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Journal of Technology and Computer (JOTECHCOM)
Published by PT. Technology Laboratories Indonesia
ISSN : -     EISSN : 30480477     DOI : -
Core Subject : Science,
Computer Science & IT
The Journal of Technology and Computer (JOTECHCOM) brings together researchers, academics (faculty and students), and industry practitioners to develop the field, discuss new trends and opportunities, exchange ideas and practices, and promote cross-disciplinary and cross-domain collaboration. JOTECHCOM aims to integrate all scientific disciplines, such as computer science, information systems, informatics, information technology, data science, databases, artificial intelligence, data mining, decision support systems, expert systems, and other related disciplines. This journal is published by PT. Technology Laboratories Indonesia (TechnoLabs) Publisher division. Accepted papers will be available online (free open access).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 98 Documents
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A Decision Support System for Selecting Employees Eligible for Bonuses at Uflo Technology Indonesia Using the Analytical Hierarchy Process (AHP) Method Tembusai, Zoelkarnain Rinanda; Santoso, Ahmad Imam; Panjaitan, Dodi Syahputra
Journal of Technology and Computer Vol. 3 No. 2 (2026): May 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Decision Support Systems (DSS) play a crucial role in minimizing cognitive biases in human resource management processes, particularly in employee incentive or bonus schemes. This study aims to design, develop, and implement a web-based decision support system to determine which employees are most deserving of annual bonuses at Uflo Technology Indonesia by applying the Analytical Hierarchy Process (AHP) method. Conventional performance evaluations, which are often subjective, have the potential to reduce work motivation and lead to organizational injustice. To address these dynamics, this system objectively evaluates employee performance based on five main criteria: discipline, productivity, teamwork, work quality, and initiative and creativity. Empirical evaluation data is sourced directly from Uflo Technology’s internal systems, including digital attendance records and daily job reports. Through the AHP algorithm, each criterion is analyzed using hierarchical decomposition and pairwise comparison to generate a consistent global priority weight, where the Consistency Ratio (CR) is rigorously tested to ensure it remains ≤ 0.1. The final results of the study show that the system successfully performs automatic evaluation synthesis and alternative ranking. Computational validation using real-world data placed the Dodi alternative at the highest rank with a final score of 0.335. The implementation of this web-based system has proven capable of improving accuracy, transparency, and time efficiency in the managerial decision-making process within a corporate environment.
Implementation of a Correspondence Inventory System at the Communication and Informatics Office in Takengon Central Aceh Hayati, T. Rahmatul
Journal of Technology and Computer Vol. 3 No. 2 (2026): May 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

The current mail administration system at Diskominfo still on manual processes, which are prone to errors, time-consuming, and difficult to access. Therefore, this study proposes the implementation of a system based on google Workspace, which includes the use of Google Forms for collecting incoming and outgoing mail data, Google sheets for storing and managing data, and Google sites for displaying reports in a transparent and structured manner. The aim of this proposed system is to enhance the efficiency of mail administration processes, reduce the risk of errors, and facilitate information access for relevant parties. The method used in this study is system desigh using a cloud-based modal, where data can be accessed anything and anywhere with an internet connection. Yhe implementation and increase work productivity. The results show that the new system is more efficient, easier to eperate, and more secure in terms of data storange and distribution.
Development of a Location-Aware Web-Based Decision Support System for Used Car Selection Using the SMART Method Aditya, Rili; Dafitri, Haida
Journal of Technology and Computer Vol. 3 No. 2 (2026): May 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

The development of information technology has significantly influenced the process of buying and selling vehicles, especially used cars. The process of selecting used cars often faces several problems, such as limited information, difficulties in comparing vehicle specifications, and different vehicle locations. This study aims to develop a location-aware web-based Decision Support System using the SMART (Simple Multi Attribute Rating Technique) method for used car selection. The system is designed to help users obtain the best used car recommendations based on several criteria, such as price, production year, engine condition, fuel consumption, transmission, mileage, and passenger capacity. The location-aware feature is implemented to allow users to search for used cars based on specific cities, such as Medan, Binjai, Pematang Siantar, and Sibolga. The SMART method is used to perform weighting and ranking of car alternatives to produce objective and measurable recommendations. This research uses data collection methods through literature studies, observations, and questionnaires distributed to 70 respondents. The results show that the developed system is capable of helping users choose used cars more effectively, efficiently, and according to user needs.
Predicting AI-Assisted Student Academic Improvement Using K-Nearest Neighbors Simangunsong, Herbet; Sinaga, Roseri; Simanullang, Jasael
Journal of Technology and Computer Vol. 3 No. 2 (2026): May 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

The rapid integration of Artificial Intelligence (AI) assistants in higher education necessitates empirical methods to evaluate their actual impact on student academic performance. A significant challenge in Educational Data Mining (EDM) is interpreting these impacts accurately, especially given the inherently imbalanced nature of educational datasets. This study proposes a predictive framework utilizing the K-Nearest Neighbors (KNN) algorithm to classify student academic improvement based on AI usage patterns and Learning Management System (LMS) engagement. To ensure model robustness, the Boruta algorithm was applied for feature selection, alongside the SMOTE-Tomek technique to address class imbalance. The optimized KNN model achieved a high predictive performance with an F1-Score of 86.8% and a Balanced Accuracy of 86.1%. Furthermore, the integration of Explainable AI (XAI) via SHapley Additive exPlanations (SHAP) revealed that using AI for conceptual clarification, rather than direct task completion, is the primary driver of academic success. The findings demonstrate that this explainable KNN framework effectively identifies at-risk students, providing educators with transparent, actionable insights to deliver personalized interventions and foster responsible AI usage.
Implementation of Educational Games Using the Levenshtein Distance Algorithm for Improving Elementary School Students' Word Vocabulary Android Rio Dwi Cahya; Nenna Irsa Syahputri
Journal of Technology and Computer Vol. 3 No. 3 (2026): August 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

The low motivation of elementary school students in learning Indonesian vocabulary through conventional methods is needed, so an innovative technology-based approach is needed that is able to combine elements of learning and entertainment. Scramble educational games are designed with a mechanism of randomizing letters from a word that must be rearranged by students into correct words. In the answer validation process, the Levenshtein Distance algorithm is used to measure the error rate based on the minimum number of edit operations (substitution, insertion, or deletion) required for the guessed word to be equal to the target word. With the application of this algorithm, the system is not only able to provide a binary right or wrong assessment, but also assess the degree of closeness of students' answers to the supposed word. This allows for more adaptive and educational feedback, such as "almost correct" when the editing distance is low, thus encouraging students to improve answers with more confidence. This research also emphasizes the ease of use through the Android platform, given the high penetration of mobile devices among the public, including elementary school students. The results of the implementation show that the Levenshtein Distance algorithm-based scramble educational game is effective in increasing learning motivation and enriching students' vocabulary, while providing an alternative interactive learning method that is relevant to the development of educational technology.
Analyzing the Impact of Information Systems Digitalization on Organizational Performance through the Technology Acceptance Model (TAM) Sitompul, Novian Paisal; Haqki, Bay; Harahap, Baginda; Harahap, Solianna; Panggabean, Erwin
Journal of Technology and Computer Vol. 3 No. 3 (2026): August 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

The digitalization of information systems has become a key strategy for organizations seeking to improve operational efficiency, decision-making quality, and overall organizational performance. However, the successful implementation of digital technologies depends largely on users’ acceptance and willingness to adopt such systems. This study aims to analyze the impact of information systems digitalization on organizational performance using the Technology Acceptance Model (TAM). The research examines the relationships between perceived usefulness, perceived ease of use, user acceptance, and organizational performance. A quantitative research approach was employed by collecting data through structured questionnaires distributed to employees who actively use digital information systems within their organizations. The collected data were analyzed using Structural Equation Modeling (SEM) to evaluate the proposed research model and test the hypotheses. The findings indicate that perceived usefulness and perceived ease of use significantly influence user acceptance, which subsequently contributes to improved organizational performance. These results highlight the importance of designing user-friendly and beneficial digital information systems to maximize organizational outcomes. The study provides valuable insights for organizations in developing effective digital transformation strategies and enhancing sustainable organizational performance through technology adoption.
Digital Transformation of Mentawai Islands Tourism Through a User-Centered Website Using the Waterfall Method Ora Pronobis Saogo; Ummul Khair
Journal of Technology and Computer Vol. 3 No. 3 (2026): August 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

The rapid advancement of information technology has significantly accelerated digital transformation in the tourism sector by improving the accessibility and dissemination of tourism information. The Mentawai Islands possess considerable tourism potential, including marine tourism, natural attractions, and cultural heritage. However, the availability of integrated digital information remains limited, reducing the effectiveness of tourism promotion. This study aims to design and develop a web-based tourism information system for the Mentawai Islands using the Waterfall software development method with a focus on user-centered interface design. The research was conducted through five sequential phases: requirements analysis, system design, implementation, testing, and maintenance. The developed website provides comprehensive tourism information, including destination descriptions, tourism categories, image galleries, location maps, and contact information. Functional testing was performed using the Black Box Testing method to evaluate the performance of each system feature. The results indicate that the developed website successfully provides structured tourism information, enhances user experience through an intuitive interface, and improves the effectiveness of digital tourism promotion. Therefore, the proposed system can support the digital transformation of tourism management while increasing public accessibility to tourism information in the Mentawai Islands.
Application of the K-Means Clustering Algorithm to Categorize Pregnant Women's Knowledge and Attitudes Towards Smoking During Pregnancy Egi Affandi; Baginda Harahap; Solianna Harahap
Journal of Technology and Computer Vol. 3 No. 3 (2026): August 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Smoking and secondhand smoke exposure during pregnancy remain a significant maternal and child health risk, yet conventional descriptive analysis tends to treat knowledge and attitude scores separately, making it difficult to identify combined risk profiles for targeted health education. This study applies K-Means Clustering, a data mining technique from computer science, to group pregnant women based on the combination of their knowledge and attitude scores toward smoking during pregnancy. Data were collected from 30 respondents through a questionnaire covering 10 knowledge items and 10 Likert-scale attitude items. The knowledge and attitude percentage scores were standardized (Z-score) and used as clustering features. The optimal number of clusters was determined using the Elbow Method and Silhouette Score, both of which pointed to k = 3 as the most interpretable solution, yielding a final Silhouette Score of 0.687. The resulting clusters were labeled Good (mean knowledge 86.0%, mean attitude 86.5%), Moderate (65.0%, 66.0%), and Poor (43.0%, 41.2%), each containing 10 respondents. The Poor cluster was dominated by housewives with the highest average parity, indicating a priority target group for smoking-related health education programs. These findings demonstrate that K-Means Clustering can serve as a practical decision-support tool for prioritizing maternal health interventions based on combined knowledge-attitude profiles, complementing conventional descriptive statistics commonly used in public health research.

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