Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal ADI Bisnis Digital Interdisiplin (ABDI Jurnal) International Transactions on Education Technology (ITEE)
Zulfadli Ardiansyah
IPB University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Impact of Digital Content Marketing Strategies on Perceived Usefulness and VALORANT Game Acceptance Nengah Sukendri; Zulfadli Ardiansyah; Agung Rizky; Asri Asri; Henry Zainarthur
ADI Bisnis Digital Interdisiplin Jurnal Vol 6 No 2 (2025): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v6i2.1335

Abstract

In the digital gaming industry that is becoming increasingly competitive, content marketing strategies play a crucial role in shaping players’ perceptions of a game’s quality and usefulness while influencing their decision to adopt it. As one of Riot games’ most prominent titles, VALORANT faces market dynamics that require digital marketing strategies that are informative, engaging, and sustainable. This study aims to analyze the influence of digital content marketing strategies on perceived usefulness and game acceptance using the Technology Acceptance Model (TAM) framework. The research employs a quantitative approach through an online survey of active VALORANT players, and the data are analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine causal relationships within TAM. The findings reveal that digital content marketing strategies have a significant positive effect on perceived usefulness, while Perceived Ease of Use (PEOU) also enhances Perceived Usefulness (PU) and overall game acceptance. Relevant and consistent content strengthens players’ perceived value, whereas ease of use supports a more comfortable and enjoyable gaming experience. This study highlights that strong digital content marketing strategies combined with a user-friendly game design are key factors in increasing player acceptance and engagement. The findings offer essential insights for developers and marketers in formulating effective content strategies to expand adoption, boost retention, and sustain the game’s community ecosystem.
Evaluating Machine Learning Techniques for Performance Monitoring and Continuous Improvement in Learning Factory Education Elika Setiawaty; Rifqa Nabila Muti; Kristina Vaher; Zulfadli Ardiansyah; Marta Rodriguez
International Transactions on Education Technology (ITEE) Vol. 4 No. 1 (2025): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v4i1.959

Abstract

The rapid advancement of data-driven technologies has transformed the landscape of educational innovation, particularly within learning factory environments that simulate real industrial settings for experiential learning. This study aims to evaluate the effectiveness of various machine learning techniques in monitoring student performance and facilitating continuous improvement in the learning process. Using a quantitative approach, data were collected from student activities, production logs, and performance metrics within a university-based learning factory over one academic term. Several machine learning algorithms, including Decision Tree, Random Forest, and Support Vector Machine, were applied to predict student performance levels and identify critical factors influencing learning efficiency. The analysis revealed that ensemble based models, especially Random Forest, achieved the highest prediction accuracy and provided valuable insights into performance trends, enabling proactive instructional interventions. Additionally, the integration of predictive analytics contributed to improved feedback mechanisms and optimization of task allocation, fostering both individual and group learning outcomes. The findings highlight the significant potential of machine learning in enhancing performance monitoring systems and promoting data informed decision-making in educational manufacturing contexts. This study concludes that the strategic adoption of machine learning techniques can substantially strengthen the feedback loop between learners and instructors, leading to more adaptive, efficient, and sustainable learning processes within the learning factory framework.
Co-Authors Agung Rizky Asri Asri Elika Setiawaty Henry Zainarthur Kristina Vaher Marta Rodriguez Nengah Sukendri Rifqa Nabila Muti