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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 The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.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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Expert System for Determining Diseases and Pests in Seaweed Using Forward Chaining (Case Study : Watorumbe Village, Mawasangka Tengah) Asriani, Ika; Muchtar, Mutmainnah; Ismail, Rima Ruktiari; Paliling, Alders; Sya'ban, Kharis; Karim, Rahmat
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.175

Abstract

Seaweed is a marine organism that plays a crucial role in both ecosystem and economy. However, it often faces attacks from diseases and pests that can jeopardize the productivity and sustainability of the seaweed industry. Hence, the development of an expert system to diagnose seaweed diseases and pests becomes imperative. This research aims to develop an Expert System for Determining Diseases and Pests in Seaweed using the Forward Chaining method, with a case study conducted in the Watorumbe Village, Mawasangka Tengah Sub-district, Southeast Sulawesi. The Forward Chaining method is employed to identify symptoms appearing in seaweed and determine potential diseases or pests. Testing is carried out with 30 data samples compared against expert diagnoses, resulting in an accuracy rate of 90%. Therefore, this system has the potential to assist seaweed farmers in diagnosing diseases and pests more quickly and accurately, thereby enhancing the productivity and sustainability of seaweed cultivation efforts.
Chicken Cage Incubator Cooling Control System Using Fuzzy Logic Agni Dhewa, Oktaf; Aldiasa Pangestu Aji
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.177

Abstract

This research examines the impact of prolonged cooling time in the incubator of chicken coops on the well-being of chicks during the incubation process. Poorly maintained temperature conditions can jeopardize the health of chicks and diminish the overall productivity of poultry farming. To address this issue, the study develops an efficient temperature control system by integrating a peltier as the main cooling component and fuzzy logic control combined with a DC fan. Experimental results indicate that the developed system is capable of providing a robust response to temperature changes in the chicken coop incubator, with transient response values meeting the expected criteria. Consequently, this temperature control system holds the potential to enhance the performance of chicken coop incubators and reduce the risk of chick mortality during the incubation process. This research serves as an initial step in advancing better temperature control for chicken coop incubators in the future.
Comparative Analysis of Google Vision OCR with Tesseract on Newspaper Text Recognition Prakisya, Nurcahya Pradana Taufik; Kusmanto, Bintang Timur; Hatta, Puspanda
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.178

Abstract

Optical Character Recognition (OCR) is a technique used to convert image files into machine-readable text. There are two Optical Character Recognition (OCR) algorithms that are currently well known and widely used, namely Google Vision's Optical Character Recognition (OCR) and Tesseract. The purpose of this study is to compare the Optical Character Recognition (OCR) algorithms of Google Vision and Tesseract so that people can more easily find out which algorithm is the right one to implement on the system they are going to build. The method used in this research is Research and Development (R&D) with the stages of literature study, needs analysis, dataset collection and expansion, architectural design development and application modeling, system implementation, testing and evaluation, drawing conclusions. To be able to determine the level of accuracy, precision and sensitivity of each algorithm, this research uses the Confusion Matrix formula. The results of this study conclude that Google Vision's Optical Character Recognition (OCR) algorithm is superior to Tesseract because the level of accuracy, sensitivity, and precision is superior to Google Vision.
Wi-Fi Optimization with Wireless Mesh Networks Arya, Primadona; Febriyan Priambodo, Dimas
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.179

Abstract

Wifi is one technology that can still penetrate into several services around us. The need for additional services in the form of our wifi trigger to provide solutions to improve quality, security and even coverage. By using an ordinary single access point, the wifi performance is not optimal because of the interference between signals and the strength or in between with wifi repeater. Access point need more power to extend range. With a mesh network, the performance of the access point can be maximized. This research shows that mesh implementation can increase from -20dB bellows to above -50dB or more than 100%. With mesh network wifi can be seen in single SSID different with repeater that has own coverage and setting. Mesh network connecting all client seamless to near node in single network SSID.
Identification of Fatigue from Facial Expressions Using Transfer Learning Manurung, Jefri; Setiawan, Andika; Cahyo Untoro, Meida
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.180

Abstract

Initially, teaching and learning activities were carried out face-to-face in the provided room, but now they have switched to online. Online learning has an impact on student learning disengagement, which is known through indicators of aspects of emotional exhaustion, physical fatigue, cognitive fatigue, and loss of motivation. Besides, the teacher must provide the material that has been provided. The teacher must also pay attention to all students who are participating in the online learning. This can be overcome by a system that can detect student disengagement using a camera device. The system works by scanning the direction of students' faces and views using OpenCV technology and Transfer Learning methods. Using context, facial expressions, and heart rate can be used to recognize student disengagement. However, with the widespread availability of cameras, it is easier to identify disengagement using facial expressions. The facial expression recognition system in this study will use the FER2013 dataset and Transfer Learning method. Facial expression recognition using the FER-2013 dataset and Transfer Learning method has a reading accuracy rate of 68% in 25 epochs. Then, after being implemented as an impression parameter in the disengagement identification system using 7 scenarios, the accuracy rate is 83.33%, precision is 100%, recall is 75%, and the f1-score is 85.71%.
Enhanced Laptop Recommendation System Using Tsukamoto Fuzzy Logic Nasrullah, Asmaul Husnah; Adiba, Fhatiah; Anastasia, Tezza; Farghina, Syakira Ayma; Akbar, Muh.
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.186

Abstract

One of the most popular and rapidly growing needs among the general public is laptops. Currently, there are many types of laptops with varying features, and not everyone knows the advantages and disadvantages of each type. The purpose of this research is to develop and build a Fuzzy inference system that applies the Tsukamoto method. This is to address issues in providing unclear or inaccurate services to customers during the laptop sales process. By developing a recommendation system that can provide guidance or suggestions in purchasing a laptop based on interest and needs in searching for references, and the type of laptop that meets the criteria. The decision to purchase a laptop uses parameters such as screen size, RAM capacity, SSD capacity, and price. The implementation of the Fuzzy Tsukamoto method for providing laptop purchase recommendations is able to give good recommendations.
A Dempster-Shafer Approach for Uncertainty Management in Diagnosing Eye Diseases Aji, Luthfi Priyanto; Suprapto
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.v1i2.200

Abstract

Expert system can be used as a consultant that could give an advice to users as well as an assistant to experts. One way to help diagnose eye disease is to create an expert system as a media consultation therefore the eye disease could be identified based on the symptoms. Expert system in this research is built using using forward chaining search method and dempster shafer method to handle the uncertainty. The dempster shafer method is a non monotonic method that is used to look for inconsistencies due to the addition or subtraction of the new facts that will change the existing rules. This research aims to handle the uncertainty of the diagnose eye disease with increase the accuracy of the system in determine the level of confidence of a disease that has been generated by the expert system. The expected results of this research is to provide a media consultation that is able to diagnose eye diseases and increasing the level of system confidence to diagnose an eye disease. This expert system is tested by comparing diagnose results from an expert and the comparasion results show accuracy rate is 96%.
Design and Implementation of Update Script in the IoT-Based Smart Indoor Farming System Module at PT Inastek Using Over-the-Air Programming Aditya, Tomi; Dhewa, Oktaf Agni
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.v1i2.201

Abstract

Extreme climate change significantly impacts Indonesia’s agricultural sector, a country with a large agrarian economy. Reduced crop productivity and in- creased risk of pest infestations threaten national food security. This study aims to develop a smart indoor farming system based on the Internet of Things (IoT) to enhance agricultural resilience and competitiveness through efficient technology. The method involves designing a system that integrates hardware and software, applying Over-The-Air (OTA) technology to update firmware on the ESP32 microcontroller. The system includes sensors, actuators, and a Human Machine Interface (HMI) that allows real-time monitoring and con- trol of plant growth conditions. Testing and validation were carried out to ensure the system’s reliability and stability. The results show that the in- tegration of OTA technology into the smart indoor farming system enables efficient firmware management, reducing the need for physical intervention, and improving flexibility in system maintenance. This system enhances the efficiency of managing plant growth in indoor environments and supports con- tinuous operational adjustments to dynamic conditions.
Evaluation Of Fuzzy C-Means Method For District Clustering Nasrullah, Asmaul Husnah; Fajar, Andi Muhammad; Taufiq, Muhammad Aqsha; Rahmat, Nuzulul; Adiba, Fhatiah
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.v1i2.203

Abstract

This study analyses the use of Fuzzy C-Means algorithm to cluster districts in South Sulawesi based on the education level of the population. Two distinct groups were found with several districts falling into each group after 17 iterations to reach the optimal solution. The clustering results were visualised with a point spread graph. The Fuzzy C-Means algorithm was executed using Python with certain parameters. The research aims to improve the quality of education with proper resource allocation and identification of districts based on the highest education. The data used includes education indicators and district minimum wage. The results are expected to provide input for a more targeted education policy in South Sulawesi. Fuzzy C-Means algorithm is effective for analysing and clustering education data in education policy decision making.
The Determination of Electronic Goods Inventory at Rahmah Store Using the Fuzzy Tsukamoto Method Jannah, Ghina Raodatul; Bittara, Andi Ghizzania Sirih; Udin, Alvin Mas; Nasrullah, Asmaul Husna; Adiba, Fhatiah
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.v1i2.204

Abstract

Toko Rahmah is faced with the challenge of determining the optimal inventory of electronic goods to avoid excess or shortage of inventory. The uncertainty of demand and large sales often leads to inefficient inventory management. This study aims to apply the Tsukamoto fuzzy method in determining the optimal inventory of electronic goods at Toko Rahmah. Using this method will increase the accuracy of managing inventory and reduce the risk of excess or shortage of inventory. Therefore, in this study, the Tsukamoto fuzzy method is used to model and overcome the uncertainty of electronic goods inventory. Sales and demand data serve as output to the fuzzy system. The steps taken include forming a fuzzy set, applying fuzzy rules, and performing defuzzification to get an output value that is used as an inventory quantity recommendation. The results of this study were tested using 2 ways, namely using the Netbeans application system and using excel. These two ways are done to see how accurate or suitable the results obtained are. The accuracy results show that the average accuracy is 0.41 from 22 existing data, which is where the system is able to provide fairly accurate recommendations in determining the inventory of goods at Toko Rahmah. This method reduces the risk of excess or shortage of inventory and increases efficiency in managing inventory.

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