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All Journal CESS (Journal of Computer Engineering, System and Science) Jurnal ULTIMATICS Jurnal Sistem Komputer dan Informatika (JSON) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Penelitian, Pendidikan dan Pengajaran: JPPP Ar-Rasyid: Jurnal Pendidikan Agama Islam Educenter: Jurnal Ilmiah Pendidikan sudo Jurnal Teknik Informatika Hello World Journal of General Education and Humanities Blend Sains Jurnal Teknik Factory Jurnal Industri, Manajemen dan Rekayasa Sistem Industri Jurnal Sains Student Research Jurnal Ilmu Komputer dan Sistem Informasi Hanif Journal of Information Systems EDUCENTER JURNAL PENDIDIKAN Portal Riset dan Inovasi Sistem Perangkat Lunak Tsabit Jurnal Informatika Dan Tekonologi Komputer
Mhd. Basri
Universitas Muhammadiyah Sumatera Utara
Religion Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Other

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Perancangan Sistem IoT Untuk Monitoring Getaran dan Stress Pada Kanopi Rumah Berbasis ESP32 Raushan Dhamir; Mhd. Basri
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.366

Abstract

The development of Internet of Things (IoT) enables real-time and continuous monitoring systems. Lightweight structures such as house roofs or canopies are vulnerable to environmental and load changes, yet monitoring is still commonly performed manually, making early detection difficult. This study aims to design and implement an IoT-based canopy structure monitoring system using ESP32 integrated with an MPU6050 vibration sensor, a load cell with HX711 module, and a DHT22 temperature and humidity sensor. Measurement data are transmitted via WiFi to a server for database storage and visualization through a web-based dashboard. Furthermore, the collected data are processed using the Relative Corrosion Potential Index (IPKR), calculated based on normalized parameters including temperature, humidity, vibration, and load variation. The results show that the system is capable of performing real-time data acquisition, transmission, and visualization effectively. The system also provides structural condition indicators based on IPKR values classified into safe, warning, and danger categories. Therefore, the developed system can serve as an effective and informative early monitoring solution for detecting changes in lightweight structure conditions.
Teacher discipline assessment with Mamdani Fuzzy Logic decision support system on attendance data at Phatnawitya School Yala Muhammad Zulfahmi Khairullah; Mhd. Basri
Educenter : Jurnal Ilmiah Pendidikan Vol. 5 No. 1 (2026): Educenter: Jurnal Ilmiah Pendidikan (In press)
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/educenter.v5i1.1850

Abstract

Teacher discipline is a crucial factor in maintaining the quality of the learning process in schools; however, discipline assessment is often conducted subjectively and relies on rigid threshold values. This study aims to develop a decision support system based on Mamdani Fuzzy Logic to evaluate teacher discipline using attendance data. The research method includes fuzzification, Mamdani fuzzy inference, and defuzzification using the centroid method, with two input variables attendance and absence without permission (alpha) and one output variable in the form of a discipline score. The results indicate that teachers with attendance ≥90% and alpha ≤3 days are classified as “Very Good”, those with attendance between 80-89% fall into the “Good” to “Fair” categories, while attendance below 75% or alpha above 12 days is categorized as “Poor”. The fuzzy system produces consistent, stable, and flexible assessments through gradual value transitions. In conclusion, Mamdani Fuzzy Logic is effective as a more objective and realistic tool for evaluating teacher discipline compared to conventional threshold-based methods.
Decision analysis on the use of figma to improve learning effectiveness at Saengsattha School Thailand using the AHP Method Defri Aldi; Mhd. Basri; Lutfi Basit
Educenter : Jurnal Ilmiah Pendidikan Vol. 5 No. 1 (2026): Educenter: Jurnal Ilmiah Pendidikan (In press)
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/educenter.v5i1.2058

Abstract

The development of digital media-based learning requires the selection of platforms that are not only easy to use, but also capable of supporting interactivity, collaboration, and providing a real impact on learning outcomes. However, the selection of digital learning media in schools is often not based on systematic and measurable decision analysis. This condition creates a need for objective evaluation of the effectiveness of digital media used in the learning process. This study aims to analyze the effectiveness of using Figma as a digital learning medium at Saengsattha School in Thailand. This study uses a descriptive quantitative approach with data collection through a five-point Likert scale questionnaire involving 100 respondents, consisting of 10 teachers and 90 students. Data analysis was performed using the Analytical Hierarchy Process (AHP) method to determine the weight of importance of four main criteria, namely ease of use, interactivity, collaboration, and impact on learning outcomes and user satisfaction. The results showed that Figma obtained a final score of 4.06 and was categorized as effective, with the criteria of impact and user satisfaction as the most dominant factors. These findings indicate that Figma is suitable for use as a digital learning medium and that AHP can be a systematic method to support decision-making in selecting digital learning media in schools.
Analysis of Determining Public Speaking Skill Levels of Junior High School Students Using the TOPSIS Method at Phatnawitya School, Yala, Thailand Zaky Soleh Wirawan; Mhd. Basri
Journal of General Education and Humanities Vol. 5 No. 2 (2026): April
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/gehu.v5i2.1098

Abstract

Evaluating junior high school students' public speaking skills often faces the challenge of subjectivity, especially in international schools where manual assessment lacks mathematical rigor. This study applied the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with manual calculations to objectively rank 28 students from Phatnawitya School, Yala, Thailand, based on seven Canva presentation criteria: Eye Contact, Body Language, Poise, Subject Knowledge, Fluency, Pronunciation, and Comprehension. Using a descriptive quantitative approach, purposive sampling targeted one top-tier class as the sample population. Teachers' Excel assessment data were analyzed using TOPSIS through decision matrix formation, normalization, weighted normalization, ideal solution determination, distance calculation, and preference assessment. The results showed that Salsabil Hayitahe ranked first (V=0.65) and Muhammadsharif Seng last (V=0.36), proving the effectiveness of TOPSIS in providing transparent, bias-free ranking. The conclusions confirm the suitability of manual TOPSIS for multi-criteria educational evaluation, without software dependence, and recommend its wider application across various classes.
Comparative Analysis of the Performance of VGG16 and ResNet50 Architectures in Multi-Class Classification of Rice Plant Diseases Based on Convolutional Neural Networks (CNN) Krisna Aditya; Mhd. Basri
Tsabit Journal of Computer Science Vol. 2 No. 2 (2025): December Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit55

Abstract

Rice plant diseases significantly affect crop productivity and food security, making early and accurate disease detection essential for effective agricultural management. Recent advances in deep learning, particularly Convolutional Neural Networks (CNN), have demonstrated strong potential in image-based plant disease classification. This study presents a comparative analysis of the performance of VGG16 and ResNet50 architectures for multi-class classification of rice plant diseases using CNN-based approaches. A dataset of rice leaf images representing multiple disease classes and healthy conditions was collected and preprocessed through image resizing, normalization, and data augmentation to enhance model generalization. Both pre-trained models were fine-tuned using transfer learning to adapt them to the rice disease classification task. Model performance was evaluated using standard metrics, including accuracy, precision, recall, F1-score, and confusion matrix analysis. The experimental results show that both architectures achieve high classification performance; however, ResNet50 demonstrates superior accuracy and better generalization capability compared to VGG16, particularly in handling complex disease patterns and intra-class variations. Meanwhile, VGG16 offers a simpler architecture with faster convergence and lower computational complexity. The findings of this study provide insights into the selection of appropriate CNN architectures for rice plant disease classification and support the development of intelligent decision support systems in precision agriculture.
Development of a Decision Support System to Determine Best-Selling Menu Canteen Employees of the Bank Indonesia Representative Office in North Sumatra Province using the Topsis Method M. Rizki Adhari; Mhd. Basri
Tsabit Journal of Computer Science Vol. 2 No. 2 (2025): December Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit60

Abstract

The availability of accurate sales information is essential for supporting managerial decision-making in institutional food services. At the Bank Indonesia Representative Office in North Sumatra Province, determining the best-selling menu for employee canteen services is still largely based on manual evaluation, which may lead to inefficiencies and subjective judgments. This study aims to develop a Decision Support System (DSS) to identify the best-selling canteen menu using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The system evaluates menu alternatives based on multiple criteria, including sales volume, price, menu availability, and employee preferences. Data were collected from historical sales records and questionnaires distributed to canteen employees. The TOPSIS method was applied to rank menu alternatives by calculating their relative closeness to the ideal positive and ideal negative solutions. The DSS was implemented as a computerized system to facilitate data processing, ranking, and visualization of decision results. The results show that the proposed system is able to objectively determine the best-selling menu and provide consistent rankings compared to conventional methods. The developed DSS improves accuracy, efficiency, and transparency in menu evaluation, thereby supporting better planning and inventory management for the employee canteen. This study demonstrates that integrating multi-criteria decision-making methods into a DSS can effectively enhance decision quality in institutional food service management.
Design and Implementation of Multi-Segment LAN Infrastructure for Computer Laboratories Andi Zulherry; Muhammad Gunawan; Mhd. Basri
Tsabit Journal of Computer Science Vol. 2 No. 2 (2025): December Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit91

Abstract

Educational computer laboratories require a reliable and well-structured network infrastructure to support learning activities and efficient resource management. However, many laboratory networks are still implemented using a single network segment, which can lead to high broadcast traffic and reduced network performance as the number of connected devices increases. This study proposes the design and implementation of a multi-segment Local Area Network (LAN) infrastructure based on institutional needs in an educational computer laboratory environment. The proposed network architecture consists of four laboratory rooms with a total of 160 computers, where each laboratory operates within a different IP network segment while remaining interconnected through routing mechanisms. Network devices such as the MikroTik RB750Gr3 hEX router are used to manage gateway functions, DHCP services, and network address translation (NAT) for internet connectivity. The implementation is evaluated through connectivity tests between laboratory networks and internet access tests. The results show that all laboratory networks successfully communicate with each other without packet loss and demonstrate low latency values, indicating stable network performance. In addition, internet connectivity tests confirm that all laboratory networks can access external resources reliably. These findings demonstrate that the proposed multi-segment LAN infrastructure improves network organization, scalability, and manageability within educational computer laboratory environments.
Anomaly Detection in Electrical Energy Consumption Using Long Short-Term Memory (LSTM) Andi Zulherry; Mhd. Basri; muhammad Gunawan
Tsabit Journal of Computer Science Vol. 3 No. 1 (2026): June Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit123

Abstract

The increasing deployment of smart meters has generated large volumes of electrical energy consumption data, creating new opportunities for intelligent anomaly detection to reduce non-technical losses, equipment failures, and abnormal consumption patterns. Conventional statistical and rule-based approaches often struggle to capture complex temporal dependencies in sequential electricity usage data. This study proposes a Long Short-Term Memory (LSTM)-based anomaly detection model to identify abnormal electricity consumption patterns with high accuracy. A time-series dataset consisting of historical hourly electricity consumption records was collected from smart metering systems and preprocessed through missing-value imputation, normalization using Min-Max Scaling, and sequence windowing. The proposed LSTM model was trained to learn normal consumption behavior and detect anomalies based on prediction error using an adaptive threshold determined from reconstruction residuals. Model performance was evaluated using accuracy, precision, recall, F1-score, and Area Under the Receiver Operating Characteristic Curve (AUC), and compared with conventional Machine Learning methods, including Support Vector Machine (SVM) and Isolation Forest. Experimental results demonstrate that the proposed LSTM model achieved an accuracy of 97.3%, precision of 96.8%, recall of 97.9%, F1-score of 97.3%, and an AUC of 0.985, outperforming the baseline models in detecting anomalous electricity consumption patterns. The superior performance is attributed to the LSTM architecture's ability to model long-term temporal dependencies and nonlinear consumption behaviors. These findings indicate that LSTM provides an effective and reliable approach for real-time anomaly detection in smart energy systems, supporting intelligent energy management, reducing power losses, and improving the operational reliability of modern electrical distribution networks.
Design and Development of an Internet of Things (IoT)-Based Real-Time Tide Monitoring System for Coastal Water Level Observation Muhammad Ari Juanda; Mhd. Basri
Hanif Journal of Information Systems Vol. 3 No. 2 (2026): February Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v3i2.71

Abstract

Sea tides are a phenomenon of the periodic rise and fall of sea level caused by a combination of gravitational force and the attractive force of astronomical objects, especially the sun, earth and moon. Every day the tidal phenomenon occurs and information about tides is very useful for human activities related to the marine sector such as fishing and other activities. There is a need for intelligent tool concept technology that can help and alleviate this problem, so an instrumentation tool has been created that can provide tidal information at any time that can be accessed via the internet network using the Android system. Decisions can match human thought patterns. The electronic components used in implementing the system are nodeMCU as a controller and internet of things (IOT) communication, ultrasonic sensors function as a medium for measuring sea water height. This research produces a system that can monitor the ebb and flow of sea water. In the system, a notification system is implemented for system users so they can monitor the ebb and flow of sea water. The application used is the blynk application which is integrated with the internet.
Implementasi Internet of Things Berbasis Website dalam Pemesanan Jasa Rumah Service Teknisi Komputer dan Jaringan Komputer Indah Purnama Sari; Ismail Hanif Batubara; Mhd. Basri; Al Hamidy Hazidar
Blend Sains Jurnal Teknik Vol. 1 No. 2 (2022): Edisi Oktober
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (304.809 KB) | DOI: 10.56211/blendsains.v1i2.136

Abstract

Pada website pemesanan jasa rumah teknisi atau di sebut dengan service computer dan jaringan computer atau di kenal internet merupakan website yang di rancangkan untuk menerima booking service untuk toko rumah teknisi computer dan jaringan internet. Pada kali ini website yang di rancangkan agar bisa mencatat riwayat servis dari PC Desktop, Laptop dan pada masalah jaringan computer. Aplikasi ini dibuat menggunakan bahasa pemrogramman Web, PHP dan HTML yang digunakan adalah MySQL dan xampp. Aplikasi ini memiliki 2 aktor yaitu Pelanggan, dan Teknisi. Hasil dari penelitian ini memberikan sistem pemesanan jasa rumahteknisi komputer berbasis web yang mudah, cepat dan akurat serta dapat diakses melalui berbagai gadget yang tersambung jaringan internet.
Co-Authors Abdul Fadlil Akhun Ihsan Hia Al Hamidy Al Khowarizmi Andi Zulherry Andi Zulherry Andi Zulherry Andy Satria Anis Badriah Anton Yudhana Baehaqi Barelvi, Ahmad Defri Aldi Dicky Apdilah Dina Salsabila Edy Rahman Syahputra Farid Akbar Siregar Fatma Sari Hutagalung G. Gunawan Halim Maulana Hasibuan, Wilda Rina Hayani, Wirda Indah Purnama Sari Indah Purnama Sari Ismail Hanif Batubara Krisna Aditya Krisna Aditya Lutfi Basit M. Rizki Adhari Mahardika Abdi Prawira Manurung, Asrar Aspia Muhammad Ari Juanda Muhammad Gunawan Muhammad Iqbal Pradipta Muhammad Zulfahmi Khairullah Nurul Hakiki Lubis Ok Muhammad Rehansyah Putra rahayu, Intan dwi Ramadhani, Fanny Raushan Dhamir Rosaldi Alfarizi RR. Ella Evrita Hestiandari Salsabila Humairoh Sihombing, Maissy Masitoh Syafrayani, Putri Rizki Syahri, Alfi Wahyu Purnomo Yohanni Syahra Zaky Soleh Wirawan Zaky, Naufal Zein, Liza Azzahra