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Journal of Information Technology and Computer Engineering
Published by Universitas Andalas
ISSN : 25991663     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Journal of Information Technology and Computer Engineering (JITCE) is a scholarly periodical. JITCE will publish research papers, technical papers, conceptual papers, and case study reports. This journal is organized by Computer System Department at Universitas Andalas, Padang, West Sumatra, Indonesia.
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Articles 186 Documents
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Continuous Integration and Continuous Deployment (CI/CD) for Web Applications on Cloud Infrastructures Alanda, Alde; Mooduto, Hanriyawan Adnan; Hadelina, Rizka
JITCE (Journal of Information Technology and Computer Engineering) Vol. 6 No. 02 (2022)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.6.02.50-55.2022

Abstract

At this time, the application development process has experienced much development in terms of tools and the programming language used. The application development process is required to be carried out in a fast process using various existing tools. The application development and delivery process can be done quickly using Continuous Integration (CI) and Continuous Delivery (CD). This study uses the CI/CD technique to develop real-time applications using various programming languages implemented on a cloud infrastructure using the AWS codepipeline, which focuses on automatic deployment. Application source code is stored on different media using GitHub and Amazon S3. The source code will be tested for automatic deployment using the AWS code pipeline. The results of this study show that all programming languages can be appropriately deployed with an average time of 60 seconds
Rancang Bangun Sistem Pengering Putar untuk Rumput Laut Berbasis Mikrokontroler Novani, Nefy Puteri; Afif, Awal
JITCE (Journal of Information Technology and Computer Engineering) Vol. 6 No. 02 (2022)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.6.02.44-49.2022

Abstract

Eucheuma cottonii is a type of seaweed that is cultivated in the coastal area of Nagari Sungai Pinang, Koto XI Tarusan District, Pesisir Selatan District, West Sumatra Province. Before being sold, seaweed farmers must dry their seaweed first, because what can be sold is dried seaweed. Drying the seaweed takes two to three days depending on the weather conditions. In this research a seaweed drying system has been designed with a tool that rotates the seaweed in the drying chamber. In this rotary drying system, the soil moisture sensor is used which functions to detect the moisture content of the seaweed, if the moisture content of the seaweed is still read > 30% then the microcontroller turns on the relay which forwards instructions to the heater and the DC motor starts rotating the player container. The DS18B20 sensor is used to detect the temperature of the drying chamber, if the total moisture content of the seaweed is 30%, then the state of dry seaweed has been reached. Tests have been carried out to determine the difference in time required between the seaweed drying process using the system that has been built in this study and the seaweed drying process that utilizes direct sunlight. To achieve a moisture content of 30% in the seaweed drying process with the system designed in this study it takes an average of ±50 minutes, while using direct sunlight it takes ±9 hours to dry the seaweed.
A review of Image Processing Technique for Monitoring The Growth and Health of Cows Zurnawita, Zurnawita; Prabowo, Cipto; Kurnia, Rahmadi; Elfitri, Ikhwana
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.8-18.2023

Abstract

In general, monitoring of animal growth and health is done directly by farmers (invasive measurement methods) which can cause cows to be injured or experience stress. To avoid this, several studies have been conducted on non-invasive methods using image processing technology. In this study, we systematically reviewed several works of literature to identify and synthesize published articles on image processing technology and image processing applications related to weight estimation and individual cattle identification. Analysis of image processing technologies used for weight estimation and individual cattle identification is the main objective of this article. Articles were searched through several databases and studies that met the inclusion criteria were analyzed and used in the review. The studies were divided into three main themes: image processing technologies, applications using image processing, and image processing research on cattle growth and health. It can be concluded that deep learning approaches are increasingly being studied, tested and considered as a viable and promising approach to monitor cattle weight and health in several aspects
Real-time Defense Against Cyber Threats: Analyzing Wazuh's Effectiveness in Server Monitoring Alanda, Alde; Mooduto, H.A; Hadi, Ronal
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 2 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.2.56-62.2023

Abstract

As cloud computing grows exponentially, organizations face escalating cybersecurity challenges due to increased cyber threats and attacks on cloud-based networks. Monitoring cloud servers is one action that can be taken to improve the security. This can be done with the help of various server monitoring tools, such as Wazuh. The study investigates Wazuh's effectiveness in real-time monitoring of three AWS EC2 instance-based cloud servers. Wazuh's capabilities such as log data collection, malware detection, active response automation, and Docker container monitoring, are examined. The research reveals detailed insights into user activities, web server access, and database operations. Wazuh proves adept at tracking file integrity, detecting malware, and responding actively, as evidenced by the 342 alerts generated during a 24-hour monitoring period. The result shows that Wazuh is a particularly effective tool for protecting cloud environments from cyberattacks because it provides quick and ongoing security monitoring, which is essential for securing intricate cloud infrastructures.
Sistem Pakar Metode Backward Chaining untuk Optimalisasi Pelayanan Pemberian Informasi Obat: Studi Kasus Puskesmas Lasi Kabupaten Agam Putra, Surya Dwi; Putri, Dhena Marichy; Defit, Sarjon; Sumijan, Sumijan
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.1-7.2023

Abstract

Drug information service is an assistance service to handle the needs of pharmacists related to medicines consumed by patients at the Lasi Health Center, Agam Regency. Nowadays, most of drug information services always require pharmacists to carry out their services, although there is limited number of pharmacists for providing drug information services at the Lasi Health Center, Agam Regency. This study aims to optimize drug information services so that the services can be carried out without the direct presence of a pharmacist. The data used in this study were drug prescription data available at the Pharmacy of Lasi Health Center Agam for the last 12 months and drug information services provided by pharmacists at the Lasi Health Center Agam Regency. This study used the backward chaining method to identify the drugs prescribed to the patients. The result achieved by this study were 356 Rules that could be applied directly to drug information services, with an accuracy rate of 100%. The rules generated using the backward chaining method can be used to optimize drug information services at the Lasi Health Center in Agam Regency without having to be served directly by pharmacists.
Comparative Analysis of Machine Learning Models for Detection of Fake News: A Case Study of Covid-19 Olayiwola, Abisola; Oyedeji, Ajibola Oluwafemi; Omoyeni, Oluwakemi; Ayemimowa, Oluwafemi; Olaoluwa, Mubarak
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.29-33.2023

Abstract

During and after the Covid-19 pandemic, people rely heavily on the internet for information because of its easy accessibility. However, the spread of fake information through this medium has been fast-growing, especially during and after the pandemic. This study, therefore, aims to evaluate the performance of 5 machine learning models used in detecting Covid-19 fake news. The models were trained using the Covid-19 dataset gathered online. The dataset contains 7,262 real news and 9,727 fake news, totalling 16,989 news altogether. 80% of this dataset was used for training the models while 20% was used for testing them. The support vector machine (SVM) with 95%, 95%, 97% and 96% for the accuracy, precision, recall and F1-score respectively was the best classifier for detecting Covid-19 fake news and has shown a better performance than the other algorithms.
Alat Koreksi dan Rekontruksi Tulisan pada Dokumen Lama Bahasa Indonesia Berbasis Mini PC Suwandi, Rifki; Kasoep, Werman; Destria, Ramon Luthvi
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.34-39.2023

Abstract

In the digital era, preserving old documents to prevent damage is a significant challenge. One solution to this problem is to reconstruct damaged or lost documents using image processing and natural language processing technologies. This article discusses the design of a tool for correcting and reconstructing writing in old papers and documents that can be implemented on a mini PC. The tool uses state-of-the-art algorithms such as Convolutional Neural Network (CNN) for character recognition and Optical Character Recognition (OCR), as well as Image Inpainting and Sequence-to-Sequence (Seq2Seq) algorithms for document reconstruction. Test results show that this tool can recognize characters with high accuracy and reconstruct damaged or lost documents effectively.
Hand Gesture to Control Virtual Keyboard using Neural Network Anandika, Arrya; Rusydi, Muhammad Ilhamdi; Utami, Pepi Putri; Hadelina, Rizka; Sasaki, Minoru
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.40-48.2023

Abstract

Disability is one of a person's physical and mental conditions that can inhibit normal daily activities. One of the disabilities that can be found in disability is speech without fingers. Persons with disabilities have obstacles in communicating with people around both verbally and in writing. Communication tools to help people with disabilities without finger fingers continue to be developed, one of them is by creating a virtual keyboard using a Leap Motion sensor. The hand gestures are captured using the Leap Motion sensor so that the direction of the hand gesture in the form of pitch, yaw, and roll is obtained. The direction values are grouped into normal, right, left, up, down, and rotating gestures to control the virtual keyboard. The amount of data used for gesture recognition in this study was 5400 data consisting of 3780 training data and 1620 test data. The results of data testing conducted using the Artificial Neural Network method obtained an accuracy value of 98.82%. This study also performed a virtual keyboard performance test directly by typing 20 types of characters conducted by 15 respondents three times. The average time needed by respondents in typing is 5.45 seconds per character.
ANN Models for Shoulder Pain Detection based on Human Facial Expression Covered by Mask Hadelina, Rizka; Rusydi, Muhammad Ilhamdi; Firza, Mutia; Samuel, Oluwarotimi Williams
JITCE (Journal of Information Technology and Computer Engineering) Vol. 7 No. 01 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.49-55.2023

Abstract

Facial expressions are a method to communicate if someone feels pain. Moreover, coding facial movements to assess pain requires extensive training and is time-consuming for clinical practice. In addition, in Covid 19 pandemic, it was difficult to determine this expression due to the mask on the face. There for, it needs to develop a system that can detect the pain from facial expressions when a person is wearing a mask. There are 41 points used to form 19 geometrical features. It used 20.000 frames of 24 respondents from the dataset as secondary data . From these data, training, and testing were carried out using the ANN (Artificial Neural Network) method with a variation of the number of neurons in the hidden layer, i.e., 5, 10, 15, and 20 neurons. The results obtained from testing these data are the highest accuracy of 86% with the number of 20 hidden layers.
Evaluating IndoGPT for Legal Queries: A Benchmark Against GPT-4 Models Palupi, Ade Cahyaning; irawan, ade
JITCE (Journal of Information Technology and Computer Engineering) Vol. 9 No. 2 (2025): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

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

Abstract

This study evaluates a chatbot developed with the Large Language Model (LLM) IndoGPT, focusing on its use of Retrieval-Augmented Generation (RAG) to answer questions about university regulations from legal PDF documents in the Indonesian Language. IndoGPT's performance is benchmarked against the more advanced models, GPT-4 and GPT-4o. The chatbot combines RAG techniques with the LangChain framework, and its effectiveness is assessed using the Retrieval-Augmented Generation Assessment (RAGAS) framework. The dataset includes publicly available legal documents from Universitas Pertamina, with test data created by the authors. IndoGPT consistently underperforms compared to GPT-4 and GPT-4o. GPT-4 achieves superior metrics with Context Precision at 0.9027, Context Recall at 0.8693, Faithfulness at 0.8486, and Answer Relevancy at 0.8142. Similarly, GPT-4o delivers strong results with Context Precision at 0.8896, Context Recall at 0.8594, Faithfulness at 0.8804, and Answer Relevancy at 0.8773. In contrast, IndoGPT shows significant deficiencies, with much lower scores: Context Precision at 0.6687, Context Recall at 0.5711, Faithfulness at 0.0738, and Answer Relevancy at 0.1628. These findings highlight IndoGPT's substantial limitations, especially when compared to GPT-4 and GPT-4o, which excel in providing accurate, contextually relevant answers. The GPT-4-based chatbot demonstrates strong capabilities in understanding user queries and delivering accurate responses while effectively reducing hallucinations through the RAG technique.

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