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LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics
Published by Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan
ISSN : 30634504     EISSN : 30629098     DOI : https://doi.org/10.28918/logiclink.v1i1
Core Subject : Science,
Computer Science & IT
LogicLink : Journal of Artificial Intelligence and Multimedia in Informatics is free of fee, open access, and peer-reviewed journal, published by Informatics Department - UIN K.H. Abdurrahman Wahid Pekalongan Indonesia, which is a dissemination medium for research results from scientists and engineers in the Artificial Intelligence and Multimedia. LogicLink is a biannual journal issued in June and December with the objectives to explore, develop, and elucidate the knowledge of computational intelligence or Multimedia to keep practitioners and researchers informed on current issues and best practices, as well as serving as a platform for the exchange of ideas, knowledge, and expertise among technology researchers and practitioners. LogicLink : Journal of Artificial Intelligence and Multimedia in Informatics focuses on issues of Computational Intelligence, such as : 1. Artificial Intelligence 2. Information Security 3. Image Processing 4. Data Mining 5. Decision Support System 6. Mobile Computing 7. Expert System 8. Multimedia, 9. and other topic related to computer technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol. 2 No. 2, December 2025" : 8 Documents clear
Aplikasi Web Pemesanan Makanan Berbasis QR Code untuk Area Food Court Falah, Muhammad Syahrul
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.11650

Abstract

The use of QR codes in food ordering systems is increasingly being used in restaurants or F&B (Food and Beverage) as a practical and efficient solution. This article discusses the planning of a web-based application prototype that integrates QR codes at each table in the food court, which allows buyers to access digital menus from various F&B tenants and place orders on the website application. This web application is also friendly to smartphones/mobile phones because it does not install additional applications and only uses a web browser and does not need to purchase hosting services because it uses the local/wi-fi network available at the food court. The purpose of this development is to improve the existing QR Code ordering system by adding table personalization features to the food court, ordering efficiency, and integration of all tenants in one platform.
Approach to Zero Trust Security Implementation to Enhance Internet of Things Infrastructure Security Rusdan, Muchamad; Ramlan, Isak
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.12634

Abstract

The heterogeneity and resource constraints of Internet of Things (IoT) devices render traditional perimeter security inadequate. This study proposes a Zero Trust Security (ZTS) framework for IoT infrastructures that integrates a novel dynamic policy engine with continuous authentication and AI-assisted anomaly detection. The framework was evaluated in a simulated IoT environment using the TON_IoT dataset. Experimental results demonstrate that the proposed model achieved a 92.5% detection accuracy, reduced average response latency to 1.76 seconds, and decreased unauthorized access attempts by 87.1%. The key novelty lies in the architecture's context-aware feedback loop, where anomaly findings directly and adaptively inform access policies in real-time, a mechanism not extensively explored in prior ZTS models for IoT. These findings confirm that integrating ZTS with intelligent analytics significantly enhances IoT security resilience. This framework offers a practical blueprint for implementing robust, context-aware security in large-scale IoT applications, such as smart cities and industrial automation.
Smart System Kumbung Jamur Tiram dengan IoT dan Sensor DHT11-LDR Rusito; Rahmawan, Andika Bagas
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.12745

Abstract

Oyster mushroom cultivation requires stable environmental conditions, particularly in terms of temperature, humidity, and lighting. Traditionally, the management of mushroom houses has been carried out manually, which often leads to inefficiency and production failures. This study aims to design and implement a Smart System for oyster mushroom houses based on the Internet of Things (IoT) using DHT11 and LDR sensors. The research employed the Research and Development (R&D) method with six main stages, namely needs analysis, planning, initial product development, limited trials, product revision, and product testing. The system was designed using NodeMCU as the main controller, with the DHT11 sensor to measure temperature and humidity, and the LDR sensor to detect light intensity. Data are displayed through an LCD and transmitted in real time to an Android application. The design validation test obtained a score of 30, categorized as “Good,” while the limited user trial involving 12 respondents achieved an average score of 35.16, categorized as “Very Good (Valid).” The system automatically activates the fan when the temperature exceeds 28°C, turns on the water pump when humidity is low, and switches on the lamp when light intensity is insufficient. Therefore, this system can assist mushroom farmers in maintaining optimal environmental conditions in real time and automatically, which is expected to improve both the quality and productivity of oyster mushroom cultivation.
Klasifikasi Penyakit Pada Buah Jambu Biji Menggunakan Algoritma Yolo V5 Rezika, Nadiya; Elmayati; Lestari, Novi
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.12942

Abstract

Horticultural agriculture, especially guava (Psidium guajava), has great economic potential in Indonesia. However, productivity often declines due to fruit disease attacks, which are still manually diagnosed by farmers. This study aims to develop an artificial intelligence-based guava disease classification system using the You Only Look Once (YOLO) version 5 algorithm. The dataset consists of 600 images divided into three disease classes: Phytophthora, Styler and Root, and Scab. Data were collected through field documentation, then preprocessed and augmented using Roboflow. The dataset was divided into 70% training data, 20% validation, and 10% testing. The YOLOv5 model was trained using Google Collaboratory and consistently evaluated using the Confusion Matrix and accuracy, precision, recall, and F1-score metrics. The test results showed that the model achieved an accuracy of more than 95% with high precision, recall, and F1-score values ​​for each disease class. This proves that YOLOv5 is effective for real-time guava disease detection. This research contributes to the application of artificial intelligence technology to help farmers make early diagnoses quickly and accurately, thereby reducing the risk of reduced crop yields.
Rancang Bangun Sistem Smart Posbindu Peyakit Tidak Menular (PTM) Berbasis Android untuk Deteksi Dini dan Monitoring Kesehatan Masyarakat Maulana, Much. Rifqi; Royanti, Nur Ika; Winoto, Ratno Aji
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.12989

Abstract

The rapid increase in internet usage (62%) and mobile phone ownership (90%) in Indonesia indicates the significant potential of digital technology to support health services. The Integrated Non-Communicable Disease Health Post (Posbindu PTM) in Mojo Village plays an essential role in early detection and community health monitoring. However, its implementation still faces several challenges, including manual schedule announcements, data recording errors and loss risks, as well as limited dissemination of health information and education. This study aims to design and develop a mobile Smart Posbindu PTM application based on Android as a digital solution to enhance the effectiveness of Posbindu services. The application was developed using the Dart programming language with the Flutter framework and Supabase as the database. Its main features include schedule notifications, digital data recording, fast and accurate reporting, health history monitoring, and educational information related to non-communicable diseases. The system development method used in this study is the Waterfall model, consisting of requirements analysis, system design, implementation, testing, and maintenance stages. Data were collected through interviews with midwives and Posbindu cadres, direct observation, and questionnaires distributed to Posbindu participants. The application was tested using User Acceptance Test (UAT) methods to ensure functionality and user satisfaction. The results show that the Smart Posbindu PTM application was successfully developed and functioned properly according to user needs. This application provides significant benefits by improving data management efficiency, accelerating reporting, facilitating health record monitoring, and supporting health education and information accessibility for the community.
Pengembangan Sistem Informasi Peminjaman Fasilitas Kampus Berbasis Natural Language Processing dengan Metode Extreme Programming Maulana, Mohammad Reza; Kamal, Muhammad Rikzam; Nugroho, Agus Susilo; Tamamudin
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.13024

Abstract

The facility (room and equipment) loan system within the Fakultas Ekonomi dan Bisnis (FEBI), Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan is still carried out manually, often using online forms and direct communication with staff. This manual process causes various problems, including schedule conflicts, asynchronous data, and a lack of transparency regarding space and asset availability. This study aims to develop a Natural Language Processing (NLP)-based Room and Equipment Loan Information System that is integrated, transparent, and can work in real-time. The system development method used is Extreme Programming (XP), which was chosen because of its adaptive, flexible nature, and focus on rapid iteration and continuous feedback from users. The XP stages include planning, design, coding, and testing. The information system is designed using the Laravel framework supported by a PostgreSQL database. The system's main functionality includes online loan applications by Borrowers, automatic validation of schedule conflicts, and approval by the Admin/Superadmin. The results show that this system is able to simplify processes, minimize schedule conflicts, and increase efficiency and transparency in the management of faculty assets.
English Predicting Student Dropout in E-Learning Using Simple Machine Learning and Explainable Data Analysis Ibrahim Ahmad, Aliyu; S.A. Aliyu; A.M. Abdullahi; D.A Nugroho
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.13116

Abstract

Online learning allows a lot of flexibility and accessibility, but the issue of student dropout becomes one of the key problems. Much of the research that has been done to predict dropout using complex machine learning methods has not been interpretable, and many of these methods are hard to implement in practice, especially in resource constrained environments. This research closes this gap by presenting a simple and explainable machine learning method of predicting early dropout. Students in several universities were surveyed on the frequency of attendance, quiz performance, completion of assignments, satisfaction with learning, and hours spent studying per week. Because there were only a few real dropout cases, a controlled synthetic data augmentation method was used to demonstrate and train the model. The use of Logistic Regression and Decision Tree classifiers was used to predict the risk of dropout. The accuracy of both models was 87.5% with the most effective indicators being learning satisfaction, attendance, and prior consideration of dropout. This research is considered new because it focuses on the simplicity and interpretability of models rather than the complexity of creating early warning systems to predict the dropout of students, showing that they are not required to be complex or made out of heavyweight models to perform well. Even though the findings are merely exploratory due to limitations of the datasets, the results show that even simplistic models might be used to assist educators in identifying at-risk learners and incorporating prompt intervention measures.
A Comprehensive Study of Information Security Principles, Threats, and Organizational Protection Measures Paiman, Mukhtar Ahmad; Afghan, Serajulhaq; Himmat, Abdul Karim
LogicLink Vol. 2 No. 2, December 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i2.13154

Abstract

Information security has become a vital specification and element in modern digital and electronic environments as organizations, governments, and individuals at an accelerating rate rely on information systems to fulfill indispensable operations. The rapid growth of digital communication, cloud computing, mobile technologies, and the Internet of Things (IoT) has augmented the volume of data generated and transmitted, making it more susceptible to cyber threats. Information security underscores on protecting data confidentiality, integrity, and availability through a synthesis of technical, organizational, and human-centered measures. This abstract provides summary of key elements of information security, examines major emerging threats, and highlights the importance of embracing comprehensive security frameworks. Cyberattacks such as ransomware, phishing, Distributed Denial of Service (DDoS), and social engineering have become more advanced, addressing system susceptibilities and human behavior. These attacks can result in financial loss, data breaches, reputational damage, and operational disruption. As a result, organizations must carry out robust security frameworks, including encryption, access control mechanisms, multi-factor authentication, intrusion detection and prevention systems, firewalls, and progressive system tracking. In addition, the integration of artificial intelligence and machine learning has enhanced cybersecurity capabilities by enabling automated threat detection and predictive analysis. However, besides technological advancements, human factors remain a major cause of security breaches. Employee negligence, weak passwords, lack of awareness, and susceptibility to social engineering attacks continue to undermine security efforts. Therefore, effective information security needs not only advanced tools but also strong organizational policies, regular training programs, and a special way of security awareness. Overall, information security is a flexible and evolving field that requires a nonstop adaptation to new threats and technologies. A holistic approach that brings togethar technical solutions, human-centered techniques, and regulatory compliance is essential for safeguarding digital assets and ensuring the resilience of information systems in an increasingly interconnected world.

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