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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 345 Documents
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Application of the KNN Algorithm to Assess Customer Satisfaction at A2 Collection Sei Silau Timur Sitorus, Lutfi Anniswa; Hutahaean, Jeperson; Maulana, Cecep
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6813

Abstract

The development of information technology and data mining in recent years has changed the way retail businesses, including small and medium-scale fashion businesses, collect, analyze, and utilize customer data to improve services and marketing strategies. In addition, through the main discussion carried out in this study, it aims to be able to analyze the factors that influence the level of customer satisfaction at Amel Fashion Prapat Janji based on the attributes of product quality, price, comfort of use, and service. In addition, this study develops and applies the K-Nearest Neighbor (K-NN) algorithm to classify the level of customer satisfaction more objectively, measurably and data-based. And in addition, for the Research Method section used in this study, a qualitative approach was chosen because the focus of this study is to explore the meaning, perception, and direct experience of business actors in the marketing and distribution process. So based on that, this study shows the results that the application of the K-Nearest Neighbor (KNN) algorithm in the customer satisfaction classification system at A2 Collection Sei Silau Timur is able to provide an effective solution in managing and analyzing customer evaluation data. This website-based system has succeeded in changing the assessment process that was previously carried out manually to be more structured, systematic, and easily accessible. Based on the system's calculations, the resulting distance values, such as 2.354, categorized as "Satisfied" and 2.325, categorized as "Dissatisfied," indicate that the proximity of attribute values significantly influences the classification results. Although the difference in distance values is relatively small, the system is still able to determine the class based on the dominance of the nearest neighbor data.
The Impact of Safeguard Import Duty (BMTP) Policies and Macroeconomic Factors on Textile Import Volumes in Indonesia Jelantik, I Gusti Ayu Agung Istri Dinda Larasshanti; Putra P, Komang Widhya Sedana
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6900

Abstract

This study aims to analyse the effectiveness of the Safeguard Import Duty or Bea Masuk Tindakan Pengamanan (BMTP) in controlling textile import volumes in Indonesia. It is also examining the influence of macroeconomic variables, exchange rates and inflation. This study is motivated by the increasing pressure from imports on the domestic textile industry and the need to evaluate trade defence policies in the context of developing countries. In this regard, the analysis integrates trade defence policies with exchange rate and inflation dynamics in order to better illustrate how macroeconomic conditions influence the outcomes of trade policies. A quantitative approach is employed using panel data regression, combining cross-sectional data from 14 countries and times series data from January 2019 to December 2025. The data are analyzed using a Fixed Effect Model (FEM) with robust standard errors to ensure reliable estimation. The results show that the countries subjected to safeguard policy (BMTP) is associated with lower import volumes, even though the effect is not statistically significant. Meanwhile, exchange rates and inflation have a positive and significant impact on import volume, indicating that macroeconomic conditions play a crucial role in shaping import dynamics. Simultaneously, all variables significantly affect import volume, highlighting the interaction between safeguard policy and macroeconomic factors. These results indicate that the effectiveness of trade policy cannot be separated from macroeconomic context. These findings contribute to the literature by providing empirical evidence on the limited effectiveness of trade protection policies when not supported by stable macroeconomic stability and industrial development. Practically, the study suggests that policymakers should complement protectionist measures with macroeconomic strategies and industrial capacity building.
The Use of the K-Means Algorithm as a Method for Grouping Major Interests of Class X Students of SMK Satrya Budi 1 Commerce Ananda Putri, Handina; Saputra, Herman; Apridonal M, Yori
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6902

Abstract

In the modern era like today, education is one of the most important aspects in supporting the development of quality human resources. In addition, through the main discussion carried out in this study aims to be able to apply the K-Means algorithm as a method for grouping the interests of class X students of SMK Satrya Budi 1 Perdagangan systematically and based on data. In addition, to be able to determine the level of compatibility between student interests and available majors based on the results of the grouping using the K-Means algorithm. And in addition, for the Research Method section used in this study, namely a quantitative approach with the support of data analysis techniques using the K-Means Algorithm Method. The selection of this method is based on the need for research to be able to produce objective grouping of class 10 student majors based on numerical data and certain relevant attributes. So based on this, this study shows the results that the application of the k-means clustering algorithm is able to provide a more objective and systematic approach in the process of determining majors. Grouping is done by processing several assessment criteria such as academic grades, aptitude tests, interest tests, entrance exams and basic skills. Based on the final results of the grouping of 30 students, the system divides students into four main major groups, namely Motorcycle Engineering and Business (8 students), Automotive Light Vehicle Engineering (2 students), Heavy Equipment Engineering (11 students) and Industrial Chemistry (10 students).
The Effect of Perceived ROI on Perceived Value and Adoption Intention Paransa, Rizki Pratama Johanis; Kusuma, Rr. Chusnu Syarifa Diah; Nugroho, Fajar Wahyu; Wulandari, Kurnia
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6926

Abstract

This study aims to examine the role of perceived return on investment (ROI) in shaping perceived value and its impact on adoption intention toward digital branding among small and medium-sized enterprises (SMEs). A quantitative approach with an explanatory research design was employed, involving 100 SME owners in the Special Region of Yogyakarta, Indonesia. Data were collected through structured questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that perceived ROI has a positive and significant effect on perceived value with a t-statistic of 4.562 and a p-value of 0.000 (<0.05) and the path coefficient is 0.513, suggesting that SMEs evaluate digital branding based on the economic benefits gained relative to the costs incurred. Furthermore, perceived value has a positive and significant effect on adoption intention with a t-statistic of 8.781 and a p-value of 0.000 (<0.05) and the path coefficient is 0.625, indicating that perceived value is a determinant in technology adoption decisions. Theoretically, this study provides insights into the importance of value-based evaluation in the context of digital branding adoption among SMEs. Practically, the results suggest that improving SMEs’ understanding of digital branding performance, particularly in terms of ROI, can enhance perceived value and encourage broader adoption of digital branding strategies.
Strategic Management and Market Feasibility of Tegal Tourism: A Digital Transformation Perspective Permatasari, Dwi Novita Cahyaningtyas; Halim, Deddy Kurniawan; Pramesti, Dinar Sukma; Vivi, Vivi
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6964

Abstract

Digital transformation in the tourism sector has accelerated the emergence of technology-driven platforms that enable the end-to-end integration of tourism experiences. This study examines the market feasibility and strategic management implications of the Tegal Tourism platform, which comprises four main subsystems: Virtual Tour, Tourism Marketplace, Mitra Jelajah (partner ecosystem), and an AI-based chatbot. Adopting a mixed-methods approach, the study combines survey data from 116 respondents with in-depth interviews, FGDs, and prototype testing. Market feasibility is evaluated across five key dimensions, namely market demand and trends, consumer segmentation and user profiles, competitor and substitute product analysis, go-to-market and distribution strategies, and quantitative demand estimation. The findings reveal that 56.9% of respondents are familiar with virtual tours, 70% are interested in exploring tourism through such technology, and more than 77% indicate a likelihood of making transactions after a virtual experience, demonstrating strong online-to-offline (O2O) conversion potential. Additionally, 94% of respondents primarily use smartphones, highlighting the importance of a mobile-first strategy. Overall, the platform demonstrates high market feasibility, supported by strong user interest, digital readiness, and significant transaction potential. Four of the five dimensions meet the feasibility criteria, while consumer segmentation and user profiles remain at a medium-to-high risk level and require targeted mitigation. This study contributes to strategic management and digital tourism literature by offering an integrated feasibility framework and practical insights for strengthening digital tourism ecosystems and MSME participation.

Page 35 of 35 | Total Record : 345

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