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Eva Khudzaeva
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Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Syarif Hidayatullah Jakarta Jl. Ir. H. Juanda No.95, Cempaka Putih, Ciputat Timur. Kota Tangerang Selatan, Banten 15412
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Applied Information System and Management
Published by Universitas Islam Negeri Syarif Hidayatullah Jakarta
ISSN : 26212536     EISSN : 26212544     DOI : 10.15408/aism
Core Subject : Education,
Languange, Linguistic, Communication & Media
Arjuna Subject : -
Articles 20 Documents
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Search results for , issue "Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)" : 20 Documents clear
The Role of Geographic Information Systems in Marketing Strategy: Improving the Efficiency of Store Locations and Consumer Targeting Based on Alfamart Locations in Bandung City Syaifuddin, Syaifuddin; Puad, Noor Aimi Mohamad; Rusdian, Suca
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.45522

Abstract

This research explores the application of Geographic Information Systems (GIS) to optimize location selection and consumer targeting strategies for Alfamart mini markets in Bandung City. The purpose of this study is to assess how GIS can improve the decision-making process in determining the location of new outlets by integrating spatial data with multi-criteria decision analysis methods. This research uses Analytical Hierarchy Process (AHP) to evaluate the best location based on factors such as population density, accessibility, and the presence of competitors. Additionally, authors conducted consumer segmentation using the K-means clustering technique to understand consumer behavior based on shopping patterns and geographical distribution. Key findings showed that the Dago area in Bandung was the optimal location for the new store, with a 25% increase in foot traffic and a 30% increase in sales during the first three months of operation. This research emphasizes the importance of using GIS not only for spatial analysis but also for more targeted marketing, improved operational efficiency, and customer satisfaction. However, there are limitations in terms of dependence on data quality and the dynamics of consumer preferences. Future research could expand the coverage area and integrate additional variables to refine the application of GIS in retail location planning.
Risk Management in IT Projects for Digital Banking: A Case Study of an Indonesian State-Owned Bank Wibowo, Aji Prastio; Raharjo, Teguh; Trisnawaty, Ni Wayan; Muhamad, Gilang Aulia; Faridy, Azka
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46123

Abstract

The increasing use of information technology in the banking industry has made it more difficult to manage risks in the digital projects of state-owned banks. This study aims to examine the risk management processes of a state-owned mortgage bank in Indonesia and how it manages the information technology risks in the digital banking project lifecycle. This qualitative research is based on content analysis of forty-three risk assessment documents, with thematic coding using ATLAS.ti. This research was further enriched through expert interviews and a quantitative survey conducted among 38 project stakeholders. Risks are defined in a hierarchical classification and mapped to project phases using the PMBOK. Identifying operational, compliance, and third-party risks is most pertinent in the execution and post-implementation phases. Additionally, there are pressing concerns, such as the potential for cyber threats, non-compliance with applicable laws and regulatory frameworks, integration issues, over-reliance on service vendors, and systemic dependence on external vendors. In this case, the study integrates PMBOK, ISO 31000:2018, and the insights of seasoned practitioners to create a singular holistic mitigation strategy. It comprises a risk prioritization matrix, phased actionable treatment plans for each defined stage, and robust governance and responsiveness enhancement mechanisms for high-risk reactive IT environments. The guidance is triangulated with sector-specific intelligence, thereby underscoring proactive risk governance through communication, vendor due diligence, dynamic control, and real-time accountability across boundaries scaffolding. Further single-initiative case studies, multi-institutional case studies, evolving longitudinal risk studies, and the application of AI and blockchain for predictive and autonomous risk steering in digital finance could enhance and refine this work. 
Evaluating The Effectiveness of Augmentation and Classifier Algorithms for Fraud Detection: Comparing CGAN and SMOTE with Random Forest and XGBoost Sarmini, Sarmini; Sunardi, Sunardi; Fadlil, Abdul
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46308

Abstract

Fraud detection in imbalanced datasets, where fraudulent transactions represent a small fraction of total data, presents a major challenge for machine learning models. Traditional classifiers often perform poorly in such scenarios due to their bias toward the majority class. This study investigates the effectiveness of two data augmentation techniques, Synthetic Minority Over-sampling Technique (SMOTE) and Conditional Generative Adversarial Networks (CGAN) in improving fraud detection performance. Both methods are applied to balance the dataset, and their impact is evaluated using two classifiers: Random Forest (RF) and XGBoost. The models are tested across three versions of the dataset: the original imbalanced data, the SMOTE-augmented data, and the CGAN-augmented data. Evaluation metrics include accuracy, precision, recall, F1 score, and ROC-AUC. Results indicate that both augmentation techniques enhance the models' ability to detect fraudulent transactions compared to the original dataset. Notably, CGAN outperforms SMOTE in terms of recall and F1 score, suggesting its ability to generate more diverse and realistic synthetic samples. While SMOTE creates new samples through interpolation, CGAN uses an adversarial process involving a generator and a discriminator, resulting in more complex data representations. The study also finds that XGBoost combined with CGAN yields the highest performance, effectively capturing intricate fraud patterns. In contrast, SMOTE, though beneficial, shows limited capacity in improving recall. This research highlights the importance of advanced augmentation techniques like CGAN in addressing class imbalance and improving fraud detection systems. It also opens pathways for future exploration of deep learning-based augmentation and classification methods in fraud detection.
Enterprise Architecture Planning with TOGAF ADM: A Case Study of a Heavy Equipment Rental Service Company Safrianto, Rian
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46335

Abstract

Strategic Information Systems (IS) and Information Technology (IT) planning play a vital role in aligning technological initiatives with business objectives, particularly in asset-intensive industries. This study aims to implement the TOGAF ADM framework to design a strategic IS/IT planning model for a heavy equipment rental company, demonstrating how enterprise architecture can align IT initiatives with business goals. PT. XYZ has not yet implemented an information system strategy for the company’s needs in terms of management, leading to inefficiencies in business operations at PT. XYZ. A qualitative approach was used to obtained through in-depth interviews with company’s owners and managers,  observation data of company’s IT asset also collected to describe organization’s current IS/IT landscape and applies the TOGAF ADM phases to design an enterprise architecture that supports business-IT alignment. This study demonstrates how TOGAF ADM can provide a structured methodology for identifying business needs, defining architectural visions, and developing a roadmap for IS/IT improvements. Findings indicate that using EA frameworks such as TOGAF ADM enhances strategic planning capabilities, supports organizational agility, and provides a repeatable model for similar enterprises in the rental or industrial sector. The results offer valuable insights for practitioners and researchers interested in applying enterprise architecture to improve IS/IT strategic planning processes.
Uncovering The Barriers and Business Impacts of E-Commerce Non-Adoption Among SMEs: A TOE Framework Perspective Religia, Yoga; Ramawati, Yussi; Said, Jamaliah
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46657

Abstract

This study investigates barriers in technology, organization, and environment that prevent Indonesian SMEs from adopting e-commerce and examines their effects on business sustainability. Using the TOE framework, this research adopts a quantitative cross-sectional method, with data from 320 SMEs analyzed using PLS-SEM. Results reveal that technological and environmental barriers significantly hinder e-commerce adoption, negatively affecting sustainability, while organizational barriers have no significant impact. These findings highlight the need for targeted interventions to address technological and environmental challenges. The study provides valuable insights for policymakers to foster supportive environments, enhance SME competitiveness, and promote digital inclusion. By addressing these barriers, SMEs can access digital markets more effectively, improve performance, and contribute to economic growth. This research underscores the importance of policies supporting SME growth and digital transformation, offering guidance to improve e-commerce adoption and business sustainability in the digital era. 
Automated Glaucoma Detection and Classification from Large-Scale Fundus Image Dataset Using YOLOv8 and CNN Islam, Sheikh Aminul; Khan, Humana; Taher, Taslim
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46658

Abstract

Glaucoma is a major eye condition that slowly damages the optic nerve and remains one of the top causes of permanent blindness around the world. This study presents an automated framework for early detection and classification of glaucoma using artificial intelligence techniques applied to large-scale retinal fundus image dataset of over 17,000 images. The optic disc (OD) and optic cup (OC) were localized using YOLOv8. Following this, we conducted Region of Interest (ROI) extraction and contour masking to isolate the OD and highlight critical regions for further examination. We extracted essential features, such as the Cup-to-Disc Ratio (CDR), Vertical CDR (VCDR), neuroretinal rim (NRR) thinning, and compliance with the ISNT (Inferior > Superior > Nasal > Temporal) rule, resulting in a detailed tabular dataset. For classification, we applied ML and DL models. YOLOv8 demonstrated superior detection precision and CNN led the classification models with 87.13% accuracy. The proposed method offers a reliable, automated solution that can support large-scale glaucoma screening in clinical settings. This framework has the potential to assist ophthalmologists by improving the speed and accuracy of early glaucoma diagnosis, reducing the risk of vision impairment in affected patients.
Predictive Modeling of Student Dropout Using Academic Data and Machine Learning Techniques Aini, Qurrotul; Rahajeng, Elsy; Tiohandra, Mufadha; Pratama, Hamzah Aji; Hammad, Jehad
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46659

Abstract

This study's objective is to investigate the performance of a predictive model for students at risk of dropout (DO) by considering several internal criteria of an academic program. This research uses academic information from UIN Syarif Hidayatullah Jakarta and applies the C4.5, Naive Bayes Classification (NBC), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) to forecast which students might drop out. The data used consists of 714 student records from Department of Information Systems for the academic year 2010–2015 as training and 2018 as testing data. The research method refers to the SEMMA framework (Sample, Explore, Modify, Model, and Assess) to ensure systematic and accurate data processing. Meanwhile, the internal criteria used are the completed courses, the status of the internship report, and the final project proposal. According to the study's findings, the C4.5 and SVM algorithms get the best accuracy rates of 94.44%, while KNN and NBC come in second and third, respectively, with 93%. The results show that the C4.5 and SVM algorithms work well with academic data. This study provides a substantial contribution to the development of a prediction system for students at risk of dropping out, which can be integrated into data-based applications or dashboards. This solution is expected to help higher education institutions identify students who need further academic support. In addition, this research also opens up opportunities for the progress of more accurate forecasting models through the integration of additional variables such as behavioral or psychological data. With this data-driven approach, higher education institutions can enhance their efficiency in monitoring and preventing student dropouts, thereby supporting a vision of quality and sustainable education.
Integrating Technology Acceptance and Government Trust to Explain Public Engagement on Social Media: An IPMA-Based Study in Local E-Government Communication Imtihan, Khairul; Rodi, Muhamad; Bagye, Wire; Fitriyani, Baiq Yulia
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46660

Abstract

In the digital transformation era, local governments increasingly use social media to foster transparency, disseminate information, and enhance civic participation. However, challenges remain in ensuring consistent public engagement and user satisfaction, especially in regions with limited digital literacy and uneven access to infrastructure. This study investigates the key determinants of user satisfaction, engagement, and continuance intention in local government social media platforms, with a specific focus on Central Lombok, Indonesia, a rural region facing significant digital inclusion gaps. The research combines the Technology Acceptance Model (TAM), which focuses on how easy and useful a system is, with the e-Government Adoption Model (e-GAM), which looks at factors like trust in the government, transparency, how interactive the platform is, and perceived risks. A survey of 557 users was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance Performance Map Analysis (IPMA), showing that user satisfaction is greatly affected by how easy the platform is to use and how much users trust it. Digital literacy, interactivity, and institutional trust further shape these perceptions. Interestingly, perceived usefulness and perceived risk did not show strong direct effects, which was surprising and might be due to regular usage habits and dependence on institutional signals in rural areas. IPMA results indicate that interactivity, user trust, and digital literacy are high-impact yet underperforming areas, warranting strategic attention. The study makes progress in theory by merging behavioral and institutional models and provides practical suggestions for improving two-way communication, building public trust, and encouraging digital skill development to boost meaningful participation in local digital governance.
Revealing User Perception and Mental Model in My Tel-U Apps: A UX and Integrated Method Muttaqin, Alif Noorachmad; Lubis, Muharman; Handayani, Dini; Zamzami, Ikhlas Fuad
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46667

Abstract

My Tel-U app user experience and usability were tested using a mixed-methods design with both quantitative and qualitative measurements. User experience was measured quantitatively using the User Experience Questionnaire (UEQ), as well as general satisfaction assessed by the Customer Satisfaction Score (CSAT), and task-based usability testing to evaluate actual user interaction. Thirty participants from different faculties and levels of study at Telkom University joined to experience various digital exposures and acclimate their behaviour to the application. UEQ results indicate overall positive attitudes across all six scales, with Perspicuity, Attractiveness, and Dependability achieving the highest scores. CSAT was 90%, indicating that most users were satisfied or very satisfied with the application. Although task accomplishment increased, usability testing revealed that problems such as slowness, poor navigation organization, and inadequate system feedback persisted. Open-ended questions confirmed similar issues, such as core functionality like grade viewing and attendance tracking, as well as ongoing concerns about performance and reliability. These results indicate that, although the application adheres to functional requirements, user support, response time, and clarity may need improvement in certain aspects. This research contributes to an integrative UX evaluation model by incorporating perceptual, emotional, and behavioural measures. The results provide positive feedback to developers and institutional stakeholders, justifying priorities for alterations that will make the My Tel-U app more accessible, user-friendly, and support long-term usage on the online learning platform.
Building Resilience Digital Community Ecosystem by Applications Information System and Brand Experience Kristanto, Harys; Arumdini, Savira; Fardhon, Muhammad; Kurniawan, Wahyu
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/caism.v8i2.46678

Abstract

In the face of rapid technological advancements and socio-economic disruptions, digital community ecosystems must develop resilience to ensure sustainability and adaptability. This study investigates how digital applications, information systems, and brand experience contribute to building resilience in Indonesia's land transportation sector. Using a quantitative approach, data were collected from 350 valid responses through online structured questionnaires targeting users of land transportation services, such as buses, trains, and ride-hailing platforms in Jakarta, Bandung, and Surabaya. The sampling was purposive, involving users with prior experience using digital transportation apps. The data were analyzed using Structural Equation Modeling - Partial Least Squares (SEM-PLS). The findings indicate that system quality and information quality significantly influence brand experience, which in turn affects user engagement. Furthermore, user engagement plays a crucial role in enhancing the resilience of the digital community ecosystem. The study confirms that brand experience partially mediates the effect of system and information quality on engagement. Implications of the study emphasize the importance for transportation providers to prioritize high-quality, user-centric digital services that foster emotional connection and trust, which are essential to sustaining adaptive and resilient community platforms in the face of urban transportation challenges.

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