MAHENDRA DATA, S.Kom., M.Kom., Ph.D.

Overview

MAHENDRA DATA, S.Kom., M.Kom., Ph.D., is a distinguished faculty member of the Fakultas Ilmu Komputer, serving within the Program Studi Sarjana Teknik Informatika. His publication record demonstrates a broad spectrum of research interests that reflect both depth and breadth in contemporary computer science. A careful examination of his recent works reveals several intriguing trends. First, there is a clear shift toward interdisciplinary applications of decision-making and optimization techniques. Early studies focused on traditional systems such as database server reliability and network protocols, while later contributions increasingly incorporate advanced analytical frameworks like the Analytic Hierarchy Process (AHP), ELECTRE, TOPSIS, and machine learning classifiers such as Random Forest. This evolution illustrates a move from purely engineering-oriented investigations toward data-driven decision support systems that address complex real-world problems.

Second, the thematic focus of his research has expanded to encompass emerging domains such as virtualization and the Internet of Things (IoT). Papers on container-based virtualization for IoT devices and precision agriculture highlight a forward-looking engagement with cutting-edge infrastructure challenges. Simultaneously, his work on classification of pottery shards and unexposed potsherd cavities demonstrates a willingness to apply computational methods to domain-specific problems outside traditional computer science, indicating a broader, interdisciplinary reach.

Third, the linguistic and regional context of his publications is noteworthy. Titles are predominantly in Indonesian, underscoring a commitment to addressing local academic and industrial needs. This local orientation is complemented by the application of globally recognized methodologies, creating a bridge between regional relevance and international best practices.

Fourth, the publication cadence suggests a steady increase in output, with multiple papers appearing within short intervals. This pattern points to an active research agenda supported by collaborative networks and possibly a growing research group. The repeated appearance of certain topics, such as the reliability of multi-master database systems, signals ongoing investigations and a sustained interest in critical infrastructure resilience.

Overall, MAHENDRA DATA’s scholarly trajectory showcases a dynamic interplay between foundational computer science topics and innovative, application-driven research. His work exemplifies how a researcher can evolve from classic systems studies to sophisticated, interdisciplinary solutions that harness decision theory, machine learning, and emerging technologies, thereby contributing meaningfully to both national and global scientific dialogues.

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Research Interest

• Artificial Intelligence (AI)
• Internet of Things (IoT)
• Cloud Computing
• Cybersecurity
• Big Data Analytics
• Machine Learning (ML)
• Database Systems
• Network Security
• Data Science

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Qualifications

Researcher's data not available yet at researchers.ub.ac.id