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Syaiful Zuhri Harahap
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Program Studi Sistem Informasi, Fakultas Sains & Teknologi, Universitas Labuhanbatu Jalan Sisingamangaraja No.126 A KM 3.5 Aek Tapa, Bakaran Batu, Rantau Sel., Kabupaten Labuhanbatu, Sumatera Utara 21418
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Journal of Computer Science and Information Systems (JCoInS)
Published by Universitas Labuhanbatu
ISSN : -     EISSN : 27472221     DOI : 10.36987
Core Subject : Science,
Computer Science & IT
Journal of Computer Science and Information Systems (JCoInS) - Journal of the Information Systems Study Program seeks to facilitate critical study and in-depth analysis of information system problems, this journal is an expert computer science scientist, information system scientist. e-ISSN : 2747-2221
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 165 Documents
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Teori Konsep Dan Aplikasinya Dalam Transformasi Digital Organisasi Sofyan, Hadron; Wardana, Priya; Harahap, Rizky Pratama; Maulana, Rezky; Pasaribu, Teguh Fadillah Alwi
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.v7i1.8843

Abstract

Management Information Systems (MIS) play a strategic role in supporting organizational management in the era of digital transformation. MIS integrates people, procedures, data, and technology to produce accurate, relevant, and timely information for managerial decision-making. This article aims to examine the basic concepts, principles, development, and application of Management Information Systems across various organizational sectors. The research method uses a conceptual literature review by analyzing MIS theories and practices, including historical development, system development models, cross-sector applications, and implementation challenges in the digital era. The results indicate that MIS functions not only as an operational tool but also as a core foundation for organizational digital transformation. Integration with modern technologies such as cloud computing, big data, and artificial intelligence enhances efficiency, transparency, and organizational competitiveness. This article is expected to serve as an academic and practical reference for organizations in implementing effective MIS.
Analisis Kualitas Layanan Sistem Akademik Terpadu Universitas Al Washliyah (SATUVA) Terhadap Kepuasan Dan Productivity Pengguna Menggunakan Metode End-User Computing Satisfaction (EUCS) Di Universitas Al Washliyah Medan Manao, Ibnu Afandi; Sarif, Muhammad Irfan; Helmandi, Asrul; Pohan, Muhammad Zainal Arifin; Sumiran, Sumiran
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.v7i1.8652

Abstract

This study analyzes the service quality of the Integrated Academic System of Universitas Al Washliyah (SATUVA) and its effects on user satisfaction and productivity at Universitas Al Washliyah Medan. Using the End‑User Computing Satisfaction (EUCS) method, a quantitative survey was conducted among lecturers, administrative staff, and students to measure dimensions such as content, accuracy, format, ease of use, timeliness, and technical support. Statistical analyses included reliability testing, correlation, and regression to examine relationships between service quality, satisfaction, and productivity. Results indicate that SATUVA’s service quality significantly influences user satisfaction, and satisfaction mediates the effect of service quality on user productivity. Findings highlight the need to improve interface design, data accuracy, user training, and support responsiveness to enhance the system’s effectiveness. Recommendations are offered for continuous development to support the university’s academic and administrative performance.
Rancang Bangun Sistem Informasi Penjualan Sepatu Menggunakan Bahasa Pemograman PHP Dan MySQL Pada Aman Store Rantau Prapat Putri, Nia Edi; Harahap, Syaiful Zuhri; Irmayanti, Irmayanti; Juledi, Angga Putra
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.v7i1.9025

Abstract

The rapid development of information technology has pushed various business sectors, including Aman Store Rantau Prapat, to adapt digital technology to enhance operational efficiency and market reach. Currently, Aman Store still relies on a manual system, which results in inefficiencies in monitoring transactions and stock, as well as a limited market reach. This research aims to design and build a web-based shoe sales information system using PHP and a MySQL database. The system development follows the Waterfall method, which includes stages of requirement analysis, system design, implementation, testing, and maintenance. System modeling is represented using the Unified Modeling Language (UML), including Use Case, Activity, and Sequence Diagrams, to visualize actor-system interactions and business processes. The result of this research is a web-based application that provides digital product catalogs, online ordering and payment features, and automated stock management. Implementation of this system is expected to accelerate the transaction process, reduce human error, and expand market coverage beyond the local area, thereby increasing the store's competitiveness.
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.
Rekayasa Fitur dan Gradient Boosting untuk Prediksi Harga Saham Pada Pasar Saham Indonesia Rambe, Bhakti Helvi; Munthe, Ibnu Rasyid; Hanum, Fauziah; Hutagaol, Anita Sri Rejeki
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.v7i1.8945

Abstract

This study aims to analyze the comparative performance of three machine learning models Neural Network, Random Forest, and XGBoost in predicting the stock price of Bank Rakyat Indonesia (BBRI.JK) based on feature engineering integration. The background of this study is based on the need to develop accurate and efficient predictive models to deal with stock market volatility. The Data used covers the period 2010-2025 with the application of technical indicators such as Moving Average (MA), Relative Strength Index (RSI), volatility, and price momentum as the main features. The research method uses a machine learning approach based on supervised learning with a five-fold cross validation process. Model evaluation was conducted using quantitative metrics including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), coefficient of determination (R2), and Mean Absolute Percentage Error (MAPE). The results showed that XGBoost produced the Best Performance With R2 = 0.9451, MAE = 87.3129,and MSE = 10327.1187, followed by Random Forest (R2 = 0.9233) and Neural Network (R2 = 0.9120). The XGBoost Model proved to be the most stable and efficient in handling nonlinear data as well as extreme price fluctuations. The discussion confirms that the integration of engineering features improves the generalization capability of the model and lowers the prediction error rate significantly. Future research is recommended to include macroeconomic variables, sentiment data, and reinforcement learning approaches to broaden the scope and improve the model's adaptability to global financial market dynamics.
Klasifikasi Tingkat Stres Mahasiswa Dalam Penyelesaian Tugas Akhir Menggunakan Naïve Bayes Dan K-Nearest Neighbor Pefrianti, Lenni; Munthe, Ibnu Rasyid; Irmayanti, Irmayanti; Masrizal, Masrizal
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.v7i1.9060

Abstract

This study aims to analyze the stress levels of final-year students and compare the performance of Naïve Bayes and K-Nearest Neighbor (KNN) algorithms in stress classification. Data were collected from 82 respondents through a questionnaire consisting of seven variables (S1–S7) measuring factors contributing to stress, which were classified into low, moderate, and high stress levels. The results show that both algorithms can classify student stress effectively, with Naïve Bayes achieving the highest accuracy (90.15%) compared to KNN (87.72%). Distribution analysis by study program indicates that Agrotechnology has the highest proportion of students with high stress (42.86%), followed by Information Systems (40.63%) and Information Technology (13.64%). This study provides insights for the university to offer targeted support through counseling or stress management workshops.
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.
Analisis Kelayakan Ekonomi Islam Melalui Investasi Mesin CNC Pada Industri Manufaktur Menengah Dengan Pendekatan Net Present Value (NPV) Supriono, Supriono; Siregar, Nur Asyiah; Sundari, Risky Fajar; Arifah, Rena; Wirasari, Riza Ria
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.v7i1.8922

Abstract

This article aims to analyze the economic feasibility of CNC machine investment in a medium-sized manufacturing industry using the Net Present Value (NPV) approach. The research method used is a library search, which involves collecting and analyzing secondary data from literature related to CNC machine investment, feasibility studies, and NPV calculation methods. The analysis begins with identifying initial investment costs, projecting annual net cash flows, determining the discount rate, calculating the NPV, and analyzing sensitivity to changes in key variables. The results show a positive NPV, indicating that this investment is financially profitable and feasible. In addition to financial benefits, the use of CNC machines also provides strategic benefits such as increased production efficiency, reduced reject rates, and improved product quality. Therefore, investing in CNC machines is recommended as a strategic step to increase the competitiveness and productivity of medium-sized manufacturing industries amidst increasingly fierce market competition.
Analisis Kepuasan Orangtua Dalam Sistem Pendidikan Ponpes Dengan Pendekatan Servqual dan Structural Equation Modelling (SEM) Manao, Ibnu Afandi; Khairul, Khairul; Helmandi, Asrul; Pohan, Muhammad Zainal Arifin; Sumiran, Sumiran
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.v7i1.9078

Abstract

This study aims to analyze parents' satisfaction with the educational system of Islamic boarding schools using the Service Quality (SERVQUAL) and Structural Equation Modelling (SEM) approaches. The increasing number of Islamic boarding schools and the growing public demand for quality educational services require educational institutions to provide optimal services. This research employed a quantitative method by collecting data through questionnaires distributed to parents of students at Tahfidz Darul Qur’an Islamic Boarding School. The service quality dimensions analyzed include tangibles, reliability, responsiveness, assurance, and empathy. The data were analyzed using SEM to examine the relationship between service quality dimensions and parents’ satisfaction. The results indicate that service quality has a positive influence on parents’ satisfaction. Several SERVQUAL dimensions significantly contribute to increasing satisfaction, particularly assurance and empathy. These findings suggest that improving educational service quality, including facilities, communication, and educator competence, plays an important role in enhancing parents’ satisfaction. This study is expected to provide insights for Islamic boarding school management in developing strategies to improve educational service quality sustainably.
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.

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