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International Journal of Management Science and Information Technology (IJMSIT)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : 27767388     EISSN : 27745694     DOI : https://doi.org/10.35870/ijmsit
Core Subject : Economy, Science,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance
The development of science related to good technology, information, and communication, both theoretically and empirically has proven to have a positive impact on various aspects of people lives. The development of the science of Information and Communication Technology provides many benefits to increase the effectiveness and efficiency in various activities in various fields of science.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Menejemen Teknologi dan Inovasi
Articles 692 Documents
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The Effects of Price Perception and Product Quality on Repurchase Intention: The Mediating Role of Customer Satisfaction Among Consumers of Make Over Lipstick in Cimahi City Wan Maharani Alista Sari; Leni Evangalista Marliani
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8041

Abstract

This study aims to analyze the influence of price perception and product quality on repurchase intention, with consumer satisfaction as a mediating variable among Make Over lipstick consumers in Cimahi City. A quantitative approach was employed, utilizing an explanatory research design and survey method. The sample consisted of 134 female consumers who had purchased and used Make Over lipstick, selected through convenience sampling. Data were collected using a five-point Likert scale questionnaire and analyzed with descriptive analysis, multiple linear regression, path analysis, and the Sobel test, assisted by SPSS version 25. The results indicate that price perception does not have a significant effect on consumer satisfaction, whereas product quality has a positive and significant effect on consumer satisfaction. Perceived price, product quality, and consumer satisfaction each have a positive and significant effect on repurchase intention, with perceived price exerting the most dominant direct influence. Mediation analysis indicates that consumer satisfaction does not mediate the effect of perceived price on repurchase intention, but does mediate the effect of product quality on repurchase intention. These findings suggest that appropriate price management and product quality improvement are necessary to enhance consumer satisfaction and repurchase intention for Make Over lipstick.
Multi-Platform Sentiment Analysis of Diabetes Mellitus on X and TikTok Using K-Nearest Neighbor, Chi-Square Selection, and Oversampling Asti Devi Mutiara Khoirun Nisa; Noor Latifah; R. Rhoedy Setiawan
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8061

Abstract

Diabetes mellitus is a chronic health condition that is widely discussed by the public on social media, generating a large volume of opinions that are difficult to interpret manually. This study analyzes public sentiment toward Diabetes mellitus using data collected from X (Twitter) and TikTok. Text data were preprocessed (cleaning, slang normalization, stopword removal, and stemming) and duplicate entries were removed. Sentiment labels were generated automatically through a rule-based lexicon across four categories (positive, negative, neutral, and irrelevant/discarded), and the reliability of this automatic labeling was verified through manual validation of a stratified sample of 200 data points, measured using Cohen's Kappa. Positive and negative data were then weighted using TF-IDF, reduced using Chi-Square feature selection, balanced using SMOTE, and classified using K-Nearest Neighbor (KNN). Model performance was evaluated using accuracy, precision, recall, and F1-score, and compared across four scenarios: baseline KNN, KNN with Chi-Square, KNN with SMOTE, and the combined KNN+Chi-Square+SMOTE model. The manual validation of 198 valid samples produced an agreement accuracy of 59.60% and a Cohen's Kappa of 0.459 (moderate agreement), indicating that the main source of disagreement lies at the boundary between the neutral and sentiment-bearing classes, while direct positive-negative misclassification was rare (4.5%). The combined model achieved an accuracy of 82.86%, with a macro-averaged precision of 82.95%, recall of 83.56%, and F1-score of 82.79%. Interestingly, Chi-Square feature selection alone yielded the highest accuracy among the four scenarios (85.10%), suggesting that feature selection contributed more to performance gains than class balancing in this dataset. These findings suggest that combining feature selection and oversampling techniques improves the reliability of multi-platform sentiment classification for health-related topics and can inform more effective public health communication strategies regarding diabetes.
Influence of Environmental Concern and Green Packaging Perception on Consumers' Willingness to Pay For FMCG: Green Skepticism as A Mediator Alfigo Adisari; Raden Johnny Hadi Raharjo
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8118

Abstract

As sustainability concerns grow, FMCG firms have increasingly turned to eco-friendly packaging as part of their green strategy. Yet a gap persists between consumers' pro-environmental attitudes and their actual purchase behavior, since favorable attitudes toward the environment do not always translate into a premium price consumers are willing to pay. Building on this gap, this study investigates how environmental concern and green packaging perception shape FMCG consumers' willingness to pay, with green skepticism examined as a potential mediating pathway. A total of 176 FMCG consumers in Indonesia were recruited through a purposive-sampling procedure to serve as the study's respondents. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The results show that EC and GP directly and positively predict WTP, whereas the indirect pathways through GS were not statistically supported. Notably, GP was found to reduce GS the reverse of what was hypothesized and GS itself showed no significant bearing on WTP. These findings indicate that in the FMCG context, consumers translate environmental concern and green packaging perception directly into willingness to pay, without a meaningful skeptical evaluation process. This study contributes theoretically by identifying the boundary conditions of green skepticism as a mediating mechanism in low-involvement product categories, and offers practical implications for FMCG companies in designing sustainability communication that is directly value-oriented for consumers.
Enhancing Employee Performance in The Public Sector: The Role of Human Resource Competence and Organizational Communication with Evidence from Selayar Islands Regency Muh. Alim; Muhammad Rusydi; Muchriady Muchran
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8127

Abstract

This study aims to examine the influence of technical guidance, human resource (HR) competence, and organizational communication on employee performance at the Secretariat of the Regional House of Representatives (DPRD) of the Selayar Islands Regency using a quantitative survey approach with 80 respondents; data were collected through questionnaires and analyzed using multiple linear regression with prior validity, reliability, and classical assumption tests to ensure model accuracy. The findings reveal that HR competence and organizational communication have a positive and significant effect on employee performance, while technical guidance does not show a significant influence; moreover, organizational communication is identified as the most dominant variable. The model demonstrates strong explanatory power with an R² value of 0.871, indicating that 87.1% of performance variation is explained by the independent variables. These results emphasize the critical role of effective communication and competent human resources in improving organizational performance, while highlighting the need to redesign training programs to better align with job-specific demands in the public sector.
Under-Five Children's Nutritional Status Prediction Using Naïve Bayes and Decision Tree Based on Anthropometric Data and Mother–Child Class Participation Tsirwatun Nisail Khasanah; Fajar Nugraha; Yudie Irawan
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8128

Abstract

Nutritional status is an important indicator of the health and development of children under five, making early identification essential for supporting appropriate nutritional interventions. This study aimed to develop and compare the performance of the Naïve Bayes and Decision Tree algorithms in classifying the nutritional status of children under five based on anthropometric measurements and participation in the mother and Children Under Five Class program in Mlonggo District, Indonesia. A quantitative approach was applied using the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The initial dataset contained 4,588 records, of which 4,563 valid records remained after the preprocessing stage. Model performance was evaluated using accuracy, precision, recall, F1-score, confusion matrix, ROC curve, and McNemar’s test. The results showed that the Decision Tree algorithm achieved a higher cross-validation accuracy of 90.90% compared with 87.59% for Naïve Bayes. The testing results also demonstrated that Decision Tree consistently outperformed Naïve Bayes across the evaluation metrics. Therefore, Decision Tree was selected as the most suitable model for nutritional status classification. The model was subsequently implemented in a web-based application supporting individual and batch prediction, along with the presentation of prediction results and recommended health interventions. The system can support healthcare workers in conducting nutritional status assessments more efficiently and objectively.
Decision Support System for Selecting the Best Smartphone Using the Multi Attribute Utility Theory (MAUT) Method at Sinar Mas Selluler Kudus Arina Fawaida; Noor Latifah; Yudie Irawan
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8145

Abstract

The increasing variety of smartphone products with different specifications and prices makes the selection process more difficult for customers and often results in subjective recommendations from sales personnel. This study aims to develop a web-based Decision Support System (DSS) for smartphone selection at Sinar Mas Selluler Kudus using the Multi Attribute Utility Theory (MAUT) method. The system evaluates smartphone alternatives based on five criteria: Random Access Memory (RAM), Internal Storage, Screen Size, Battery Capacity, and Price. The research employed the System Development Life Cycle (SDLC) approach, including planning, analysis, design, implementation, and testing. The MAUT method was applied through criteria weighting, utility normalization, preference value calculation, and ranking to generate objective recommendations. The developed system was functionally validated using Black Box Testing to ensure that all system features operated according to the specified functional requirements. The developed system successfully automated the evaluation process, reduced subjective decision-making, and improved the efficiency of smartphone selection. The calculation results showed that Huawei (A3) achieved the highest preference value of 0.7215, indicating that it is the most suitable smartphone alternative according to the predefined criteria and weights. The implementation results demonstrate that the proposed system can assist sales personnel in providing objective recommendations while helping customers compare smartphone alternatives more efficiently based on their preferences and budget constraints. Therefore, the proposed system provides accurate, transparent, and consistent recommendations to support customers and sales personnel in making better purchasing decisions.
Structural Change Detection and Forecasting of Indonesia's Tourism-Related Output Using PELT and SARIMA Intervention Models Haves Qausar; Zata Hasyyati
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8180

Abstract

Quarterly tourism-related output is seasonal and highly vulnerable to structural disruptions, so models fitted to stable historical patterns may fail after shocks. This study detects changepoints and compares forecasting models for Indonesia's real GDP in Accommodation and Food Service Activities, used as a proxy for tourism-related economic output. The dataset comprised 50 quarterly observations at constant 2010 prices from 2013Q1 to 2025Q2. PELT was applied to detrended, seasonally adjusted log-training residuals. Ordinary SARIMA, SARIMA models with pulse and step interventions, six exponential-smoothing specifications, and a seasonal-naive benchmark were screened using training AICc, 16 rolling one-step validation origins, and an untouched ten-quarter fixed test. PELT identified 2017Q2, 2020Q2, and 2022Q1 as changepoints, with 2020Q2 remaining the most robust under stronger penalties. SES achieved the smallest rolling-validation RMSE (6,283.9), while the pulse-plus-temporary-step SARIMA intervention was best within its family (RMSE 6,917.4). On the fixed 2023Q1-2025Q2 test, SARIMA (0,1,1) × (0,0,0)₄ performed best overall, with MAE of Rp5,301.9 billion, RMSE of Rp6,131.6 billion, sMAPE of 5.23%, and MASE of 1.016. For the selected baseline SARIMA, residual autocorrelation and ARCH effects were not significant; the intervention model, however, retained significant residual autocorrelation. Residuals were non-normal across the retained models, and the baseline SARIMA underpredicted the later recovery. PELT provided structural diagnosis, but explicit intervention effects did not guarantee superior holdout forecasts. Parsimonious SARIMA provides the most defensible baseline, supplemented by changepoint monitoring and scenario-based intervention analysis.
The Influence of Financial Literacy and Digital Wallet Usage on Financial Behavior Among Students: An Empirical Study of Students in South Jakarta Revaldo Revaldo; Mukti Soma
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8186

Abstract

This study evaluates the influence of financial literacy and the use of e-wallets on the financial behavior of students in South Jakarta, focusing on both individual effects and the interaction between these factors. A quantitative approach was employed within an explanatory-causal framework, with primary data collected through a 1-4 Likert scale questionnaire distributed to 400 students residing or studying in the area, selected via purposive sampling. The analysis included instrument quality assessment, descriptive statistics, classical assumption testing, multiple linear regression, as well as t-tests and F-tests. Findings indicate that financial literacy does not exert a significant influence on students' financial behavior, with a significance value of 0.178, exceeding the 0.05 threshold. In contrast, e-wallet usage demonstrates a notable positive impact, evidenced by a significance value of 0.000, which is below 0.05, along with a positive regression coefficient. When assessed together, both factors significantly affect financial behavior, as shown by an F value of 902.144 and a significance level of 0.000. The Adjusted R Square value of 0.819 suggests that 81.9% of the variance in students' financial behavior can be attributed to financial literacy and e-wallet usage, while the remaining 18.1% is influenced by other variables not examined in this study. These results emphasize the greater role of e-wallet usage in shaping financial practices among students compared to financial literacy. Therefore, it is recommended that digital financial literacy initiatives be enhanced, focusing on the development of record-keeping skills, expenditure management, and responsible use of digital transaction tools.
Skintific Purchase Decisions Among TikTok Users in Purwokerto: The Role of Influencer Marketing, e-WOM, Brand Image, and Product Quality M Rizki Bahtiar; Totok Haryanto Totok Haryanto; Erny Rachmawati; Hengky Widhiandono
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8288

Abstract

This study aims to examine the influence of consumer purchasing decisions of Skintific skincare products in Purwokerto with the variables of influencer marketing, electronic word of mouth, brand image, and product quality. Quantitative data collection using Google Forms with a Likert Scale of 1-5. The research population is residents of Purwokerto who have purchased Skintific skincare products and are actively using TikTok. Sampling used a non-probability method with a purposive sampling technique. The Lemeshow method was used to determine the minimum number of samples and and the final sample consisted of 130 respondents. This study uses the Construct Validity and Reliability Test, Discriminant Validity of Fornell-Larcker and HTMT criteria, Inner VIF, Model Fit, R-Square and Hypothesis Test. The data were analyzed using the SmartPLS 3. The results of this study showed that all variables were positively related to purchase decisions, influencer marketing (β=.334), electronic word of mouth (β=.276), brand image (β=.357), and product quality (β=.306), all p<.001; R²=.643. In this study, all variables can influence purchasing decisions with the findings of brand image as the variable that has the highest influence. The findings indicate the importance of brand image consistency in Skintific communication on TikTok. This study contributes to the digital marketing literature by providing empirical evidence on the effects of influencer marketing, e-WOM, brand image, and product quality on purchase decisions. However, this study is limited to TikTok users in Purwokerto.
A Web-Based Gold Price Prediction Model Using Geopolitical Sentiment from Social Media and Gated Recurrent Unit (GRU) Narendra Saputra; Anteng Widodo; Zainur Romadhon
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8297

Abstract

Gold is widely recognized as a safe-haven asset whose price is sensitive to economic and geopolitical uncertainty. This study develops a web-based international gold price prediction system using the Gated Recurrent Unit (GRU) algorithm and evaluates the contribution of geopolitical sentiment from the X social media platform. The study uses historical XAUUSD data and English-language posts related to the Iran–United States–Israel conflict. Text data were processed through cleaning, case folding, tokenization, stopword removal, lemmatization, TF-IDF transformation, and sentiment analysis using VADER. The resulting daily sentiment scores were integrated with historical gold price features and used as an additional input to the GRU model. Two experimental scenarios were evaluated: GRU without sentiment and GRU with sentiment. The results show that the GRU model without sentiment achieved an MAE of 55.07, RMSE of 69.81, MAPE of 1.17%, and R² of 0.9629, while the model with sentiment achieved an MAE of 80.87, RMSE of 92.93, MAPE of 1.72%, and R² of 0.9342. These findings indicate that incorporating daily aggregated social media sentiment did not improve prediction performance for the dataset used. The developed Flask-based web application provides prediction, sentiment analysis, visualization, and model evaluation features, demonstrating the practical implementation of the proposed approach.

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