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Media of Computer Science
Published by CV. Digital Innovation
ISSN : 30634822     EISSN : 30634997     DOI : https://doi.org/10.69616/mcs
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science
Media of Computer Science (MCS), a two times annually provides a forum for the full range of scholarly study . MCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can be built to industrial applications. The topics include but not limited to : fuzzy logic, neural network, genetic algorithm and evolutionary computation, hybrid systems, adaptation and learning systems, distributed intelligence systems, network systems, human interface, biologically inspired evolutionary system, artificial life and industrial applications. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 18 Documents
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Augmented Reality Integration for Smart Campus Experience at USN Kolaka Muarif, Amar; Sari, Jayanti Yusmah; Bantun, Suharsono
Media of Computer Science Vol. 1 No. 2 (2024): December 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i2.205

Abstract

In an effort to enhance promotion at the Universitas Sembilanbelas November (USN) Kolaka, an Augmented Reality (AR) application has been developed incorporating the smart campus concept. This application is designed to provide interactive 3D visualizations of campus facilities, allowing prospective students and visitors to explore the infrastructure virtually. It has undergone extensive black box testing across various devices, demonstrating high technical reliability with key functionalities operating stably. Media expert evaluations gave an average score of 4.9, reflecting a very high level of satisfaction with its design and functionality. Moreover, a usability evaluation conducted with students noted that 80% of them rated it as excellent, describing the application as user-friendly and engaging. This success underscores the potential of AR applications in enriching campus experiences, reinforcing USN Kolaka's image as a modern and technologically adaptive educational institution, and opening opportunities for its use in broader campus promotion and marketing efforts.
Design Of A Geographic Information System For Mapping Crime-Prone Areas In The City Of Pinang Web-Based Kurniawan, Ardi Ari; Aji, Agung Prasetyo; Firmanto, Tudi; Fadhil, Ahmad
Media of Computer Science Vol. 1 No. 2 (2024): December 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i2.206

Abstract

One of the information systems that can help map an area is a Geographic Information System (GIS). GIS helps researchers, managers, and decision makers in solving problems, one of which can be implemented in mapping crime-prone areas. Crimes that often occur in the jurisdiction of the Kota Pinang Police Station are persecution and beatings, bullying, theft, fraud and so on. Because there is no GIS that can map existing crime-prone locations, so that people are still looking for criminal location information through the nearest police station and the police are still recording criminal cases manually. So a geographic information system was built that can map crime-prone locations in the Kota Pinang Police Station using the Rapid Application Development (RAD) method. The main feature of this geographic information system is to display the number of crime points based on the year and the location of crime-prone areas. The test results obtained, recorded 58 types of crime at 12 crime-prone points in the Kota Pinang area in 2024. With this web-based Geographic Information System, the police can easily record crime-prone areas, as well as the general public who want to know the crime-prone areas by simply looking at the data contained in this system.
Identification of Leaf Spot Diseases in Eggplant Using Gray Level Co-Occurrence Matrix (GLCM) Feature Extraction and Support Vector Machine (SVM) Classification Pahlevi, Reza; Setiawan, Andika; Kesuma, Rahman Indra
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.202

Abstract

Eggplant (Solanum melongena L.) is one of the widely cultivated vegetables in Indonesia, belonging to the Solanaceae family. This plant is susceptible to several diseases, one of which is leaf spot disease. Leaf spot disease, caused by the pathogenic fungus Alternaria sp., is characterized by irregularly shaped brown spots with a diameter of approximately 0.5 cm. To address this issue, a digital image processing-based system was developed to identify whether the plant is infected. The proposed system employs feature extraction using the Gray Level Co-Occurrence Matrix (GLCM) combined with the Support Vector Machine (SVM) classification algorithm. The study utilized a dataset of 100 images for training and 50 images for testing. The highest achieved accuracy was 100%, obtained by applying Laplace of Gaussian (LoG) edge detection along with Linear Kernel and Polynomial Kernel SVM classifiers.
Recommendation of Assistant Lecturer for Advanced Programming Course using Fuzzy Tahani Amaliah, Annisa Shela; Sulmadani, Fitriah; Khaida, Fatihah; Adiba, Fhatiah; Nasrullah, Asmaul Husna; Munawir, Munawir
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.224

Abstract

The recruitment of teaching assistants for certain courses is a regular activity conducted during specific periods to meet the needs of teaching and learning both inside and outside the classroom. The main objective of the recruitment is to obtain the best teaching assistants who can perform their duties optimally. However, selecting teaching assistants based solely on grades and GPA without considering other criteria is ineffective and subjective. This research proposes the use of the Fuzzy Tahani method in a recommendation system to select teaching assistants for the Advanced Programming course. The aim is to develop a recommendation system for selecting teaching assistants using the Fuzzy Tahani method and to improve objectivity and accuracy in the decision-making process for selecting teaching assistants by considering four criteria: grades, recommendations, availability, and students' GPA. This recommendation system approach is necessary to minimize subjectivity and ensure that the selected teaching assistants can effectively carry out their duties. The result obtained is a recommendation system for selecting teaching assistants, where there is a high level of accuracy between the system's results and the calculation results in Excel, with a difference of 0.00 between them.
A Decision Support Model for Scholarship Recipient Selection Based on Tsukamoto Fuzzy Logic Muhtadi; Aksa, Muhammad; Naoval, Ahmad; Adiba, Fhatiah; Nasurllah, Asmaul Husna
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.225

Abstract

This study proposes a decision support model for scholarship recipient selection based on the Tsukamoto fuzzy logic method to overcome the inefficiencies and subjectivity inherent in manual selection processes. The model incorporates three key criteria: Grade Point Average (GPA), parents’ income, and number of dependents. Experiments were conducted using a dataset of 25 students obtained from a public Kaggle repository. The model employs fuzzification, rule formulation, and defuzzification to compute a final decision score for each applicant. The experimental results demonstrate that the proposed model achieves an accuracy rate of 92%, indicating its effectiveness in supporting objective and efficient scholarship selection decisions.
Expert System For Identification Of Symptoms And Diseases In Lobsters Using The Backward Chaining Method Yiyuni; Miftachurohmah, Nisa; Paliling, Alders; Mardiawati; Sya'ban, Kharis
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.232

Abstract

Lobster is a high-value fishery commodity widely cultivated, including in Watorumbe Bata Village. However, diseases attacking lobsters are often difficult for farmers to identify early, leading to economic losses due to delayed treatment. This study aims to develop an expert system to identify lobster symptoms and diseases using the backward chaining method. This method enables the system to reason logically and systematically from disease hypotheses to symptom facts. Data collection was conducted through observation, interviews with lobster experts, and literature study. The system development followed the Waterfall model, comprising analysis, design, coding, and testing phases. The implementation results show that the system can diagnose diseases based on symptom inputs and provide information including disease name, cause, solution, and likelihood level. Black-box testing confirmed that all system functions operated properly, while accuracy testing using 20 sample data showed a system accuracy rate of 90%. These results indicate that the expert system using the backward chaining method is effective in assisting farmers to identify lobster diseases more quickly and accurately, thus supporting the sustainability and productivity of lobster farming.
Analysis and Implementation of Bandwidth Management on Wireless Local Area Network Internet Using the PCQ Method at SMAN 1 Mawasangka Tengah M, Nurhayati; Al Jum'ah, Muhammad Naim; Mardianto
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.234

Abstract

With the rapid development of internet network technology, bandwidth management has become crucial, especially in networks with many users SMAN 1 Mawasangka Tengah has a Wi-Fi network used by teachers and students, but the network often experiences disruptions due to the lack of proper bandwidth management. This research aims to analyze and implement bandwidth management using the Per Connection Queue (PCQ) method to automatically and evenly allocate bandwidth to all users. Testing was conducted by comparing network performance before and after the implementation of bandwidth management, with QoS tests including throughput, delay, and packet loss. The results show that after implementing the PCQ method, the network's performance became more stable with a more even distribution of bandwidth. This is proven by an increase in average throughput for download activities from 8,690 kbps to 12,316 kbps, and video streaming from 986.33 kbps to 1,607.33 kbps. Delay decreased from 1.1 ms to 0.71 ms for downloads, and video streaming from 9.85 ms to 5.02 ms. Packet loss also decreased from 4.43% to 0% for downloads, and video streaming from 7.73% to 0.1%. In conclusion, the PCQ method is effective in addressing network stability and bandwidth management issues at SMAN 1 Mawasangka Tengah.
PRAKERIN Monitoring Web-Based Information System with QR Code Implementation at SMK Negeri 3 Kolaka Ariani, Irma; Adawiyah, Rabiah; Sagala, La Ode Hasnuddin S; Zainuddin, Noorhasanah; Pradipta, Anjar; Pasrun, Yuwanda Purnamasari
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.235

Abstract

Student attendance monitoring during industrial internship programs (Prakerin) is still commonly carried out manually, leading to potential data inaccuracy, reporting delays, and inefficiency in school administration. The issue becomes more complex when a large number of students are placed in different locations, making it difficult for supervising teachers to monitor attendance in real time. This study aims to design and develop the PRAKERIN Monitoring Web-Based Information System with QR Code Implementation at SMK Negeri 3 Kolaka. The system was developed using the Waterfall model, which consists of requirement analysis, system design, implementation, and testing. Black-box testing confirmed that all system functions operated validly as intended. External evaluation using a Likert-scale questionnaire with 15 respondents indicated an average satisfaction rate of 82%, with 78% agreeing that the interface facilitated attendance access, 80% stating that the system improved real-time tracking, and 86% confirming that automated reporting supported evaluation. The findings demonstrate that the system is feasible, effective, and capable of enhancing transparency, accuracy, and efficiency in Prakerin monitoring.

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