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All Journal Jurnal Multidisiplin West Science EDUJAVARE: International Journal of Educational Research Journal of Computer Science Advancements
Aini, M. Anwar
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Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Bridging the Digital Divide: Ensuring Equitable Access to Education Technology Aini, M. Anwar
EDUJAVARE: International Journal of Educational Research Vol. 3 No. 1 (2025): EDUJAVARE: International Journal of Educational Research
Publisher : CV. Edujavare

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/edujavare.v3i1.800

Abstract

The digital divide in education perpetuates inequities, limiting access to essential learning resources and hindering students' academic success, particularly in underserved regions. This study investigates the barriers and opportunities in ensuring equitable access to educational technology across different geographical and socioeconomic contexts. Using a qualitative research approach, data were collected through in-depth interviews, focus group discussions, and field observations in three regions of Indonesia: Jakarta, Central Java, and Eastern Indonesia. The study found significant disparities in access to digital tools and resources, with urban areas facing digital literacy challenges and rural and remote areas encountering severe infrastructural obstacles. Moreover, sociocultural factors, such as gender and the lack of home-based support, further exacerbated these inequalities. The research highlights the need for context-sensitive and equity-driven policies that address infrastructural and pedagogical gaps. It also emphasizes the importance of community involvement in developing local solutions to bridge the digital divide. The study contributes to the growing body of literature on digital inequality in education by providing insights into the multidimensional nature of the problem and offering recommendations for more inclusive edtech strategies. The findings suggest that bridging the digital divide requires a holistic approach beyond access to technology and includes digital literacy, teacher training, and community engagement.
Pengaruh Implementasi Internet of Things Terhadap Pengambilan Keputusan Bisnis Pada Perusahaan Teknologi di Jakarta Judijanto, Loso; Hiswara, Abrar; Aini, M. Anwar; Nanjar, Agi
Jurnal Multidisiplin West Science Vol 3 No 03 (2024): Jurnal Multidisiplin West Science
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/jmws.v3i03.1075

Abstract

Penelitian ini menyelidiki pengaruh implementasi Internet of Things (IoT) terhadap pengambilan keputusan bisnis dalam perusahaan teknologi di Jakarta, Indonesia. Melalui analisis kuantitatif, data dikumpulkan dari 123 perusahaan teknologi melalui kuesioner terstruktur. Penelitian ini mengeksplorasi hubungan antara adopsi IoT dan efisiensi dan efektivitas pengambilan keputusan. Hasil penelitian menunjukkan adanya hubungan positif yang signifikan antara implementasi IoT dan efisiensi serta efektivitas pengambilan keputusan. Temuan ini menggarisbawahi pentingnya integrasi IoT secara strategis dalam meningkatkan proses pengambilan keputusan di dalam perusahaan teknologi, memberikan wawasan yang berharga untuk strategi organisasi yang bertujuan untuk memanfaatkan IoT untuk hasil bisnis yang lebih baik.
Optimization of Grid Computing for Big Data Processing in Biomedical Research Sope, Devi Rahmah; Cale, Wolnough; Aini, M. Anwar; Yusuf, Nur Fajrin Maulana; Zoraida, Masli Nurcahya
Journal of Computer Science Advancements Vol. 2 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i6.1619

Abstract

The rapid growth of biomedical research has generated massive volumes of data, creating significant computational challenges. Traditional high-performance computing systems struggle to efficiently process, analyze, and manage such large-scale datasets. Grid computing, with its distributed architecture, offers a promising solution by enabling scalable and cost-effective data processing. This study explores the optimization of grid computing frameworks for big data processing in biomedical research, focusing on enhancing computational efficiency, scalability, and fault tolerance. The research aimed to evaluate the performance of optimized grid computing systems in processing diverse biomedical datasets, including genomic, proteomic, and imaging data. A combination of experimental and comparative approaches was employed, integrating grid computing frameworks such as Apache Hadoop and Globus Toolkit with biomedical data pipelines. Key metrics, including processing time, resource utilization, and error rates, were analyzed to assess the system’s performance. The findings demonstrated that optimized grid computing systems reduced processing time by an average of 35% compared to traditional methods while maintaining high accuracy. Scalability tests confirmed the framework’s ability to handle datasets up to 15 times larger without significant performance degradation. Fault tolerance improved through adaptive resource allocation, minimizing workflow interruptions. The study concludes that optimized grid computing is a transformative approach for big data processing in biomedical research. Its ability to enhance computational efficiency and scalability positions it as a crucial tool for addressing the growing data demands of modern biomedical science.
Co-Authors Abrar Hiswara Cale, Wolnough Judijanto, Loso Nanjar, Agi Nur Fajrin Maulana Yusuf Sope, Devi Rahmah Zoraida, Masli Nurcahya