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International Journal of Applied Mathematics and Computing.
Published by Asosiasi Riset Ilmu Matematika dan Sains Indonesia
ISSN : 30481988     EISSN : 3047146X     DOI : 10.62951
Core Subject : Science, Education,
Computer Science & IT Mathematics
This Journal accepts manuscripts based on empirical research, both quantitative and qualitative. This journal is a peer-reviewed and open access journal of Mathematics and Computing
Arjuna Subject : Matematika - Matematika Komputer
Articles 57 Documents
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A Systematic Literature Review The Impact of ERP and DSS on Organizational Performance: The Mediating Role of Decision-Making Quality Julianto, Dimas Gibran Julianto; Hamdani, Hamdani; Achmad, Gusti Noorlitaria; Ramadhani, Herry; Arifin, Zainal
International Journal of Applied Mathematics and Computing Vol. 3 No. 3 (2026): July: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i3.334

Abstract

The adoption of Enterprise Resource Planning (ERP) and Decision Support Systems (DSS) is increasingly widespread to improve organizational performance, yet the underlying mechanisms remain fragmented. This study aims to conduct a Systematic Literature Review (SLR) to identify the impact of ERP and DSS on organizational performance, highlighting the mediating role of decision-making quality. A systematic search was performed on four sources (Scopus, Web of Science, Google Scholar, and ProQuest) for the 2021–2025 period. From 217 initial records, 34 empirical studies were analyzed using thematic synthesis. The results show that both ERP and DSS positively affect organizational performance, directly and through the enhancement of decision-making quality. Decision quality encompassing speed, accuracy, and information completeness – acts as a significant mediator. The mediation effect is determined by factors including top management support, organizational culture, data quality, and user competency. The findings emphasize that IT investments only yield superior performance when accompanied by strengthened decision-making capabilities
Utilization of Management Information Systems in Strategic Decision Making in the Human Resources Sector Dharmawan, Ade Putra; Hamdani, Hamdani; Achmad, Gusti Noorlitaria
International Journal of Applied Mathematics and Computing Vol. 3 No. 3 (2026): July: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i3.336

Abstract

This study employs a systematic literature review and bibliometric analysis to examine trends, patterns, and conceptual developments in Human Resource Management Information Systems (HR-MIS). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was applied to ensure the literature review process was conducted systematically, transparently, and reproducibly. Selected articles met key inclusion criteria: published before April 16, 2026, written in English, and specifically discussing HR Management Information Systems. The Scopus database, an abstract and citation database of peer-reviewed literature, served as the primary data source for this literature review. A visual mapping analysis was performed using VOSviewer, software for constructing and visualizing bibliometric networks, to map citation networks, collaborations, and keyword co-occurrences, uncovering the intellectual structure and evolutionary trajectory of the human resource field. The findings indicate that the use of HR-MIS is strongly correlated with improved efficiency in strategic decision-making and resource allocation. The literature is divided into two primary clusters: strategic information governance and the operational impact on organizational behavior. By integrating bibliometric and systematic methodologies, this study successfully provides a comprehensive identification of key contributors, research trends, benefits, challenges, and future research agendas.
The Role of Human Resource Information Systems (HRIS) in Improving Employee Performance: A Systematic Literature Review AS, Falga Bara Prima Abadi; Hamdani, Hamdani; Lestari, Dirga
International Journal of Applied Mathematics and Computing Vol. 3 No. 3 (2026): July: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i3.337

Abstract

As modern enterprises embrace digital transformation, Human Resource Information Systems (HRIS) have become essential for managing organizational talent. This systematic literature review synthesizes empirical evidence from 30 academic papers and three foundational texts published between 2021 and 2026, explicitly examining how digital HR infrastructures elevate individual workforce achievements. Utilizing the PRISMA protocol, the study extracts data across multiple global databases to map the direct impacts and underlying mechanisms linking system utilization to employee productivity. Comprehensive analysis confirms that digital HR platforms significantly boost staff effectiveness by optimizing administrative routines, elevating data precision, and upgrading evaluation protocols. Crucially, these technological advantages translate into individual success primarily through intermediate channels, including workplace contentment, active engagement, and superior strategic judgments. Furthermore, organizations only realize these benefits when supported by an accommodating corporate culture and flawless technical integration. By assembling previously disconnected findings, this review bridges the gap between technological capabilities and behavioral outcomes, equipping executives with evidence backed strategies for technological governance while outlining a rigorous agenda for future multilevel and longitudinal research.
A Comparison of SVM and ELM Algorithms Based on SMOTE for Anemia Classification Using Hematology Data Dharmaesa, Dio; Hamdani, Hamdani; Suyatno, Addy
International Journal of Applied Mathematics and Computing Vol. 3 No. 3 (2026): July: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i3.376

Abstract

Anemia remains a significant global health concern, and its diagnosis through manual interpretation of Complete Blood Count (CBC) results is susceptible to bias and misinterpretation. Machine learning techniques offer a promising solution for identifying complex patterns in medical data; however, their performance is often hindered by class imbalance issues commonly found in healthcare datasets. Therefore, this study aims to evaluate and compare the classification performance of Support Vector Machine (SVM) and Extreme Learning Machine (ELM) algorithms enhanced with the Synthetic Minority Over-sampling Technique (SMOTE) for anemia detection. The proposed approach employs SVM with an RBF kernel and ELM with a sigmoid activation function, both optimized through a 5-Fold Cross-Validation inner loop to determine the best regularization parameter C and the optimal number of hidden neurons, respectively. SMOTE is applied exclusively to the training data to address class imbalance without data leakage. To ensure robust and unbiased performance estimation, experiments were conducted over 10 independent runs using stratified 80:20 train-test splits on a secondary CBC dataset consisting of 200 patient records. Experimental results show that the SMOTE-based SVM model achieved a mean accuracy of 87.75% ± 0.75%, precision of 98.08% ± 1.92%, recall of 84.83% ± 1.69%, and F1-score of 90.94% ± 0.57%, with an average computation time of 1.430 seconds per run. In comparison, the SMOTE-based ELM model attained a mean accuracy of 85.25% ± 5.86%, precision of 95.81% ± 3.11%, recall of 83.45% ± 8.56%, and F1-score of 88.91% ± 4.89%, while requiring only 0.460 seconds per run. The findings suggest that SVM delivers more stable performance with higher precision, making it effective in minimizing false positive predictions. In contrast, ELM offers greater computational efficiency, making it suitable when rapid processing is prioritized over predictive accuracy.
Supporting Junior Secondary Students’ Geometric Visualisation Through Augmented Reality and a STAR Scaffold: An Exploratory Pre–Post Pilot Study Dinda Ayu Putri; Bulan Ainayya Fathiyyaturahma; Liffia Salwa Nabila
International Journal of Applied Mathematics and Computing Vol. 3 No. 2 (2026): April: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i2.385

Abstract

Geometric visualisation is a fundamental yet challenging competency in mathematics education, particularly for junior secondary school students who struggle to interpret three-dimensional (3D) spatial structures using conventional two-dimensional instructional media. This study examines the effectiveness of Augmented Reality (AR) integrated with the STAR instructional strategy (Situation, Task, Action, Result) in enhancing students’ geometric visualisation skills. A quantitative pilot study employing a one-group pretest–posttest design was conducted with 9 eighth-grade students at SMP Muhammadiyah 3 Sukolilo, Indonesia, selected through purposive sampling. Data were collected using validated geometry visualisation tests administered before and after the intervention. The data were analysed using normalised gain (N-Gain) and paired sample t-test. The results indicate a significant improvement in students’ performance, with the mean score increasing from 20.00 (SD not reported due to small sample size) on the pretest to 88.89 on the posttest. The normalised gain score (g = 0.67) indicates a moderate-to-high improvement, while inferential analysis shows statistically significant differences (p < 0.05). The findings suggest that AR enhances spatial cognition by enabling interactive manipulation of 3D geometric objects, while the STAR strategy provides structured cognitive scaffolding that guides students through contextual problem understanding, task execution, and reflective learning. The novelty of this study lies in integrating STAR as a structured pedagogical scaffold within an AR-based spatial learning environment for geometry instruction in a low-resource classroom context. This study contributes to the growing body of evidence supporting immersive technologies in mathematics education, particularly for improving spatial reasoning in early secondary learners.
Analysis of Students’ Behavior in Solving Mathematical Literacy Problems at the Junior High School Level Dwita Elfri Mayani; Heri Retnawati
International Journal of Applied Mathematics and Computing Vol. 3 No. 3 (2026): July: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i3.403

Abstract

Background: Mathematical literacy is a key competency in 21st-century learning; however, Indonesian students’ achievement remains low. Previous research has largely focused on cognitive aspects, while behavioral dimensions such as self-regulation, the use of mathematical tools, and self-confidence have not received adequate attention, even though these aspects play a crucial role in successful problem-solving. Methods: This study employed a qualitative approach using grounded theory. Participants consisted of 18 eighth-grade students from three public junior high schools in Yogyakarta, selected through stratified random sampling. Data were collected through a mathematics literacy test, semi-structured interviews, and observations, and analyzed using constant comparison until data saturation was reached. Results: The analysis revealed a new behavioral category, termed “semi-superior,” situated between regular and superior behaviors. Self-regulation, the use of mathematical tools, and self-confidence interacted dynamically. Students with stronger self-regulation and higher self-confidence demonstrated more strategic and reflective approaches. A clear alignment was found between mathematical literacy proficiency and behavioral orientation. Implication: Mathematics instruction must integrate cognitive, metacognitive, psychomotor, and affective competencies. Future research should examine the socio-economic and technological factors that influence students’ mathematical literacy behaviors.
Development of Learning Media by Applying Scratch Assisted Computational Thinking Oriented to Self-Regulated Learning and Students' Mathematical Problem-Solving Skills Anis Widiyanti; Dhoriva Urwatul Wutsqa
International Journal of Applied Mathematics and Computing Vol. 3 No. 3 (2026): July: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v3i3.406

Abstract

This study developed and evaluated interactive Scratch-based learning media integrating computational thinking to support students’ self-regulated learning and mathematical problem-solving ability. The research used a Research and Development approach by adapting the ADDIE model: Analysis, Design, Development, Implementation, and Evaluation. Participants were 11 eleventh-grade students and one mathematics teacher at SMK PIRI 1 Yogyakarta. Data were collected through expert validation sheets, teacher and student response questionnaires, learning implementation observations, a mathematical problem-solving test, and a self-regulated learning questionnaire. Qualitative and quantitative analyses included multivariate and univariate normality tests, Hotelling’s T² test, and one-sample t-tests using RStudio. The results indicated that the developed media met validity and practicality criteria. Experts declared the media valid, while the teacher rated it very practical, students rated it practical, and implementation exceeded 80%. The media was effective in improving self-regulated learning, with a significance value of 0.006371, a mean score of 3.8, and 74.99% mastery. However, the proportion test did not confirm that mastery exceeded the predetermined criterion. Mathematical problem-solving ability also failed to meet the minimum effectiveness criterion, with a significance value of 0.1792, a mean score of 77.04, and 64% mastery. Therefore, the media requires refinement to strengthen students’ mathematical problem-solving outcomes consistently.

Page 6 of 6 | Total Record : 57

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