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All Journal Journal of Computer Science and Information Systems (JCoInS)
Sahat Parulian Sitorus
Teknologi Informasi, Sains dan Teknologi, Universitas Labuhanbatu
Computer Science & IT

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Analisis Tren Pendaftaran Siswa Alwashliyah Marbau Menggunakan Big Data Mhd Aftiansyah Putra; Marchelius Mulawarman; Abdul Aziz; Sahat Parulian Sitorus
Journal of Computer Science and Information System(JCoInS) Vol 7, No 1: JCoInS | 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v7i1.8865

Abstract

This study aims to analyze student enrollment trends at the Alwashliyah Marbau Education Foundation over the past five years, focusing on the MTS, MAS, SMK-1, and SMK-2 levels. The analysis shows that the SMK-1 vocational program has seen a 15% increase in enrollment annually, while the MAS program has seen a significant decline of up to 20% in the last year. The majority of enrollees come from the Marbau area (70%), indicating a certain geographic dominance in student recruitment. Correlation tests identified a positive relationship between digital promotion and enrollment growth at the SMK level. Key recommendations include increasing the intensity of digital promotion, adjusting the curriculum based on job market needs, and evaluating promotional strategies for programs with declining trends. The resulting data visualization also provides insights to support recruitment strategy optimization.
Pemanfaatan Teknologi Big Data Dalam Pengambilan Keputusan Dan Inovasi Di Era Digital Arnes Dian Putri Harefa; Julianti Julianti; Kessia Inriani Nahampun; Putri Ritonga; Sahat Parulian Sitorus
Journal of Computer Science and Information System(JCoInS) Vol 7, No 1: JCoInS | 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v7i1.8866

Abstract

Big Data is an information technology designed to manage data with extremely high volume, velocity, and variety that cannot be effectively processed using traditional approaches. This technology provides solutions to enhance decision-making processes, predict behavioral patterns, and foster service innovation across various sectors, including industry, education, and healthcare. This study conducts a comprehensive review of the evolution of Big Data technology, its main characteristics, and its impact on digital transformation through a literature review of recent scientific publications from the period 2021–2025. The results indicate that the adoption of infrastructures such as Hadoop, Spark, and real-time analytics platforms contributes to improved operational efficiency and the implementation of data-driven decision making. However, challenges related to data privacy, data quality, and human resource competencies still require appropriate mitigation strategies. The findings of this study highlight the importance of integrating Big Data with artificial intelligence and cloud computing architectures to address future analytical demands.
Co-Authors Abdul Aziz Arnes Dian Putri Harefa Julianti Julianti Kessia Inriani Nahampun Marchelius Mulawarman Mhd Aftiansyah Putra Putri Ritonga