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INDONESIA
Journal of Information Systems Engineering and Business Intelligence
Published by Universitas Airlangga
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal ini menerima makalah ilmiah dengan fokus pada Rekayasa Sistem Informasi ( Information System Engineering) dan Sistem Bisnis Cerdas (Business Intelligence) Rekayasa Sistem Informasi ( Information System Engineering) adalah Pendekatan multidisiplin terhadap aktifitas yang berkaitan dengan pengembangan dan pengelolaan sistem informasi dalam pencapaian tujuan organisasi. ruang lingkup makalah ilmiah Information Systems Engineering meliputi (namun tidak terbatas): -Pengembangan, pengelolaan, serta pemanfaatan Sistem Informasi. -Tata Kelola Organisasi, -Enterprise Resource Planning, -Enterprise Architecture Planning, -Knowledge Management. Sistem Bisnis Cerdas (Business Intelligence) Mengkaji teknik untuk melakukan transformasi data mentah menjadi informasi yang berguna dalam pengambilan keputusan. mengidentifikasi peluang baru serta mengimplementasikan strategi bisnis berdasarkan informasi yang diolah dari data sehingga menciptakan keunggulan kompetitif. ruang lingkup makalah ilmiah Business Intelligence meliputi (namun tidak terbatas): -Data mining, -Text mining, -Data warehouse, -Online Analytical Processing, -Artificial Intelligence, -Decision Support System.
Arjuna Subject : -
Articles 15 Documents
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Search results for , issue "Vol. 11 No. 2 (2025): June" : 15 Documents clear
Exposing Causative Factors on Software Discontinuity using an Elaborative Qualitative Method Gandhi, Arfive; Kusumo, Dana Sulistiyo; Sardi, Indra Lukmana
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.103-114

Abstract

Background: Software discontinuity due to the inability to accommodate the needs of users is a the significant challenge facing the software development life cycle. This implied that the development team must be capable of producing software with extended lifespan, including the ability to detect outages early, to maintain continuity. Organizations need to determine the contributing and inhibiting factors responsible for discontinuity usage.  Objective: This research aimed to explore the factors that contribute and inhibit the discontinuation of software use in organizations as well as the prevention strategies.  Methods: The summative content analysis technique was used to capture, codify, and classify statements from respondents to discover usage pattern. Data were collected through interview and questionnaire techniques with 10 respondents from various Indonesian companies. The respondents had various sectoral backgrounds in software usage for more than a year. The data collected were compared, contrasted, and synthesized to deliver a holistic pattern among respondents.  Results: The result showed that 10 key factors contributed to software discontinuity, namely Loss of Perceived Usefulness (LUS), Loss of Perceived Ease of Use (LEU), Decreased Effort Expectancy (DEX), Decreased Performance Expectancy (DPX), Social Influence (SOI), Lack of Facilitating Conditions (LFC), Decreased Price Value (DPV), Lack of Habit (LHB), Hedonic Motivation (HDM), and Loss of Perceived Behavioral Control (LBC). The factors were further categorized into three big issues, including Software Usability (LUS, LEU, DEX, and DPX), External Triggers (DPV, SOI, and LBC), and Risk Management after Discontinuity (LFC, LHB, and SOI). Furthermore, the results indicated that nine factors contributed to software discontinuity except HDM with LEU and LUS having weak significance since most respondents stated partial agreement and disagreements.  Conclusion: This research employed a rigorous qualitative method to validate the factors in the proposed software discontinuity model with 10 causative factors. The acquired knowledge is expected to aid organizations or related development units to build software that accommodates user needs, including meeting long-term business targets.  Keywords: Software, Software Discontinuity, Influencing Factors, Qualitative Method
Assessing Information Security Awareness Among Indonesian Government Employees: A Case Study of the Meteorology, Climatology, and Geophysics Agency Prasetyo, Aji; Aji, Rizal Fathoni; Wibowo, Wahyu Setiawan
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.126-142

Abstract

Background: Cybersecurity is important for government agencies and the usefulness shows the need for a thorough understanding of information security awareness (ISA) among employees in order to enhance protective measures and ensure compliance with regulations. The Meteorology, Climatology, and Geophysical Agency (BMKG) of Indonesia is very important in providing essential national data and this responsibility shows the need to assess and promote ISA among the employees. The efforts to ensure a robust ISA culture can allow BMKG to safeguard sensitive meteorological and geophysical data, strengthen operational resilience, maintain public trust, and mitigate potential cyber threats that are capable of compromising national security.  Objective: This study aimed to evaluate the level of organizational ISA among employees at BMKG and to improve measures considered important.  Methods: The Human Aspects of Information Security Questionnaire (HAIS-Q) was administered as the reference model to assess the knowledge, attitudes, and behaviors of employees regarding information security. A descriptive statistical analysis and Partial Least Squares Structural Equation Modelling (PLS-SEM) were further applied to analyze data from 459 BMKG employees across various security domains, including password management, email use, internet use, social media use, mobile device security, and incident reporting.  Results: The results showed that BMKG employees possessed a high overall level of ISA (88.06%) with the average knowledge, attitudes, and behaviors recorded to be 88.06%, 81.89%, and 80.74%, respectively. Meanwhile, specific areas such as email use (78.70%) and mobile device use (73.19%) had only moderate awareness. The structural model analysis also showed that behavior exerted the most significant influence on ISA (β = 0.423), followed by attitude (β = 0.289) and knowledge (β = 0.214).  Conclusion: The overall awareness level was positive but there was a need for targeted efforts in password management, email use, and mobile device security to improve ISA practices. Moreover, the implementation of comprehensive information security policies, regular training, and organizational support was suggested to be important for fostering a robust security culture within BMKG.  Keywords: Information Security Awareness, Cybersecurity, BMKG, PLS-SEM, Government Employees, Indonesia
Factors Influencing the Diffusion of Blockchain Technology in the Indonesian Goverment Noman, Eltyasar Putrajati; Gwenhure, Anderson Kevin
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.215-225

Abstract

Background: Blockchain can improve the security and efficiency of government information systems. However, the adoption of this technology in Indonesia is still limited, especially in the government sector. Previous studies have emphasized the importance of regulatory and legal aspects in blockchain implementation. This condition is a challenge and an opportunity to examine the factors that influence the diffusion of blockchain innovation in the Indonesian government.  Objective: This study aims to identify and analyze the factors that influence the diffusion of blockchain technology in the Indonesian government through hypothesis testing and conceptual model development, as well as to determine the current stage of blockchain technology diffusion in the Indonesian government.  Methods: This study uses data from a questionnaire survey of 24 government agencies in Indonesia, representing various levels of central, provincial, district, and city, and focusing on the technology sector. A total of 192 responses were successfully collected. The collected data were analyzed using SmartPLS software to test the validity and reliability of the instrument, research hypothesis, and proposed conceptual model, and the results of the hypothesis test were used to determine the current stage of blockchain technology diffusion in the Indonesian government.  Results: The study's results indicate that the research instruments used are valid and reliable and meet the requirements for use in this study. Of the eight hypotheses proposed, three were accepted, and five were rejected. The tested conceptual model showed good agreement with the empirical data.  Conclusion: This study concludes that relative advantage and stakeholder roles are key factors significantly influencing the Indonesian government's intention to adopt blockchain technology. In contrast, complexity, regulation, top management support, and competence do not significantly influence adoption intentions. The diffusion of blockchain technology in the Indonesian government is still in the knowledge stage, so the decision to adopt it has not been reached. The implication is that the government needs to prioritize blockchain advantages and actively involve stakeholders, such as experts and developers, in efforts to adopt this technology.  Keywords: Diffusion of Innovation, Blockchain, Information Systems, E-Government, Information Technology Management 
User Experience as a Predictor of E-commerce Continuation Intention in Indonesia: Examining the Role of Shopping Orientation as a Moderator Widyaningrum, Premi Wahyu; Astuti, Endang Siti; Yulianto, Edy; Mawardi, Mukhammad Kholid
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.187-199

Abstract

Background: The integration of Stimulus-Organism-Response (SOR) framework and Technology Acceptance Model (TAM) is still in need of improvement, particularly in studies examining individual behavior in Indonesian e-commerce context. A common challenge in e-commerce adoption is individual willingness and intention to adopt, which is influenced by previous user experience. Consequently, there is a need for the establishment of standard to measure user experience in e-commerce.  Objective: This study aims to measure the post-adoption experience of e-commerce user, which will shape attitude and influence future continuance intention (CI).  Methods: This study integrated SOR and TAM frameworks, followed by the collection and analysis of data from 263 respondents using Structural Equation Modeling-Partial Least Squares (SEM-PLS). Among the four hypotheses proposed, two represented novel contributions to the existing literature.  Results: The results showed a positive and significant influence of Interaction Experience (IE), Sense Experience (SE), and Flow Experience (FE) on Attitude Toward Using (ATU). The data analysis also indicated a positive and significant effect of ATU on Continuance Intention (CI). However, the influence of ATU on CI became insignificant when moderated by Shopping Orientation (SO).  Conclusion: Based on the results, not all hypotheses proposed in this study are supported. However, the results provide both theoretical and practical contributions.  Keywords: SOR, TAM, User Experience, Continuance Intention, e-commerce 
The Influence of Gamification Affordance on Customer Loyalty among E-Commerce in Indonesia Zega, Luther Risman Luosaro; Perdanakusuma, Andi Reza; Hariyanti, Uun
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.115-125

Abstract

Background: The e-commerce industry in Indonesia is experiencing competition due to the rising number of users and price-sensitive consumers, making user loyalty a major challenge for companies. Although gamification, such as task/quest type, was recognized as a strategy to boost loyalty, previous studies showed inconsistent results regarding its impact on hedonic and utilitarian values.  Objective: This study aimed to explore the relationships among task/quest-type gamification affordance (GA), hedonic value (HV), utilitarian value (UV), satisfaction (SA), and loyalty (LOY) among Indonesian e-commerce users.   Methods: A total of 284 e-commerce app users who had engaged in task/quest-type gamification were selected as participants using a convenience sampling method. A quantitative method was adopted and survey data were examined by covariance-based structural equation modeling (CB-SEM) conducted in SmartPLS4.  Results: The analysis showed that gamification affordance significantly impacted users’ perceived hedonic and utilitarian values. An increase in these values significantly enhanced user satisfaction, and strongly correlated with loyalty. Gamification affordance also indirectly influenced loyalty through hedonic value, utilitarian value, and satisfaction.  Conclusion: Task/quest-type gamification affordance effectively enhanced user loyalty in Indonesian e-commerce by improving perceived hedonic and utilitarian values and satisfaction. These results suggested that gamification strategies focusing on task/quest-type elements could foster loyalty in a competitive e-commerce environment.  Keywords: Gamification Affordance, Hedonic Value, Utilitarian Value, Satisfaction, Loyalty
Classification and Counting of Mycobacterium Tuberculosis using YOLOv5 Saurina, Nia; Chamidah, Nur; Rulaningtyas, Riries; Aryati, Aryati
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.267-278

Abstract

Background: Indonesia is a nation with the third-highest number of tuberculosis (TB) cases worldwide, after China and India. TB detection has been facilitated using YOLOv5 deep learning framework despite previous studies not having incorporated assessment metrics recommended by International Union Against Tuberculosis and Lung Disease (IUATLD).   Objective: This study aims to present a method for classifying and enumerating Mycobacterium tuberculosis by using YOLOv5 architecture with IUATLD evaluation standards. Sputum samples served as the primary medium for identifying the presence of Mycobacterium tuberculosis. In addition, the method showed precise delineation of bacterial boundaries to minimize classification inaccuracies and improve edge clarity through YOLOv5.  Methods: Following the acquisition of microscopic images of TB, the data were resized from 1632x1442 to 640x480 pixels. Annotation was performed using YOLOv5 bounding boxes, and the model was subsequently trained as well as tested according to IUATLD guidelines.  Results: During the analysis, YOLOv5-based classification system produced optimal performance. The model achieved 84.74% accuracy, 87.31% precision, and Mean Average Precision (mAP) score of 84.98%. These metrics showed high reliability in identifying Mycobacterium tuberculosis in the image dataset.  Conclusion: The classification and quantification of Mycobacterium tuberculosis using YOLOv5 framework shows high precision, with mAP score of 84.98%, signifying strong model performance. Additionally, the counting process achieves a MAPE (Mean Absolute Percentage Error) of 0.15%, reflecting excellent prediction accuracy.  Keywords: IUATLD, Tuberculosis, YOLOv5.
Boosting Multiverse Optimizer by Simulated Annealing for Dimensionality Reduction Mutlag, Wamidh K.; Mazher, Wamidh Jalil; Ibrahim, Hadeel Tariq; Ucan, Osman Nuri
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.254-266

Abstract

Because of its dynamic graph structure and exceptional global/local search abilities, the Multiverse Optimizer (MVO) is widely used in feature selection. The exponential growth of the search space makes finding the optimum feature subset for numerous dimensional datasets quite challenging. Despite that MVO is a promising algorithm, the sluggish convergence issue affects the multi-verse optimizer performance. This work focuses on hybridizing and boosting MVO with the powerful local search algorithm, Simulated Annealing algorithm (SAA), in order to get around MVO limitations and enhance feature selection efficiency in high dimensional datasets. Stated differently, a paradigm known as high-level relay hybrid (HRH) is put forth that sequentially implements self-contained optimization (i.e. MVO and SAA). As a result, the optimal regions are found by MVO and then supplied to SAA in the suggested MVOSA-FS model. Ten high-dimensional datasets obtained from the Arizona State University (ASU) repository were used to verify the effectiveness of the proposed method; the results are compared with other six state-of-the-art feature selection algorithms: Atom Search Optimization (ASO), Equilibrium Optimizer (EO), Emperor Penguin Optimizer (EPO), Monarch Butterfly Optimization (MBO), Satin Bowerbird Optimizer (SBO), and Sine Cosine Algorithm (SCA). The results validate that the proposed MVOSA-FS technique performed better than the other algorithms and showed an exceptional ability to select the most significant and optimal features. The lowest average error rates, classification standard deviation (STD) values, and feature selection (FS) rates are obtained by MVOSA-FS across all datasets.
Enhancing the Comprehensiveness of Criteria-Level Explanation in Multi-Criteria Recommender System Rismala, Rita; Maulidevi, Nur Ulfa; Surendro, Kridanto
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.160-172

Abstract

Background: The explainability of recommender systems (RSs) is currently attracting significant attention. Recent research mainly focus on item-level explanations, neglecting the need to provide comprehensive explanations for each criterion. In contrast, this research introduces a criteria-level explanation generated in a content-based pardigm by matching aspects between the user and item. However, generation may fall short when user aspects do not match perfectly with the item, despite possessing similar semantics.  Objective: This research aims to extend the aspect-matching method by leveraging semantic similarity. The extension provides more detail and comprehensive explanations for recommendations at the criteria level.    Methods: An extended version of the aspect matching (AM) method was used. This method identified identical aspects between users and items and obtained semantically similar aspects with closely related meanings.   Results: Experiment results from two real-world datasets showed that AM+ was superior to the AM method in coverage and relevance. However, the improvement varied depending on the dataset and criteria sparsity.  Conclusion: The proposed method improves the comprehensiveness and quality of the criteria-level explanation. Therefore, the adopted method has the potential to improve the explainability of multi-criteria RSs. The implication extends beyond the enhancement of explanation to facilitate better user engagement and satisfaction.  Keywords: Comprehensiveness, Content-Based Paradigm, Criteria-Level Explanation, Explainability, Multi-Criteria Recommender System
Optimizing IndoBERT for Revised Bloom's Taxonomy Question Classification Using Neural Network Classifier Darfiansa, Lazuardy Syahrul; Fitriyani; Larasati, Sza Sza Amulya
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.226-237

Abstract

Background: A major challenge in Indonesian education system is the continued dominance of exam questions that primarily assess basic thinking skills, such as remembering and understanding. In order to effectively nurture students with critical, analytical, and creative thinking skills, the integration of higher-order thinking questions has become increasingly urgent. An effective conceptual framework that can be utilized in this regard is Revised Bloom's Taxonomy (BT). This framework classifies cognitive skills into 6 levels, namely remember, understand, apply, analyze, evaluate, and create. Furthermore, the framework is particularly important as it promotes the development of exam questions that transcend lower-level thinking skills, fostering a deeper and higher level of understanding among students. In this context, automated systems powered by deep learning (DL) have shown promising accuracy in classifying questions based on BT levels, thereby offering practical support for educators aiming to design more meaningful and intellectually stimulating assessments.  Objective: This research aims to develop a classification system that can effectively classify Indonesian exam questions based on BT using IndoBERT pretrained models. These models were combined with Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) classifiers (referred to as IndoBERT-CNN and IndoBERT-LSTM) to determine the model with the highest performance.   Methods: The dataset utilized was self-collected and underwent several stages of preparation, including expert labeling and splitting. Furthermore, preprocessing was conducted to ensure the dataset was consistent and free from irrelevant features related to case folding, tokenization, stopword removal, and stemming. Hyperparameter fine-tuning was subsequently carried out on IndoBERT, IndoBERT-CNN, and IndoBERT-LSTM. Model performance was evaluated using Accuracy, F-Measure, Precision, and Recall.  Results: The fine-tuned IndoBERT model results showed that IndoBERT-LSTM outperformed IndoBERT-CNN. The optimal hyperparameter configuration, batch size of 64 and learning rate of 5e-5, showed the highest performance, achieving Accuracy of 88.75%, Precision of 85%, Recall of 88%, and F-Measure of 86%.  Conclusion: IndoBERT, IndoBERT-CNN, and IndoBERT-LSTM reflected promising results, although the performance of the models was significantly affected by respective architectures and hyperparameter settings. Among the three observed models, IndoBERT was found to perform best with smaller batch sizes and moderate learning rates. IndoBERT-CNN achieved stronger results with a higher learning rate and similar batch sizes. IndoBERT-LSTM recorded the highest accuracy with larger batch sizes for gradient stability. However, IndoBERT was constrained by its focus on Indonesian language, and the interpretability of the predictions made, specifically in relation to expert-labeled data, remained unclear.  Keywords: Bloom’s Taxonomy, CNN, Hyperparameter Fine-Tuning, IndoBERT, LSTM, Question Classification
Aligning Software Product Management with Software Engineering Concepts: A Systematic Literature Review Oruthotaarachchi, Chalani; Wijayanayake, Janaka
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.143-159

Abstract

Background: Software Product Management (SPM) plays a vital role in the success of many software projects by aligning customer needs with their business objectives and ensuring a seamless and effective software product lifecycle. SPM is established as a collection of tools, techniques, and practices that help an organization accomplish its objectives and enhance the predictability and profitability of software product development. However, despite its significance, SPM research has been fragmented into specific topics having limited SPM literature reviews. This research study addresses this gap and discusses the status of the SPM domain in a more holistic spectrum.  Objective: The study aims to review recent literature on SPM, focusing on the alignment of SPM with software engineering concepts, a product manager’s role, the existing framework, ontologies, and best practices that support ensuring the success of a product manager’s role.  Methods: A systematic literature review was conducted using SCOPUS, IEEE Xplore, ACM Digital Library, ScienceDirect, and ProQuest Central as databases. 71 articles were selected following a rigorous screening process as per the PRISMA 2000 statement.  Results: Integrating SPM and SE is crucial in delivering value-driven software solutions. Available theoretical models and frameworks can help with this integration; however, implementing these frameworks often has challenges. Even though product managers play a vital role in the software lifecycle, they lack sufficient organizational support to enrich their skills and knowledge. Other major challenges are the lack of knowledge to use emerging technologies such as AI for data-driven decision-making processes and the tendency to replace humans with such technologies.  Conclusion: Aligning strategic vision with agile flexibility is important to integrate SPM with SE practices. To improve decision-making and ensure better alignment of SPM with business objectives, organizations have to enhance product managers’ capabilities by leveraging emerging technologies. Research can focus on developing adaptable and user-friendly SPM frameworks that match both medium-scale and large-scale organizational expectations.  Keywords: Organizational Value, Product Manager Role, Software Engineering Integration, Software Product Management, SPM Challenges, SPM Frameworks 

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