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All Journal Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Engineering Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks CHIPSET (Journal on Computer Hardware, Signal Processing, Embedded System and Networking)
Rizka Hadelina
Universitas Andalas
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Medicine & Pharmacology Social Sciences Other

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Journal : Journal of Information Technology and Computer Engineering

 1 
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.
Continuous Integration and Continuous Deployment (CI/CD) for Web Applications on Cloud Infrastructures Alde Alanda; Hanriyawan Adnan Mooduto; Rizka Hadelina
JITCE (Journal of Information Technology and Computer Engineering) Vol 6 No 02 (2022): Journal of Information Technology and Computer Engineering
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
Co-Authors - Liliwarti Agung W. Setiawan Alde Alanda, Alde Andrivo Rusydi Arrya Anandika Budi Rahmadya Dodon Yendri Elmiyasna Kimin Fauzi Akbar Ferdian, Rian Hanriyawan Adnan Mooduto Minoru Sasaki Mutia Firza Nefy Puteri Novani Nefy Puteri Novani Nefy Puteri Novani Oluwarotimi Williams Samuel Pepi Putri Utami Rahmi Eka Putri Ratna Aisuwarya Rifki Suwandi Rifki Suwandi Rusydi, Muhammad Ilhamdi Satwarnirat Satwarnirat Syafii . Tati Erlina Tati Erlina Werman Kasoep Yolanda, Desta