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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. 5 No. 02 (2021)" : 7 Documents clear
Metode Kernel Distance Classifier Terhadap Klasifikasi Penyakit Jantung Aprianto, Kasiful
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.70-74.2021

Abstract

This study compares the Support Vector Machine (SVM) and Kernel Distance Classification (KDC) methods to classify heart disease. SVM works by transforming data into higher dimensions using the kernel and classifying data linearly using a hyperplane. Meanwhile, KDC works by finding points that represent each classification from the data that has been transformed into a higher dimension using the kernel, and the new data is predicted based on the closest distance from the point of each classification. The results show that the accuracy produced by SVM is 81.11%. The accuracy produced by the SVM model is better than that produced by the KDC model of 80.47% with a difference of 0.64%, even though both models use kernel transformation.
Utilization of AHP-MAUT Method to Determine the Country of Exhibition Abroad in Batik Hatta Boutique Cholil, Saifur Rohman; Ardianita, Tria
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.52-56.2021

Abstract

This research was conducted with the aim of helping decide the destination country for overseas exhibitions at the Batik Hatta Boutique. By knowing all the data and information of a country, boutique owners can decide which country to visit in the batik exhibition. Because if you attend the cast in all countries, there will be overruns in costs. The methods used are AHP and MAUT. The AHP method is used as a weighting using a linguistic value scale. Weights are obtained from the pairwise comparison matrix between two elements of all elements that occur at the same hierarchical level. The MAUT method is used to determine the importance of each alternative for the ranking process. The results of this study indicate that Cambodia was chosen as the location to be visited for the batik exhibition. The results of the validation using the Spearman Rank correlation comparison obtained a value of 0.951 meaning that this method can be used as a decision making.
Pengembangan Media Interaktif Pengembangan Media Interaktif Berbasis Game Edukasi dalam Meningkatkan Kreativitas Guru Sekolah Dasar di Masa Pandemi Covid-19 Aminuddin, Fattachul Huda; Djauhari, Teuku D; M.Pd, Merty Megawati
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.63-69.2021

Abstract

The presence of the Covid-19 Virus in the world has not only changed the learning culture, but has become a new challenge in developing teacher creativity in the teaching and learning process. This conventional learning pattern that has evolved into technology-based distance learning requires teachers to be able to adapt and adapt to the limited learning needs of students during the pandemic. Digital technology tools are currently very developed, but they are enough to help educators to adapt to the diverse learning needs of today's students. So it is necessary to use the right learning media in carrying out learning during the pandemic. This training aims to train abilities and skills in increasing the creativity of teachers in using interactive learning media during the pandemic using the Quizizz platform. Quizizz is an interactive game-based online platform that can be used in a fun teaching and learning process during the Covid-19 pandemic by utilizing an Android smartphone. The method used is the lecture method and interactive training by involving the teacher as a simulation model.
Sistem Kendali Sirkulasi Udara dan Pembatasan Jumlah Pelanggan Toko Berbasis IoT Hanif, Labiq Al; Prasetyo, Aditya Putra Perdana; Ubaya, Huda
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.81-92.2021

Abstract

The emergence of the COVID-19 pandemic in early 2020 had a major impact on human life on a global scale. Many actions and policies are aimed at anticipating transmission and breaking the chain of the spread of the COVID-19 virus, thus requiring store owners to implement various health protocols. This study discusses the monitoring system for the condition of the storeroom in real-time with the IoT concept, and the implementation of Sugeno fuzzy logic in controlling the speed of the exhaust fan motor to circulate air in the room and limit the number of customers during the COVID-19 pandemic based on conditions of temperature, humidity, and many people in the storeroom. The actual test results from the implementation of Sugeno fuzzy logic show that the system has good performance in controlling the speed of the exhaust fan and limiting the number of customers based on the level of danger of the potential COVID-19 transmission in the room automatically and can monitor the condition of the room through the Thinger.io website in real time.
Rancang Bangun Alat Pendeteksi NOx dan CO Berbasis Mikrokontroler ESP32 dengan Notifikasi Via Telegram dan Suara Asmazori, Mutiara
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.57-62.2021

Abstract

The design of NOx and CO detectors based on notifications via telegram and voice has been carried out. This detector consists of a gas sensor MQ-135 as a nitrogen oxide detector and an MQ-7 sensor as a carbon monoxide detector. Data processing is carried out using an ESP32 microcontroller which can send results to a telegram bot and play sound using speakers connected to the ISD 1820 sound module. The tool made can send notifications if the concentration of nitrogen oxides and carbon monoxide exceeds 50 ppm. The test is carried out by burning waste to produce smoke. Burning smoke contains various gases and particles that are harmful to the body. The characterization of the MQ-135 sensor was carried out by comparing the data obtained from the ISPU to measure nitrogen oxide gas and producing an error value of 9.09%. Meanwhile, the characterization of the MQ-7 sensor was carried out using a biogas analyzer and resulted in an error ratio of 3.26%. These results prove that the tools that have been designed can work well.
Implementasi Cloud Based Video Conference System Menggunakan Amazon Web Service Alanda, Alde; Satria, Deni
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.75-80.2021

Abstract

Since December 2019, the world and Indonesia have fought a major disaster, namely the Covid-19 virus pandemic. With the rapid spread or transmission of the virus, the Indonesian government decided to impose social distancing or social restrictions that impacted the education sector. Students and lecturers cannot conduct lectures face-to-face in class or laboratory, but lectures must be conducted online. For that, we need an open-source system developed by the campus in carrying out online courses. This application was developed using cloud technology and JITSI as an open-source video-conferencing application. In this study, testing of the features that exist in video conferencing and resource usage on the server is carried out. The results of feature testing on the application run as expected with several important features used for learning such as chat, share screen, recording features that can run optimally. The result tested the system resources based on the number of participants, 31 participants with an average use of 2.1GB RAM and 78 participants with an average RAM usage of 2.8GB.
Sistem Pendeteksi Gejala Awal Tantrum Pada Anak Autisme Melalui Ekspresi Wajah Dengan Convolutional Neural Network Novani, Nefy Puteri; Salsabila, Dini Ramadhani; Aisuwarya, Ratna; Arief, Lathifah; Afriyeni, Nelia
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.93-106.2021

Abstract

Tantrums are outbursts of anger and they can occur at any age. An attitude tantrum or what is commonly referred to as a temper tantrum is a child's outburst of anger that often occurs when a child shows negative behavior. Emotional outbursts of tantrums that occur in children with autism are not only to seek the attention of adults, but also as an outlet for a child's feelings for parents and those around him on a whim or feeling he is feeling, but the child cannot convey it. For this reason, researchers propose a system for detecting early symptoms of tantrums in children with autism through facial expressions with CNN. The CNN method is one of the deep learning methods that can be used to recognize and classify an object in a digital image. Then the preprocessing process is carried out using labeling on the data. Then the CNN architecture is designed with input containing 48x48x1 neurons. The data was then trained using 357 epochs with an accuracy rate of 72.67%%. Then tested using test data for children with autism to get an average accuracy value of 72.67%%.

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