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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 306 Documents
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The Influence of Video Marketing and Digital Storytelling on Perceived Increase in Consumer Purchase Intention through Brand Engagement: A Study on MSMEs Frans Sudirjo; Suherlan; Moses Odhiambo Okombo; Syamsuri
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.46698

Abstract

This study investigates the influence of video marketing and digital storytelling on consumer purchase intention through brand engagement among MSMEs in Jakarta. The research is grounded in the Theory of Planned Behavior (TPB) and Customer Engagement Theory, which together provide the conceptual framework for understanding how visual and narrative-based digital content affects consumer attitudes, engagement, and behavioral intention. The study is driven by real-world challenges faced by MSMEs, particularly the widespread use of video and storytelling content that often fails to generate meaningful engagement or improve sales due to limited emotional depth, weak narrative authenticity, and low digital literacy among business actors. Using a quantitative approach and SEM–PLS analysis on data obtained from 100 MSME respondents, the findings reveal that both video marketing and digital storytelling significantly enhance brand engagement. However, only video marketing shows a significant direct effect on purchase intention, while digital storytelling demonstrates no significant impact and even indicates a negative tendency. Additionally, brand engagement does not serve as a significant mediator for either content strategy. These results highlight that exposure to video or narrative content alone is insufficient without strong contextual relevance and emotional resonance. The study contributes to the development of TPB and Customer Engagement Theory by showing that engagement and intention require deeper psychological processes beyond content exposure and provides practical insights for MSMEs to produce more authentic, emotionally compelling, and culturally aligned digital content. 
Development of an ORMAWA Work Program Management Information System Using a User-Centered Design Approach Muhammad Helmi; Mohammad Reza Faisal; Friska Abadi; Dodon Turianto Nugrahadi; Setyo Wahyu Saputro; Deni Sutaji
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.46734

Abstract

Student organizations (ORMAWA) at the Faculty of Mathematics and Natural Sciences, Universitas Lambung Mangkurat, face significant challenges in managing their work programs manually. This reliance on paper-based processes and decentralized record-keeping leads to chronic delays, documentation errors, and difficulties in tracking accountability. These issues severely hamper efficient coordination with faculty administrators, complicating timely decision-making and budget monitoring. The primary aim of this research is to develop and implement a web-based work program management information system for ORMAWA using a User-Centered Design (UCD) approach. Specific objectives include providing a centralized digital platform for program submission, approval, and reporting, and significantly enhancing the administrative efficiency and accountability of the entire workflow. The research methodology involved requirements gathering, iterative system design, and implementation using the React JS and Laravel frameworks. Evaluation was conducted through black box testing and User Acceptance Testing (UAT) with 13 ORMAWA administrators. Results demonstrate high user satisfaction (85%) and a substantial 30% efficiency improvement in program submission and reporting processes. The UCD approach was crucial in delivering a system that successfully eliminated redundant administrative tasks and centralized documentation. This study contributes to the application of UCD in developing organizational management systems in higher education, demonstrating how technology can transform traditional administrative workflow.
Brand Experience and Brand Loyalty Relationship: A Study Under Attribution Theory Perspective Shely Rizki Hardiana; Muhamad Ridwan
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.46750

Abstract

Research on coffee shop brand loyalty has largely focused on factors like self-congruity, brand equity, and brand trust, while the role of brand experience remains underexplored. Moreover, its link to multidimensional loyalty outcomes and attribution theory has received little attention, especially in emerging markets. This study investigates how brand experience influences brand loyalty dimensions—willingness to pay more (WTPM), word-of-mouth recommendations (WOM), and repurchase intention (RI)—within Indonesian coffee shop brands, using attribution theory to explain the mechanisms. A quantitative approach was used, with 246 Indonesian coffee shop consumers completing a questionnaire. To confirm the assumptions, we applied partial least squares structural equation modeling (PLS-SEM). The findings reveal that brand experience significantly enhances all three factors of brand loyalty: WTPM, WOM, and RI. The research provides a theoretical foundation for understanding how brand experience affects customer loyalty, suggesting future studies could explore similar relationships in other cultural and market contexts. For coffee shop owners, the findings emphasize the need to enhance brand experience through sensory, emotional, and intellectual engagements. Tailoring environments for intellectual activities can help differentiate brands in a competitive market. The study emphasizes how coffee shops serve as social and intellectual hubs. By fostering such environments, coffee shops can enhance their value, offering spaces for cognitive engagement and social interaction.
Assessing ERP Adoption Determinants in Oil Palm Plantations Using UTAUT2 and SEM Evidence from PT Menthobi Makmur Lestari Bimantoro Suryo Budi Sudibyo; Evi Triandini; Dadang Hermawan
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.46793

Abstract

The palm oil plantation industry in Indonesia still faces challenges in efficiency, resource management, and operational sustainability. To overcome these challenges, Enterprise Resource Planning (ERP) systems offer integrated solutions. However, their adoption is often hindered by organizational and individual barriers. This study investigates the factors influencing ERP adoption at PT. Menthobi Makmur Lestari is using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. Data were collected from 88 respondents, including managers and staff actively engaged with ERP systems, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings reveal that price value, facilitating conditions, and performance expectancy significantly and positively affect behavioral intention, which in turn drives actual system usage. Moderation analysis of age, gender, and Experience showed minimal influence, indicating that demographic characteristics play a limited role in shaping ERP adoption behavior. Instead, organizational support, infrastructure availability, and perceived economic benefits emerged as the dominant enablers of ERP adoption. The findings highlight the critical role of management strategies, training, and system alignment with employee tasks in ensuring successful ERP implementation. The study concludes that ERP adoption in palm oil companies is more strongly determined by organizational readiness than by individual differences. 
Food Recommendations to Support Unsold Food Marketplace Using Content-Based Filtering Susana Limanto; Liliana; Fenny Cahyawati; Daniel Soesanto; Maya Hilda Lestari Louk; Heru Arwoko
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.47114

Abstract

Unsold food is food that has a short shelf life, is intended to be sold, and is still edible. Based on survey results, business owners usually resell unsold food at a discounted price via WhatsApp or posters placed in front of the shop or distribute it to the surrounding community. Meanwhile, consumers buy unsold food by visiting the shop directly. Unsold food promotions via WhatsApp or posters do not reach the wider community. Meanwhile, direct purchases limit the opportunity to buy unsold food from several sellers simultaneously and increase the risk of stockouts, which can lead to wasted food and missed savings for consumers. This study aims to develop an unsold food marketplace integrated with two key features: bargaining and recommendations. Recommendations are generated using content-based filtering with cosine similarity to measure the similarity between the user's purchase history and each unsold food item. The recommendation feature's findings reveal that content-based filtering generates recommendations more in line with user preferences than popularity-based ones. Validation results confirm this finding, demonstrating 100% accuracy in matching the recommended food categories with the ones users have purchased. Meanwhile, during the marketplace validation stage, 15 respondents reported strong acceptance, with average scores of 4.67 out of 5 for usefulness and 4.71 out of 5 for usability. This study highlights how an unsold food marketplace supports consumers with limited budgets, reduces food waste, and increases seller revenue, while its bargaining and recommendation features enhance user satisfaction and engagement, thereby achieving mutual benefits.
Artificial Intelligence Integration Strategy in Management Information Systems: A Case Study of Micro, Small, and Medium Enterprises Emi Sita Eriana; Asep Erlan Maulana
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.47193

Abstract

Digital transformation through the integration of Artificial Intelligence (AI) technology into Management Information Systems (MIS) has become an urgent need for Micro, Small, and Medium Enterprises (MSMEs). The MSME sector in Indonesia plays a vital role in the national economy but faces significant challenges, including limited access to capital and technology. This study aims to develop an effective AI integration strategy to improve MSME operational efficiency. Using a mixed-methods approach combining exploratory and descriptive designs, this study involved 30 MSMEs from various sectors selected through purposive sampling. Data were collected through structured questionnaires, semi-structured interviews, and direct observation, and then analyzed using descriptive statistics, regression analysis, and thematic analysis. The results reveal a paradox: 85% of MSMEs show strong enthusiasm for AI technology while simultaneously facing implementation barriers. A significant gap exists between infrastructure readiness (40%) and human resource readiness (25%). Five critical success factors were identified: human resource readiness (35%), technology infrastructure (25%), financial support (20%), management commitment (15%), and the digital ecosystem (5%). MSMEs that successfully implemented AI achieved operational efficiency improvements of up to 30% and ROI within 12–18 months. This study produced the "MSME-AI Integration Framework" as a practical guide for phased implementation. Strategic recommendations include a phased implementation approach, ongoing digital training programs, government support, and partnerships with technology providers for affordable AI solutions. 
Evaluation of The Performance of Learning Management System Using IS Success Model Reni Haerani; Feby Charlos; Angga Pramadjaya
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.47325

Abstract

Learning Management Systems (LMSs) have become a crucial element in digital learning at universities. However, not all LMSs demonstrate optimal implementation results. The urgency of this study arises from the need to ensure that the implemented LMS truly has a positive impact on the educational process, enhances the effectiveness of learning interactions, and increases user satisfaction. This study aimed to assess the effectiveness of LMS using the Information System Success Model (ISSM) proposed by Delone and McLean through a quantitative Partial Least Squares–Structural Equation Modeling (PLS-SEM) approach. The variables analyzed included system quality, information quality, service quality, user satisfaction, system usage, and net benefits. The study's population comprised 548 LMS users from universities in Banten Province, including instructors and students who were active in the previous semester. Data were collected through questionnaires distributed via Google Forms and analyzed descriptively and quantitatively using SmartPLS 3.0 software to test the outer and inner models. The results of the study revealed that of the 10 hypotheses tested, 6 were accepted and 4 were rejected. The main findings indicate that system quality and service quality have a positive impact on intention to use and user satisfaction. These findings provide practical contributions for LMS managers in formulating steps to improve system quality, as well as theoretical contributions in developing models to evaluate the success of information systems in education.  
Understanding Online Purchase Intention in Social Commerce: The Roles of Web Quality, User Satisfaction, and Algorithmic Personalization Megi Nediawan; Asrid Juniar; Liko Noor Rafianto Rahadian; Muhammad Rayyan Adhiyani; Nasywa Ghaida Salsabila; Paarth Agarwal
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.48916

Abstract

This study examines how web quality influences online purchase intention through user satisfaction in social commerce, with a specific focus on TikTok Shop. Drawing on the WebQual 4.0 framework and expectation-confirmation theory, the research investigates the effects of usability quality, information quality, and service interaction quality on user satisfaction and how satisfaction subsequently drives online purchase intention. Extending prior WebQual research, this study integrates algorithmic personalization as a moderating mechanism that strengthens the satisfaction–online purchase intention relationship, addressing an aspect largely overlooked in existing social commerce studies. Data were collected from 210 TikTok Shop users in Banjarmasin and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that all web quality dimensions significantly enhance user satisfaction, which in turn positively affects online purchase intention. Algorithmic personalization significantly reinforces this relationship, and the model explains 44.6% of the variance in online purchase intention (R² = 0.446). The findings contribute to theory by extending WebQual to algorithm-driven social commerce contexts and offer practical insights for platforms seeking to optimize user experience and personalized recommendation strategies.
Mapping Theories, Digital Predictors, and Asian Dominance in Green Purchase Intention Research Elisa Elisa; Sarwo Edy Handoyo; Haris Maupa
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.49260

Abstract

Despite growing environmental awareness, consumers often fail to translate this interest into actual green purchases. This systematic review maps the theoretical and empirical evolution of green purchase intention research during the period of rapid digital transformation from 2020 to 2025. This study follows PRISMA guidelines and analyzes 56 empirical studies from five major academic databases, including Scopus and ScienceDirect. The analysis focuses on publication trends, geographical distributions, theoretical frameworks, and key predictors. The review reveals a significant geographical concentration of research in Asia, particularly China, India, and Vietnam, while studies from Western contexts remain limited. Theoretically, while the Theory of Planned Behavior remains the dominant framework, the Stimulus-Organism-Response model is gaining traction as researchers increasingly explore digital contexts. Key findings indicate that attitude and green trust are the most consistent psychological predictors, while social media influence has emerged as a powerful external stimulus. This review is timely, as it captures how digital marketing factors have reshaped traditional behavioral models in the post-2020 period, a shift that earlier reviews did not address. The main contributions include: (1) documenting the paradigm shift from static behavioral models to dynamic, digitally-integrated frameworks; (2) identifying the most robust predictors across diverse contexts; and (3) examining the implications of the geographical research concentration for global theory development. The study concludes by recommending that future research prioritize longitudinal designs, cross-cultural comparisons, and investigations into digital platform features to understand better how green intentions translate into actual sustainable consumption behaviors across different cultural and institutional contexts.  
Predicting Consumer Purchase Intention in Informal Retail Using Machine Learning and the Purchase Intention Probability Index (PIPI) Gatot Tri Pranoto; Yoga Religia; Dwi Pebrianti
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): 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.v9i1.49459

Abstract

Informal retail remains a growing and predominant form of shopping for many people. However, modern and well-organized supermarkets, using data-driven approaches to attract consumers, have increasingly challenged informal retailers in recent years. This phenomenon presents new challenges, particularly in predicting consumers' purchase intentions given limited, unstructured, and poorly documented data. Therefore, this study aims to develop and evaluate a predictive model for consumer purchase intention in informal retail using machine learning techniques and to introduce the Purchase Intention Probability Index (PIPI) as a probability-based aggregation approach to enhance predictive sensitivity. The study uses the Subsistence Retail Consumer Dataset from Mendeley Data, comprising 281 consumer records with 38 demographic, behavioral, and psychological attributes, with purchase intention as the binary target variable. Three widely used classification algorithms in consumer behavior research (decision tree, random forest, and support vector machine (SVM)) were employed to identify purchase-predictive patterns in the data. Based on these models, the PIPI was developed, which aggregates the highest probabilities from all three models to produce more robust predictions, particularly for small and heterogeneous datasets, and supports cross-model performance evaluation. The results show that the proposed PIPI method achieves the highest recall (1.00), outperforming individual classifiers in detecting purchase intention. This fact indicates that informal retailers can apply machine-learning-based analytics to improve marketing effectiveness and decision-making without requiring advanced technological infrastructure. 

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