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Information Technology Readiness and Acceptance Model for Social Media Adoption in Blended Learning: A Case Study in Higher Education Institutions in West Java, Indonesia Yusuf, Fahmi; Rahman, Titik Khawa Abdul; Subiyakto, Aang
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.195

Abstract

Technological developments, including the internet, and learning opportunities are increasing. This also encourages the development of learning strategies and models. The blended learning model is applied in almost all universities in Indonesia and the world. With so many universities in Indonesia, implementing blended learning is a challenging thing because it requires a lot of technological preparation and human resources. This research aims to identify factors, develop a model, and evaluate the model to see the readiness and acceptance of technology for adopting social media in blended learning among private higher education institutes students in Indonesia. The population of this research is students from private higher education institutes in West Java, Indonesia, who are directly involved in using blended learning and social media. This quantitative research used a research instrument with five-Likert’s scale. The research population was 663,307, with a sample of 384 students spread across West Java. The contribution of this research is to make a significant contribution to the theoretical framework by expanding and refining existing concepts, providing a more comprehensive understanding of the readiness and acceptance factors for the adoption of social media in blended learning so that it has the potential to provide information to learning planners at private higher education institutes in West Java, Indonesia to help make the right decisions and optimize blended learning planning using social media technology. These findings statistically explain that 19 of 31 the hypotheses are the accepted ones. Moreover, nine of 12 variables influenced the readiness and acceptance of social media technology in blended learning based on the student perception among the private higher education institutions. They were the technological literacy factor, perceived validity, perceived trust, and technology readiness factors, namely optimism and Innovativeness, and technology acceptance factors, namely perceived effectiveness, perceived easy to use, intention to use and usage behaviour.
Enhancing Abstractive Multi-Document Summarization with Bert2Bert Model for Indonesian Language Muharam, Aldi Fahluzi; Gerhana, Yana Aditia; Maylawati, Dian Sa'adillah; Ramdhani, Muhammad Ali; Rahman, Titik Khawa Abdul
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.110-121

Abstract

This study investigates the effectiveness of the proposed Bert2Bert and Bert2Bert+Xtreme models in improving abstract multi-document summarization for Indonesians. This research uses the transformer model to develop the proposed Bert2Bert and Bert2Bert+Xtreme models. This research uses the Liputan6 data set which contains news data along with summary references for 10 years from October 2000 to October 2010 and is commonly used in many automatic text summarization research. The model evaluation results using ROUGE-1, ROUGE-2, ROUGE-L, and BERTScore show that the proposed model has a slight improvement over previous research models, with Bert2Bert being better than Bert2Bert+Xtreme. Despite the challenges posed by limited reference summaries for Indonesian documents, content-based analysis using readability metrics, including FKGL, GFI, and Dwiyanto Djoko Pranowo, revealed that the summaries produced by Bert2Bert and Bert2Bert+Xtreme are at a moderate readability level, meaning they are suitable for mature readers and aligns with the news portal's target audience.
Evaluating Readiness and Acceptance of Artificial Intelligence Adoption Among Elementary School Teachers Darmawan, Erlan; Rahman, Titik Khawa Abdul; Thamrin, Nani Ronsani
JOIN (Jurnal Online Informatika) Vol 9 No 2 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i2.1385

Abstract

Artificial Intelligence (AI) is a computer system that mimics the human brain's ability to process information and make decisions. AI technology is used to learn patterns in data and make predictions or decisions based on that learning. Despite the potential benefits of AI in education, elementary school teachers face significant challenges in adopting AI technology due to limited training, lack of resources, and resistance to change. This research aims to identify the factors influencing the adoption of AI technology among primary school teachers in West Java, Indonesia. The study involved 384 participants and employed a quantitative approach. Specific factors influencing AI adoption were identified by developing a model for AI-based teaching and learning and assessing readiness factors. The results identified optimism, innovativeness, insecurity, discomfort, perceived validity, trust, usefulness, and ease of use as critical factors for successful AI adoption among primary school teachers in West Java. The customized adoption model provides a practical roadmap for integrating AI into teaching and learning processes, addressing regional specificities while remaining relevant to similar educational challenges worldwide. The assessment of readiness factors offers actionable insights for fostering a supportive environment for technology integration. The study concludes with recommendations for future research and implications for educators, administrators, and policymakers.
Contextualizing Procurement Maturity: Lessons from Government Procurement for Enhancing Regional-Owned Enterprise (BUMD) Performance Sutisna, Nandang; Rahman, Titik Khawa Abdul; Bin Mansor, Shazali
International Journal of Multidisciplinary Approach Research and Science Том 3 № 02 (2025): International Journal of Multidisciplinary Approach Research and Science
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v3i02.1568

Abstract

Procurement governance represents a strategic function critical to the success of public organizations, particularly Regional-Owned Enterprises (BUMDs), which operate under hybrid mandates combining public service delivery and market competitiveness. This study critically examines the applicability of the Indonesia Procurement Maturity Model (IPM2) to BUMDs and proposes an adapted conceptual framework better suited to their unique governance complexities. Through analytical deconstruction, the study finds that while elements such as transparency, accountability, and technology utilization in IPM2 are directly adoptable, significant adjustments are necessary in organizational structures, competency frameworks, and risk management approaches. Rigid elements tied to governmental budget cycles and inspectorate-driven oversight are deemed incompatible with BUMD operational realities. An adapted maturity model is proposed, positioning procurement as a strategic enabler supported by five interconnected adaptive dimensions: Strategic Human Capital Development, Agile Institutional Structures, Performance-Driven Management Systems, Strategic Technological Integration, and Proactive Risk and Opportunity Management. Grounded in contingency theory and contemporary hybrid governance literature, the model reframes procurement maturity as a dynamic, value-driven system rather than a linear, compliance-oriented progression. This research offers both a practical roadmap for BUMDs and a conceptual contribution to the evolving field of procurement governance in hybrid public organizations.
Machine learning-based B2C software project success prediction model in Indonesia Setiawan, Rudi; Rahman, Titik Khawa Abdul
International Journal of Advances in Intelligent Informatics Vol 11, No 3 (2025): August 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i3.2123

Abstract

The success of a software project is a crucial factor in the information technology industry, but it is often difficult to predict due to its complexity and high dynamics. This research aims to develop a model for predicting the success of software projects, particularly B2C e-business software in Indonesia, utilizing a machine learning approach. This study involved 28 variables that affect the success of software projects obtained from previous research. The dataset was compiled from the historical records of software projects from various software development companies in Indonesia. The predictive model was developed using Support Vector Machine and Artificial Neural Network algorithms, with hyperparameter tuning performed via Grid Search. The modelling process includes the pre-processing stage of data, which involves synthetic data generation due to inadequate data collection, as well as the application of several dataset mining techniques (SMOTE, ADASYN, SMOTE Tomek Links, and ADASYN Tomek Links). Additionally, model training and performance evaluation are conducted using a confusion matrix. The search for important features using the Shapley Additive Explanations method is also conducted to develop an automated recommendation system based on key factors that require improvement. The results showed that the SVM model with Grid Search tuning of hyperparameters in the SMOTE Tomek Links data test yielded the best performance, with an accuracy of 87.8%, demonstrating the significant potential of machine learning in identifying project success factors from the early stages. This study contributes to the development of decision-support tools for B2C project managers in Indonesia by providing accurate early predictions and interpretable recommendations.
Quantitative Analysis of the Key Factors Driving Cybersecurity Awareness Among Information Systems Users Helmiawan, Muhammad Agreindra; Firmansyah, Esa; Herdiana, Dody; Akbar, Yopi Hidayatul; Subiyakto, A’ang; Rahman, Titik Khawa Abdul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4861

Abstract

Cybersecurity threats are increasingly complex and widespread, posing significant risks to individuals and organizations. However, many studies tend to address the technological or behavioral aspects separately. The study uses a survey-based quantitative approach using PLS-SEM to analyze key factors that influence cybersecurity awareness, including demographics, training, psychological bias, and organizational culture. The findings suggest that several constructs-such as threat awareness, perceived risk, and education-significantly predict cybersecurity awareness and behaviour. Notably, the model yields an R² value of up to 0.703 with a strong path significance (p < 0.05), which underscores the robustness of the relationship. This study offers an integrated perspective on cybersecurity by bridging the psychological, educational, and organizational dimensions. It highlights cybersecurity awareness as a mediating construct that links upstream factors to secure user behavior-a relational structure that has not been explored in previous research.