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Journal : Journal of Computer Science and Information Systems (JCoInS)

Sistem Informasi Manajemen di Era IoT dan Cloud Audya, Anggi; Pefrianti, Lenni; Saroni, Habi; Putri, Pujawati Kurnia; Indriani, Vivi; Srikandy, Yuyun Lili; Sitorus, Sahat Parulian
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.v7i1.8816

Abstract

The rapid development of Internet of Things (IoT) and cloud computing technologies has significantly transformed the way organizations manage information. Management Information Systems (MIS) are no longer limited to data recording and reporting functions but have evolved into integrated systems capable of providing real-time information to support strategic decision-making. This article aims to examine the role, benefits, and challenges of implementing Management Information Systems in the era of IoT and cloud computing. The research method employed is a literature review, drawing on relevant journals, books, and scientific publications. The results indicate that the integration of IoT and cloud computing into MIS can enhance operational efficiency, data accuracy, and system flexibility. However, several challenges remain, particularly related to data security, privacy issues, and the readiness of human resources.
Pemanfaatan Teknologi Big Data Dalam Pengambilan Keputusan Dan Inovasi Di Era Digital Harefa, Arnes Dian Putri; Julianti, Julianti; Nahampun, Kessia Inriani; Ritonga, Putri; Sitorus, Sahat Parulian
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.
Pemanfaatan Big Data dalam Meningkatkan Daya Saing UMKM Hasibuan, Muhammad Ridho; Adriansyah, Wahyu; Akmal, Zahri; Tarigan, Oktari; Sitorus, Sahat Parulian
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.v7i1.8875

Abstract

The rapid development of information technology has driven the growth of data in massive volumes, commonly referred to as Big Data. The utilization of Big Data offers strategic opportunities for Micro, Small, and Medium Enterprises (MSMEs) to enhance their competitiveness amid increasingly intense business competition. This study aims to examine the role of Big Data in supporting decision-making, understanding consumer behavior, and improving the operational efficiency of MSMEs. The research method employed is a literature review of relevant journals, books, and research reports. The findings indicate that the application of Big Data enables MSMEs to conduct market analysis, personalize products, and optimize digital marketing strategies. However, challenges such as limited human resources, technological infrastructure, and data security remain significant barriers. Therefore, support from the government and related stakeholders is necessary to encourage the optimal adoption of Big Data in the MSME sector.
Visualisasi Data Perkara Tindak Pidana Umum Menggunakan Python (Studi Kasus : Case Management System Kejaksaan Negeri Labuhanbatu Tahun 2023-2024) Adryan, Ahmad; Andre, Ivo; Rambe, Fani Wulandari; Sitorus, Sahat Parulian
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.v7i1.8887

Abstract

This study examines general criminal cases at the Kejaksaan Negeri Labuhanbatu for the years 2023–2024, focusing on three main aspects: case types, monthly trends, and the status of case handling. The data were analyzed and visualized using Python with pandas and matplotlib, producing bar and line charts that facilitate the identification of patterns, fluctuations, and case distribution. The analysis shows a decrease in Narcotics and Theft cases, while other case types, including Child Protection and Fraud, remained relatively stable. Monthly trends revealed that the highest number of cases occurred in November 2023, whereas the lowest was observed in April 2024, indicating potential seasonal effects on case occurrences. Regarding case handling, most cases successfully reached the stages of File Receipt and Complete File, although the number of cases achieving execution decreased compared to the previous year. These visualizations provide a clear and comprehensive view of the workflow from case initiation to execution, highlighting stages that require more attention and resources. Overall, this study demonstrates that data visualization can significantly improve understanding of complex datasets, support strategic planning, and assist the District Attorney’s Office in prioritizing case management for general criminal cases.
Fundamental Dan Implementasi Big Data Dalam Transformasi Digital Setiawan, Haykal Tito; Reksa, Angga; Ritonga, Rizky Pratama Ramadani; Sitorus, Sahat Parulian
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.v7i1.8894

Abstract

Digital transformation has encouraged organizations to optimally utilize information technology to manage data. Big data has become a key element that plays a crucial role in supporting the digitalization process in various sectors. The theoretical basis of this study discusses the concepts of big data, digital transformation, information systems, data governance, and digital human resources. These theories form the basis for understanding the relationship between technology and organizational performance. The research method used is descriptive qualitative, using a literature review and case study approach. Data was obtained from various reliable sources and systematically analyzed to obtain valid results. The results show that implementing big data can improve operational efficiency and the quality of decision-making. In addition, big data also drives innovation and strengthens organizational competitiveness. The research discussion emphasizes that the success of big data implementation is influenced by the readiness of human resources, infrastructure, and management support. A holistic approach is necessary for digital transformation to be sustainable. The study concludes that big data is a strategic asset in the digital era. Optimal utilization of big data can support organizational growth, innovation, and sustainability in the future.
Analisis Tren Pendaftaran Siswa Alwashliyah Marbau Menggunakan Big Data Putra, Mhd Aftiansyah; Mulawarman, Marchelius; Aziz, Abdul; Sitorus, Sahat Parulian
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.