential in modern agriculture as they supply vital nutrients to plants, enhancing growth and yield. However, selecting the most appropriate fertilizer involves multiple criteria and a diverse range of available options. This study conducts a comparative analysis of two Multi-Criteria Decision-Making (MCDM) methods: the Weighted Sum Model (WSM) and the Weight Product (WP) method, supplemented by WSM-Score and vector-based approaches. The evaluation is based on four criteria price, quality, ease of availability, and fertilizer form across seven alternatives: Urea, Compost, TSP, KCL, Gandasil, NPK, and ZA. Using normalized weights from expert judgment, both methods were used to rank the alternatives. A key contribution of this study is the integration of WSM-Score and vector approaches, which enhance traditional MCDM by improving score comparability (WSM-Score) and enabling geometric interpretation of alternative positioning (vector). Results show that Compost (A2) ranks highest across all methods, indicating convergence despite differences in computational logic. WSM offers ease of interpretation, while WP better accounts for proportional differences but is more sensitive to low-performing criteria. The findings suggest that method selection should be context-dependent. Although the ranking results are consistent, the absence of empirical validation through expert comparison or field data limits the generalizability of the conclusions. Further research should include such validation to strengthen the reliability of MCDM-based decision support systems in agricultural applications.
Co-Authors Abror, Dzulchan Ali Ikhwan Asyahri Hadi Nasyuha Marwanta, Y. Yohakim Nurarif, Saiful Perangin-angin, Moch. Iswan Tujantri , Harkam Veza, Okta WINDHA MEGA PRADNYA DHUHITA