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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 227 Documents
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Development of a User-Personalized Decision Support System for Contraception Method Selection Karami, Ahmad Fahmi; Ekawati, Rany; Marier, Syauqi Muhammad; Susantini, Purwanti
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.44648

Abstract

The number of unmet needs for contraception has not reached the target set by the Indonesian government, while the uneven distribution of health workers, the main source of information for contraception, is still an unresolved problem. The Internet serves as an alternative source of information for contraception selection. However, without personalization, it may lead to inappropriate choices. This study discussed the development of an information system for selecting contraceptives, incorporating a decision support system (DSS), enabling personalized recommendations based on user preferences to assist in determining the appropriate contraceptive method. The functionality of the information system was evaluated using black-box testing, conducted by reproductive health experts, while its usability was assessed based on ISO-9241-11:2018 standards with 25 respondents. The functional evaluation of the system showed that 14 functions successfully passed the testing procedures, while 2 functions failed. The usability evaluation yielded excellent results, with an overall score of 4.52. Based on these findings, the developed information system can serve as a medium for reducing the number of unmet needs for contraception by providing users with contraceptive information tailored to their preferences. Further research needs to enhance system information by integrating user medical reports and user location and evaluating the recommendation-to-selection conversion rate— the extent to which users follow the system’s recommendations when choosing contraceptives.
Critical Success Factors for IT Risk Management in the Digital Transformation Era: Insights from a Multiple Case Study Yuniarto, Dwi; Rahman, Aedah Binti Abd.
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.41090

Abstract

The convergence of Information Technology risk management and digital transformation is a vital consideration for contemporary organizations navigating the rapidly changing digital landscape. This research investigates the intersection of these domains, aiming to identify the critical success factors that enable effective Information Technology risk management within the context of digital transformation. Through a Systematic Literature Review, a comprehensive search on Web of Science and Scopus led to the acceptance of 61 peer-reviewed papers published between 2020 and 2024, providing a solid foundation for understanding current trends and best practices. Employing a qualitative multiple case study approach, this study examines the experiences, strategies, and challenges of organizations that have successfully managed Information Technology risks during their digital transformation journeys. Thematic analysis reveals three key critical success factors: executive leadership and support, cross-functional collaboration, and risk-aware decision-making. These findings offer actionable insights for organizations seeking to align their risk management practices with the complexities of digital transformation. By bridging theoretical frameworks with practical insights, this research provides valuable recommendations for organizations to navigate digital transformation securely. Future research could focus on exploring the implementation nuances of these success factors across various industries, such as healthcare, finance, and manufacturing, to deepen our understanding of the intricate relationship between IT risk management and digital transformation in diverse contexts.
A Comparative Study of Machine Learning Models for Fashion Product Demand Prediction: Exploring Algorithms, Data Splitting, and Feature Engineering Mardiah, Reviana Siti; Fitrianingsih, Fitrianingsih
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.45600

Abstract

The fashion industry faces challenges in accurately predicting demand due to inherent uncertainty, leading to suboptimal inventory and financial losses. Machine learning (ML) offers a robust solution by analyzing large and complex data, identifying non-linear patterns, and providing more accurate predictions than conventional methods that rely on limited factors.  This research aims to compare and evaluate the performance of six different ML models—XGBoost, SVM, RF, GBM, KNN, and NN, considering the influence of feature engineering and various data split ratios on predicting fashion product demand. KNN and NN were included due to distinct modeling approaches and competitive capabilities in identifying local and non-linear patterns across numerical, categorical, and time series data.  Techniques such as feature extraction and selection and various data split ratios (70:30, 80:20, 90:10) were used.  Using Adidas sales data, the models were evaluated based on Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results indicate that the XGBoost-based model with feature engineering consistently outperforms the other models across all data split ratios. Particularly, XGBoost with feature engineering at a data split ratio of 90:10 achieved the best performance with an RMSE of 4.46 and an MAE of 1.51. Analyzing model performance shows that the predictive ability of ML models is influenced by the implementation of feature engineering and the selection of the data split ratio. These results demonstrate the potential of using feature-engineered XGBoost models and optimized data ratios to mitigate the risk of stockouts or overstocks, and reduce financial losses and environmental waste.
Assessing the Acceptance and Trust in Student Information Systems Through a Modified TAM Perspective Hidayat, Muhammad Taufik Nur; Hariguna, Taqwa; Saputra, Dhanar Intan Surya
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.42324

Abstract

The rapid development of information technology has motivated universities to implement technology-based student information systems to enhance the efficiency and effectiveness of student data management. This research seeks to evaluate acceptance and trust in student information systems at universities using a modified version of the Technology Acceptance Model, incorporating perceived trust as an additional variable. The study involved a sample of 200 active university students, with data analyzed using the structural equation modeling approach. Findings from the analysis show that both perceived usefulness and perceived ease of use significantly impact students’ intention to adopt the system, which in turn influences actual system usage. Additionally, perceived trust emerged as a critical factor in reinforcing both the intention to use and the subsequent actual use of the student information system. The results indicate that the intention to use the system acts as an essential mediator in the relationships between students’ perceptions of usefulness, ease of use, trust, and their actual usage behavior. These results have significant implications for universities aiming to improve the adoption of student information systems. Enhancing user experience, building system trust, and ensuring robust security should be prioritized in the development and refinement of such systems. By focusing on these aspects, institutions can foster higher acceptance and sustained usage, leading to more effective student data management and a better overall educational experience.
Analysis and Design of Inventory Management Information Systems at PT. XYZ Kumaladewi, Nia; Firdaus, Ryan Faatih
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.42602

Abstract

This study aims to analyze and design an Inventory Management Information System (IMIS) for PT. XYZ, a company that currently relies on manual inventory processes, leading to inefficiencies and operational delays. To address these challenges, the IMIS was developed using the Rapid Application Development (RAD) methodology, which followed three key stages: requirements planning, design workshop, and implementation. In the requirements planning stage, comprehensive user needs and system specifications were gathered. During the user design phase, iterative prototyping and continuous feedback sessions helped refine the system’s interface and functionalities. The rapid construction phase saw the development of core features—such as real-time inventory tracking, automated restocking alerts, and detailed transaction histories—using PHP, HTML, JavaScript, and MySQL. Finally, in the cutover phase, pilot testing demonstrated that the system reduced material search times from 15–30 minutes to nearly instantaneous retrieval, significantly improving inventory accuracy and overall operational efficiency. Further research is needed to evaluate its long-term performance and scalability. This study not only highlights the practical advantages of the RAD-based approach but also offers a promising model for organizations seeking to modernize their inventory management practices. 
Integrating Artificial Intelligence in Human Resources Management: A Bibliometric Analysis of Emerging Trends and Influences Baskara, Dwi Soca; Gunadi, Suyud; Muttaqin, Nabil
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.40352

Abstract

This study aims to analyze the integration of Artificial Intelligence (AI) in the field of Human Resource Management (HRM) from 2004 to 2024. By measuring productivity, impact, collaboration and research topics, this research tracks the development of the domain. These findings may provide a foundation for future research on the growth of AI-focused HRM research, lead authors, institutions, and emerging themes. Using the Scopus database, 381 relevant documents were identified and analyzed, showing an increase in publications year on year, with significant growth between 2020 and 2023. This shows the transformative impact of AI on HRM. This analysis reveals rapid growth and international collaboration in AI-enabled HRM research, demonstrating significant potential. Future research could explore specific applications of AI, ethical considerations, and long-term impacts on HRM practices.
Implementation of Bidirectional Long Short-Term Memory and Convolutional Neural Network in Detecting Hoax Content on Social Media Lantang, Oktavian A.; Sendow, Raphael Edber Christopher; Kambey, Feisy Diane
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.45222

Abstract

The advancement of internet technology has facilitated the spread of information, including false information or fake news. The dissemination of hoaxes on social media, such as Twitter, can cause confusion and negatively impact society. This study aims to implement a hybrid model that combines Bidirectional Long Short-Term Memory (Bi-LSTM) and Convolutional Neural Network (CNN) for hoax detection. The dataset used consists of English tweets containing both real and fake news, collected between 2020 and 2022, as provided by the TruthSeeker dataset. The model utilizes an embedding layer with word2vec, a Conv1D layer, and a BiLSTM layer to effectively capture temporal and spatial patterns in text data. Additionally, experiments were conducted by varying the number of BiLSTM units and CNN filters to analyze their impact on model performance. After conducting parameter experiments, the best results were achieved using a Conv1D layer with 64 filters and a BiLSTM layer with 64 neurons/units. The evaluation results on the test data indicate an accuracy of 96.14%, a precision of 96%, a recall of 96.25%, and an F1-score of 96%. These results demonstrate the model's high capability in accurately detecting hoaxes, which is significant for combating misinformation on social media. With its strong performance, the model has potential applications in real-time content moderation systems, early hoax detection tools, and digital literacy platforms to help reduce the spread of false information.
Enhancing Repeat Buyer Classification with Multi Feature Engineering in Logistic Regression Mauludiah, Siska Farizah; Crysdian, Cahyo; Arif, Yunifa Miftachul
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.45025

Abstract

This study presents a novel approach to improving repeat buyer classification on e-commerce platforms by integrating Kullback-Leibler (KL) divergence with logistic regression and focused feature engineering techniques. Repeat buyers are a critical segment for driving long-term revenue and customer retention, yet identifying them accurately poses challenges due to class imbalance and the complexity of consumer behavior. This research uses KL divergence in a new way to help choose important features and evaluate the model, making it easier to understand and more effective at classifying repeat buyers, unlike traditional methods. Using a real-world dataset from Indonesian e-commerce with 1,000 records, divided into 80% for training and 20% for testing, the study uses logistic regression along with techniques like SMOTE for oversampling, class weighting, and regularization to fix issues with data imbalance and overfitting. Model performance is assessed using accuracy, precision, recall, F1-score, and KL divergence. Experimental results indicate that the KL-enhanced logistic regression model significantly outperforms the baseline, especially in balancing precision and recall for the minority class of repeat buyers. The unique contribution of this work lies in its synergistic use of KL divergence in both the feature engineering and evaluation phases, offering a robust, interpreted, and data-efficient solution. For e-commerce businesses, the findings translate into improved targeting of high-value customers, better personalization of marketing efforts, and more strategic allocation of resources. This research offers practical tips for enhancing predictive customer analytics and supports data-driven decision-making in digital commerce environments.
Evaluation of The Orthopedic Hospital Website's Performance Using User Acceptance Testing Setyadi, Resad; Rahman, Aedah Abd.; Anwar, Toni
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.42951

Abstract

User Acceptance Testing (UAT) is essential for ensuring a system meets the real-world needs of its users. Unlike traditional testing that prioritizes technical accuracy, UAT focuses on usability and overall user satisfaction. For the Orthopedic Hospital's website, UAT served as the primary evaluation method, targeting its core user groups—patients, staff, and stakeholders. The testing process followed the ISO 9126 software quality standards, evaluating the website across key dimensions such as functionality, reliability, usability, efficiency, maintainability, and portability. A Likert scale was used to capture structured user feedback, providing quantifiable insights into user perceptions. This combined approach allowed for a well-rounded assessment, balancing technical quality with user experience. Results indicated a high satisfaction rate of 92.7%, reflecting strong approval of the website’s design and functionality. However, the evaluation also pointed to areas for enhancement. The online registration process, for example, could be simplified to improve ease of use and task completion. While the results are promising, continued improvement is vital—especially in healthcare, where user experience directly affects patient outcomes and service efficiency. To maintain alignment with evolving user needs and technologies, ongoing UAT cycles should be integrated into the hospital’s digital strategy. Leveraging ISO 9126 standards and user-centered tools like the Likert scale will ensure the website remains effective, accessible, and responsive to its users.
Design and Analysis of a Flutter-Based Mobile Application for Palm Oil Monitoring Hannan, Ananda Rahmatul; Sopandi, Ajang; Firdaus, Ali; Kurniawan, Arif; Rusdianto, Hengki
Applied Information System and Management (AISM) Vol 8, No 1 (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.v8i1.41277

Abstract

In the current era of digital transformation, it is essential to modernize data processing systems to improve operational efficiency and competitiveness across industries. However, PT Agro Sawit Musi Rawas still relies on outdated manual processes, resulting in reporting delays, inaccurate data, and difficulties in real-time performance monitoring. Therefore, the aim of this research is to design a comprehensive monitoring system specifically tailored to meet the unique operational needs of PT Agro Sawit Musi Rawas. The system criteria were identified through methods such as observations, interviews, and literature reviews, which provided valuable insights into the company’s specific challenges and requirements. The system design incorporates data collection and analysis using the URS (User Requirement Specification) and UML (Unified Modeling Language) frameworks, ensuring it addresses the identified needs effectively. The design and analysis follow a structured and systematic process to develop an information monitoring system that enhances transparency, operational effectiveness, and efficiency. The findings reveal that the implementation of the proposed system can significantly improve reporting speed, data accuracy, and real-time monitoring capabilities. By adopting this monitoring system, PT Agro Sawit Musi Rawas can optimize reporting processes, facilitate real-time performance monitoring, and ultimately strengthen its competitive market position.

Page 13 of 23 | Total Record : 227

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