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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 7 Documents
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Search results for , issue "Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering" : 7 Documents clear
LoRa Communication in the Service Level Monitoring Satu Duit Bogor Bridge Sulis Setiowati; Riandini Riandini; Via Arsita Sari; Indah Luthfiyyah Purwanti; Noval Andriansyah
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.19-28.2023

Abstract

Lora is the solution to the problem of the need for long-distance two-way communication between machines that are targeted by IoT (Internet of Thins. LoRa has long-distance transmission capabilities, has power, and a low bit rate. Based on the needs related to LoRa, further research is needed, to analyze the performance of LoRa communication. The LoRa communication protocol will be applied to the One Duit Bogor bridge monitoring system using the Website and LabVIEW. This study used LoRa SX1276 with a frequency of 915MHz with the LoRa point-to-point method and LoRa gateway. The parameters analyzed include RSSI (Received Signal Strength Indicator), SNR (Signal to Noise Ratio), Delay, Throughput, and Packet loss to determine the quality of LoRa performance with TIPHON standards. Based on the tests that have been carried out, it proves that LoRa communication has good performance. In urban areas or around the Satu Duit Bogor bridge, LoRa can transmit data from a distance of 0 to 500 m with an average delay of 217 ms, an average packet loss of 10.237%, an average throughput of 137.881 bps, an average SNR of 7.54 dB, and an average RSSI of -71,798 dBm. At a distance of 0-400 m there is an insignificant change in LoRa parameters, but at a distance of 500 m a high change occurs, this is due to the fact that the distance greatly affects the transmission of data. The longer the range, the more obstacles will be passed so that data transmission is disrupted.
A review of Image Processing Technique for Monitoring The Growth and Health of Cows Zurnawita Zurnawita; Cipto Prabowo; Rahmadi Kurnia; Ikhwana Elfitri
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
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
Sistem Pakar Metode Backward Chaining untuk Optimalisasi Pelayanan Pemberian Informasi Obat Surya Dwi Putra; Dhena Marichy Putri; Sarjon Defit; Sumijan Sumijan
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
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 Abisola Olayiwola; Ajibola Oluwafemi Oyedeji; Oluwakemi Omoyeni; Oluwafemi Ayemimowa; Mubarak Olaoluwa
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
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 Rifki Suwandi; Werman Kasoep; Ramon Luthvi Destria
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
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 Arrya Anandika; Muhammad Ilhamdi Rusydi; Pepi Putri Utami; Rizka Hadelina; Minoru Sasaki
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
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 Rizka Hadelina; Muhammad Ilhamdi Rusydi; Mutia Firza; Oluwarotimi Williams Samuel
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
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.

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