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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika International Journal of Artificial Intelligence Research JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) METIK JURNAL Vocatech : Vocational Education and Technology Journal Jurnal Sosial Humaniora Sigli Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Bulletin of Computer Science Research JUTECH : Journal Education and Technology Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) TECHSI - Jurnal Teknik Informatika Journal of Information Technology (JINTECH) Jurnal Teknologi Terapan and Sains 4.0 Journal of Computer Engineering, Electronics and Information Technology Journal Of Artificial Intelligence And Software Engineering Jurnal Informatika: Jurnal Pengembangan IT Journal of Tourism Sciences, Technology and Industry Jurnal Malikussaleh Mengabdi Proceeding of The International Conference on Electrical Engineering and Informatics Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS)
Muhammad Fikry
Teknik Informatika Universitas Malikussaleh
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ANALISIS RISIKO DAN PENENTUAN PRIORITAS MITIGASI ASET TEKNOLOGI INFORMASI PADA KOPERASI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING Wahdana, Aldi; Asrianda; Fikry, Muhammad
Journal of Information Technology (JINTECH) Vol. 7 No. 1 (2026): Februari 2026
Publisher : Prodi Teknologi Informasi UIN Ar-Raniry Bekerjasama dengan Pusat Penelitian dan Penerbitan LP2M Universitas Islam Negeri Ar-Raniry Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/jintech.v7i1.9511

Abstract

This study aims to analyze risks and determine mitigation priorities for information technology assets at the Melati Civil Servant Cooperative. The Simple Additive Weighting (SAW) method is used to determine mitigation priorities based on four main criteria: risk level, asset criticality, Return on Investment (ROI), and Total Cost of Ownership (TCO). This study involved eight information technology assets used to support the cooperative's daily operational activities. Research data was obtained through structured interviews with cooperative administrators to assess the probability and impact of possible risks, the criticality level of each asset, the cost of asset ownership during its useful life, and the resulting economic benefits. The obtained data was then processed using the SAW method to generate a preference value for each asset. The analysis results show that the Savings and Loans Data asset received the highest preference value of 0.876, making it the main mitigation priority. Furthermore, the Cooperative Member Data and Backup Storage Device assets were ranked next in priority. Based on these results, it can be concluded that the SAW method is able to assist cooperative administrators in determining risk mitigation priorities for information technology assets objectively and efficiently
Optimizing Multi-Time Notifications Using Q-Learning Muhammad Fikry; Muhammad Iqbal
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 3 (2022): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v3i.42

Abstract

In this research, we propose time optimization for notifications to assist users in remembering their actions by taking into consideration the amount of time it takes for them to respond and react. Using the Q-Learning algorithm, this proposal calculates when the best time to send notifications to users' smartphones in order to remind them of something important. The time at which the message is sent will be adjusted depending on the replies of prior users, which may be transformed into feedback at any time that is convenient. Notifications will be sent out, either repetitively or not, depending on the appropriate time for each individual, with the goal of ensuring that users do not forget about activities that they have planned. The results of testing our technique using the dataset show that it may be used to improve the time at which notifications are issued to recipients. It is possible to experiment with a variety of different times for the delivery of alerts in order to determine which of these periods is most successful for prompting users to take action. As a consequence of this, the algorithm is able to accommodate specific characteristics of individuals and find solutions to problems using a variety of standard operating procedures. Our proposal has the potential to successfully maintain the notification execution time at the intended level, which will prevent users from becoming concerned about the volume of notifications. Users who do not see the notification initially have the opportunity to do so at a later time step, which guarantees that activity data will still be collected.
Indoor Thermal Comfort Improvement of the Naturally Ventilated House in Tropical Climate, Indonesia Muhammad Iqbal; Muhammad Dastur; Muhammad Fikry
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 3 (2022): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v3i.48

Abstract

Two types of houses in North Aceh, Indonesia, are investigated in this study. Even though the hot and humid conditions throughout the year, most Indonesian stay in a house that uses natural ventilation due to energy poverty and economic conditions. Commonly, they rely on natural ventilation by opening windows to achieve thermal comfort in the indoor environment. Therefore, an on-site survey and questionnaire were performed on more than 240 occupants and 115 naturally ventilated houses to investigate thermal comfort performance between two houses based on thermal sensation vote (TSV) and thermal comfort vote (TCV). In addition, some questions related to thermal preference and body response are employed. This study also examines thermal comfort with a numerical simulations program called THERB for HAM, a coupled analysis software for heat, moisture, and air. The results show that the room comfort level was not optimal, where most occupants' feelings were warm and hot. However, type 1 is more comfortable than type 2, and simulation results confirm indoor environmental conditions. Furthermore, this study presents the adaptive behavior, where most occupants utilize the windows openings in the morning until noon and operate the fans during the night to modify indoor environment conditions to be more comfortable.
Innovative IoT-Based Automatic Gate System with RFID and Electro-Magnetic Lock for Secure Access David Fadlianda; Muhammad Fikry; Nunsina
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.884

Abstract

In this study, we developed an innovative IoT-based automatic gate system aimed at enhancing security and providing flexible access control. The system incorporates an ESP32 microcontroller with integrated Wi-Fi, enabling seamless remote access via mobile devices. It also features RFID technology for reliable physical access control when an internet connection is unavailable. To ensure user safety, an HC SR-04 ultrasonic sensor is implemented to detect obstacles during gate movement, preventing potential accidents. The security of the system is further reinforced by a dual-layer mechanism utilizing an electromagnetic lock (Emlock), which activates upon gate closure to prevent unauthorized access and deactivates when the gate opens. Experimental results indicate that the system effectively addresses the shortcomings of conventional gate control methods, delivering improved security, convenience, and safety for users. Performance tests confirm the reliable operation of both RFID and mobile control functions, with minimal delays observed in sensor response times. This comprehensive solution is well-suited for residential and commercial properties, offering a modern approach to automatic gate security.
Machine Learning Algorithms Comparison for Gender Identification Aldo januansyah. H; Muhammad Fikry; Yesy Afrillia
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.885

Abstract

Abstract. In this study, we presents a comprehensive analysis of gender identification methods utilising eight distinct classification models: K-Nearest Neighbors (KNN), Naive Bayes, Decision Tree, Random Forest, Logistic Regression, XGBoost, Support Vector Machine (SVM), and Neural Network. Gender identification is a critical task with significant applications in marketing, social analysis, and security systems, necessitating the exploration of various methodologies to achieve optimal performance. The dataset employed in this research underwent normalisation using the Min-Max scaling technique, which enhances the performance of classification models by ensuring that all features contribute equally, particularly when the data exhibits varying ranges of values. The results reveal that the K-Nearest Neighbors (KNN) model significantly outperformed the other models, achieving an impressive accuracy of 0.9758 with a support of 951, underscoring the effectiveness of the KNN algorithm in gender identification tasks and establishing it as a reliable choice for applications requiring high accuracy. Furthermore, the study emphasises the critical importance of selecting appropriate models in machine learning tasks and the substantial impact of data normalisation on model performance. Overall, this research provides valuable insights into the KNN algorithm, demonstrating its ease of implementation and exceptional effectiveness in achieving high precision in gender identification tasks, with implications for future research and practical applications across various fields. Keywords : classification models; data normalisation; gender identification; K-Nearest Neighbours; machine learning.
Research Results Boardify A Comprehensive Approach to Academic Task Management with Push Notifications and Scheduling Optimization Faiz Syukri Arta Faiz; Muhammad FIkry; Rini meiyanti
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.910

Abstract

Abstract. This study explores the development and implementation of Boardify, an integrated academic task management system designed to enhance the thesis submission process for Informatics students. The system incorporates features such as task management, status tracking, file submission, and seamless communication between students and supervisors, aiming to streamline the entire workflow. By leveraging Firebase Cloud Messaging, Boardify enables real-time push notifications, ensuring timely updates and reducing delays. Furthermore, the implementation of scheduling algorithms optimizes notification timing based on probabilistic factors, enhancing the efficiency of the system. A comparative analysis was conducted between Boardify and similar task management platforms, focusing on aspects such as website load speed, feature functionality, and user experience. The system's performance was further evaluated by measuring the average time taken by supervisors to review student submissions. Results indicate that Boardify significantly improves the efficiency of the thesis submission process, enhancing transparency and facilitating effective communication. The findings underscore Boardify's potential as a powerful tool for academic institutions, offering a promising approach to optimizing educational task management and promoting the advancement of educational technology. Keywords: Boardify. Probability Scheduling, Push Notifications, Informatic, Task Management System
IoT-Integrated Home Energy Management System with Real-Time Monitoring and Solar Panel Optimization Mhd Firza Ryzaaldy; Muhammad Fikry; Said Fadlan Anshari
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.949

Abstract

In this study, an IoT-integrated Home Energy Management System (HEMS) was developed using solar panels as the primary energy source. The system employs an ESP32 microcontroller as the core controller, equipped with DHT22, LDR, and INA219 sensors to monitor temperature, humidity, light intensity, voltage, and current. Real-time sensor data is presented on a web interface, allowing users to monitor system status and control devices like fans and lights either manually or automatically. The system demonstrated stable performance with a control response time of under one second and effective energy management aligned with environmental conditions. However, a key limitation was the limited capacity of the 10 Wp solar panel, particularly during low sunlight periods. To address this, enhancements such as improved load management or increased solar panel capacity are recommended. The system successfully implemented real-time monitoring and automated control, activating the fan at temperatures above 30 degrees Celsius and turning on lights when light intensity is below 1000 lux. This research highlights the potential of IoT technology in achieving efficient and sustainable home energy management.
Enhancing Academic Security with RFID-Based Smart Locks and Real-Time Attendance Tracking System Muhammad Al Imran; Muhammad Fikry; Sujacka Retno
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.950

Abstract

In this study, we propose a novel RFID-based smart lock system integrated with real-time attendance tracking to enhance academic security. Traditional security methods such as mechanical locks and manual attendance systems are prone to various limitations, including lost keys, falsification, and lack of automatic tracking. Our system utilizes E-KTP cards as RFID identification tools, supported by Internet of Things (IoT) technology, to provide automated door access and efficient attendance monitoring. The implementation results demonstrate a high accuracy rate of 99.5% in reading E-KTP cards, with an average response time of 850 Ms and a 99.5% uptime during a 30-day testing period. The system can handle up to 40 access requests per minute during peak hours. Additionally, it reduces access time by 91%, lowers errors from 5% to 0.2%, cuts operational costs by 60%, and decreases maintenance time by 75%. Security is reinforced through dual encryption using the Vigenère and Bcrypt algorithms, ensuring no security breaches over six months. The dashboard provides real-time monitoring, and the automated attendance system reduces human error, integrating seamlessly with academic databases for user verification and schedule management. This research demonstrates the effectiveness of RFID and IoT technologies in modernizing and securing academic environments.
Implementation of the Naïve Bayes Method in a Web-Based Fish Species Classification System Rizki Suwanda; Muhammad Fikry; Said Fadlan Anshari
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The current fish resources are abundant, and the discovery of new species has increased the variety of fish in the ocean. These fish are categorized into three groups: demersal, pelagic, and reef fish, each with unique characteristics of their respective groups. The manual classification process for large datasets requires a long time and involves complex procedures. With the advent of data and information technology, it is now possible to recognize and identify several fish species found in the ocean, which can be classified into the three groups. To simplify this classification process, a web-based system has been developed to classify fish into these groups. The data to be processed in this research will be classified using the Naive Bayes method to address this issue. This technique utilizes large datasets to extract information that was previously unknown or inaccessible, and it can provide accurate information for various purposes. The data for this study will be collected from various internet references and direct data obtained from fish landing sites (TPI) in Lhokseumawe and North Aceh. Additionally, a literature review method will be used to complement the data analysis process. The development of the web-based system will be implemented to facilitate the classification of fish species based on the existing data.
The Influence of Google Lens-Assisted Discovery Learning Model on Improving Students' Mathematical Connections Hidayatsyah Hidayatsyah; Muhammad Fikry; Said Fadlan Anshari; Sudirman Sudirman
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze the effect of the Discovery Learning learning model assisted by Google Lens on improving students' mathematical connections. This study used a quasi-experimental method with a Non-equivalent Control Group Design involving high school/vocational high school students in Lhokseumawe City. The sample consisted of an experimental group using Google Lens and a control group using conventional learning. The results showed a significant increase in mathematical connection skills in the experimental group compared to the control group. Students' perceptions of the use of Google Lens were also positive, with indicators of increased learning motivation and engagement. These findings provide implications for the implementation of technology in mathematics learning.
Co-Authors Aldo januansyah. H Amalia, Iklasni Annisa Helmina Aprian Gigin Prasetia Ar Razi Asrianda Asrianda Asrianda, Asrianda - Aynun, Nur Azzahra Iskandar, Farah Bustami Bustami Bustami Chrisnata Manihuruk Cut Ita Erliana Dahlan Abdullah David Fadlianda Dessayani Putri Dyah Ika Rinawati Ella Suzanna Erwanda, Ade Putra Eva Darnila Fadlisyah Fadlisyah Faiz Syukri Arta Faiz Fajar Rivaldi Chan Fajriana, Fajriana Faradilla, Cut Meutia Febi Yanto Gusti, Siska Kurnia Hafizh Al Kautsar Aidilof Hanif, Wan Muhammad Hasan Tahir Helmi Naluri Herman Fithra Hidayatsyah Hidayatsyah Hizamrul jaen Ibnu Khaldun Ima Pratiwi Imam Rosadi Irfan Sahputra Iskandar, Fahra Azzahra Ismail Ismail Khaidar, Al Khairina, Jikti Kurnia Amanda, Destiara Kurniawati Kurniawati Lidya Rosnita Luthvy Ilhamdi M Ishlah Buana Angkasa Maharani, Silfa Mhd Firza Ryzaaldy Muchlis Abdul Muthalib Muhammad Al Imran Muhammad Dastur Muhammad Iqbal Muhammad Iqbal Muhammad Sapriadi Muhammad Yani, Muhammad Mukhlis Mukhlis Muqarrabin, Khalis Al Nazwa Aulia NELI SUSANTI, NELI Nunsina Nura Usrina Nurdin Nurdin Rahma, Mutiara Ramadhani, Ramadhani - Rauzana, Rauzana - Rifkial Iqwal Rini meiyanti Risawandi, Risawandi Rizal S.Si., M.IT, Rizal Rizki Suwanda Rozzi Kesuma Dinata Safwandi Safwandi Said Fadlan Anshari Sari, Cut Jora Sembiring, Vivi Dista Br Silfa Maharani Br Padang Siti Hajar Subhan Hartanto Subhan Hartanto Sudirman Sudirman Sujacka Retno Sukma Rizki Taufiq Taufiq Taufiqurrahman Taufiqurrahman Tejas Shinde Umar Khalil Wahdana, Aldi Yani, Muhamamd Yesy Afrillia Yesy Afrillia Yusra, Yusra Zahratul Fitri Zara Yunizar zulfhazli zulfhazli