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Hanif Journal of Information Systems
Published by Ilmu Bersama Center
ISSN : -     EISSN : 30252342     DOI : https://doi.org/10.56211/hanif
Core Subject : Science,
Computer Science & IT Library & Information Science
Hanif journal of Information Systems aims to provide scientific literatures specifically on studies of applied research in information systems (IS)/information technology (IT) and public review of the development of theory, method and applied sciences related to the subject. Hanif Journal of Information Systems accepts manuscripts on the topics: E-Business/E-commerce E-Government E-Health E-learning Human-Computer Interaction Information Assurance & Intelligent Information Security & Risk Management IS/IT Operations Management IS/IT Organization & Human Resource Management IS/IT Strategic Planning IT Governance IT Investment Analysis IT Project Management Web Science Social Media in Business Multimedia Application Big Data Research New Technology Acceptance and Diffusion Green Information Systems Innovation Management/Technopreneurship Data Science And other topics relevant to Information Systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 26 Documents
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Home Anti Theft System Uses Based Telegram Bot Internet of Things Fadhlurrohman, Dimas; Basri, Mhd
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.36

Abstract

Often we hear cases of home theft and belongings valuable. This crime is difficult for the owner of valuables to know. Usually it will be known after the theft disaster. Circumstances like this certainly make us uncomfortable and feel restless about our valuables. Most people for their valuables security systems use CCTV (Closed Circuit TeleVision), which can record the movements of every person's activity. One of the disadvantages of using CCTV is that after we know there is a theft disaster, then we can only see from the image recordings that have occurred, and the perpetrators of the theft can be revealed. This of course still makes it difficult for us to solve these problems.
IoT Based Industrial Waste Monitoring System Design with Data Visualization on A Web Application Using The Supervised Learning Method Ritonga, Muhammad Nauval Asyqar Ridwan; Maulana, Halim
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.50

Abstract

Industrial waste management is a critical aspect of sustainable manufacturing, as improper handling can lead to severe environmental pollution and health hazards. Real-time monitoring of industrial waste parameters enables early detection of irregularities and supports informed decision-making for compliance with environmental regulations. This study presents the design of an IoT-based industrial waste monitoring system integrated with data visualization on a web application and enhanced by the supervised learning method for predictive analysis. The system utilizes IoT sensor nodes to measure key waste parameters such as pH level, temperature, turbidity, and chemical concentration. Sensor data is transmitted wirelessly to a cloud server, where it is stored, processed, and analyzed using supervised learning algorithms to classify waste quality and detect potential violations. The web application provides interactive dashboards, historical data tracking, and real-time alerts for stakeholders. Testing results demonstrate that the system achieves high accuracy in classifying waste conditions, offers user-friendly visual analytics, and enables proactive waste management. This research contributes to the development of intelligent environmental monitoring solutions, promoting efficiency, compliance, and sustainability in industrial operations.
Design and Implementation of a Web-Based Online Registration System for HIMATIF Using the Agile Development Method Senoaji, Arya Dimas; Akbar, Farid
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.51

Abstract

Efficient and well-organized registration processes are essential for supporting the activities and membership management of student organizations. The Information Technology Student Association (HIMATIF) requires a system that can streamline registration, reduce administrative workload, and improve data accuracy. This study focuses on the design and implementation of a web-based online registration system for Himatif using the Agile development method. The system features member registration, data validation, document uploads, activity selection, and administrative dashboards for managing registrant information. The Agile approach, specifically the Scrum framework, was applied to enable iterative development, continuous feedback, and rapid adaptation to changing requirements. The system was developed using PHP with the Laravel framework and MySQL for database management, ensuring secure and scalable performance. Testing results show that the application meets functional requirements, operates reliably across multiple devices, and significantly reduces the time required for registration compared to manual processes. This system enhances operational efficiency, improves data management, and provides a better user experience for both members and administrators.
Implementation of Linear Regression Algorithm in a Web-Based Major Prediction System for New Student Applicants at SMK N 1 Percut Sei Tuan Pulungan, Sabrina Meylani; Siambaton, Mhd. Zulfansyuri; Santoso, Heri
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.47

Abstract

This study aims to develop a web-based major prediction system by applying a linear regression algorithm to enhance transparency and accuracy in the selection process. The system predicts 14 available majors at SMK N 1 Percut Sei Tuan, including: Civil Construction and Housing Engineering, Modeling and Building Information Design, Geomatics Engineering, Electrical Installation Engineering, Electrical Power Network Engineering, Heating, Air Conditioning and Refrigeration Engineering, Audio Video Engineering, Machining Engineering, Welding Engineering, Light Vehicle Engineering, Motorcycle Engineering, Software Engineering, Computer and Network Engineering, and Television Production and Broadcasting. The system uses report card scores from the 5th and 6th semesters of junior high school as predictor variables, including Bahasa Indonesia, Mathematics, Science, and English. The system development method includes data collection through observation, literature study, and interviews, as well as system design using PHP, HTML, JavaScript, MySQL database, and XAMPP. System modeling was carried out using UML (Unified Modeling Language), which includes use case diagrams, sequence diagrams, and activity diagrams. The linear regression algorithm is implemented by calculating subject averages, regression coefficients, and intercepts to predict student acceptance. The results of the study, based on five student data samples, show that M. Dafi and Ahmad Suhendra were not eligible for any major. Adellya Saputri and Alfit Septian were accepted into one major, Television Production and Broadcasting. Meanwhile, Ummi qualified for five majors: Modeling and Building Information Design, Audio Video Engineering, Welding Engineering, Light Vehicle Engineering, and Television Production and Broadcasting.
A Decision Support System for Determining Optimal Concrete Quality Using the Simple Additive Weighting (SAW) Algorithm (Case Study: UISU Concrete Laboratory) Rianto, Muhammad Aulia Abdi; Siambaton, Mhd. Zulfansyuri; Santoso, Heri
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.48

Abstract

This study aims to design a decision support system to determine the best concrete quality using the Simple Additive Weighting (SAW) algorithm. Concrete is the primary material in construction, possessing various mechanical properties and characteristics that define its quality. At the Concrete Laboratory of Universitas Islam Sumatera Utara (UISU), the determination of concrete quality is still conducted manually, relying on subjective experience, which can lead to inconsistencies in assessment. Therefore, developing a system based on the SAW algorithm is necessary to enhance efficiency and objectivity in selecting the best concrete. The research process begins with data collection on concrete samples, covering parameters such as compressive strength, water volume, setting time, cement content, and aggregate quantity. Each criterion is assigned a weight based on its importance, followed by normalization to align scale values. The SAW algorithm is then applied to calculate the final preference values for each concrete sample, ultimately generating a recommendation for selecting the highest-quality concrete. The study results show that Concrete C achieves the highest final score (0.94706), followed by Concrete A (0.88328) and Concrete B (0.76292). The study concludes that the SAW algorithm effectively enhances objectivity and accuracy in determining the best concrete quality.
Application of Data Mining to Determine the Performance of Family Planning Field Officers (PLKB) Using the C4.5 Algorithm Nasution, Perdinal; Azhari, Mulkan
Hanif Journal of Information Systems Vol. 3 No. 1 (2025): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i1.52

Abstract

The effectiveness of family planning programs is closely related to the performance of Family Planning Field Officers (PLKB). Conventional performance evaluation methods often rely on manual assessments, which may lead to subjectivity and inconsistency. To overcome this issue, data mining techniques can be applied to analyze performance data systematically and objectively. This study employs the C4.5 decision tree algorithm to classify and evaluate the performance of PLKB. The dataset used in this research includes several indicators, such as service coverage, counseling frequency, reporting accuracy, and community participation. Prior to model construction, data preprocessing was performed to handle missing values and normalize attributes. The model performance was evaluated using accuracy, precision, recall, and F-measure. The findings indicate that the C4.5 algorithm successfully classified PLKB performance into three categories: high, medium, and low. The model achieved an accuracy of [insert % if available], demonstrating its effectiveness in identifying key determinants of officer performance. Moreover, the decision tree generated interpretable rules that highlight the most influential attributes affecting PLKB performance. The application of data mining using the C4.5 algorithm provides an objective and efficient method for evaluating PLKB performance. This approach not only enhances decision-making for supervision and training but also contributes to the improvement of family planning program implementation. Future research is suggested to compare the C4.5 algorithm with other classification methods to achieve higher accuracy and generalizability.

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