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All Journal Jurnal Teknologi Elekterika JAREE (Journal on Advanced Research in Electrical Engineering)
Alwali, Muhammad
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Design of Information System for Pajjaiang Makassar Clinic Based on Web and Mobile Alwali, Muhammad; Bastian, Alvian; Asriyadi, Asriyadi
Jurnal Teknologi Elekterika Vol. 21 No. 1 (2024)
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v21i1.4817

Abstract

The role of information technology is currently developed according to the current rapid development of the times. The most developed types of information technology are web-based and mobile devices. Web-based and mobile devices are used to facilitate daily activities along with technological advances. One of the important things for everyday life by utilizing technological advances is in the field of health services, especially services at health clinics. In this regard, a web-based and mobile information system was designed at the Pajjaiang Makassar clinic to facilitate service. Making this system uses the waterfall method which is often used in the development of information systems or software. This system consists of 4 actors, namely patients, admins, doctors, and pharmacists. Patients are connected to the mobile application, while admins, doctors, and pharmacists are connected on the web side. The patient registers for the examination, the admin manages the patient's data, the doctor conducts the examination, and the pharmacist manages the available drugs. Everything is interconnected using mysql database as the database and Application Programming Interface (API) to connect it. With this web-based and mobile information system is a form of digitalization process in the field of health services.
Markerless Facial Reconstruction Motion Capture Using Triangulation Method Alwali, Muhammad; Pambudi, Sevito Fernanda; Suciningtyas, Laras; Yuniarno, Eko Mulyanto
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.456

Abstract

Motion capture is a popular research topic, with one of its main applications being human face reconstruction. The demand for converting 2D images into 3D reconstructions continues to increase, especially in facial reconstruction, where progress is made in improving the accuracy of facial position prediction. However, there is still a significant gap in developing facial reconstruction technologies that can consistently convert 2D to 3D data with high accuracy, especially in scenarios involving dynamic facial expressions, diverse facial angles, and complex environmental conditions. Therefore, an approach using the triangulation method for 3D face reconstruction in the real world was developed. In the experiments, two cameras were used to obtain two face landmark coordinates so that the triangulation method can be implemented for 3D face reconstruction. This research aims to develop a motion capture approach that is able to accurately and efficiently transform 2D data into 3D face models without the need for complex hardware. The main contribution of this research is the development of a machine learning-based markerless motion capture technique designed to improve the accuracy of face position prediction in 3D face reconstruction from 2D data in realistic environments. This method seeks to bridge the current technology gap by providing a more flexible and reliable solution, expanding the potential applications of motion capture in various fields without dependence on specialized hardware. The results of face reconstruction research using markerless motion capture and triangulation method show RMSE values of 3.560839 for eyes, 1.644749 for nose, and 4.054638 for lips.
Co-Authors Asriyadi Asriyadi BASTIAN, ALVIAN Eko Mulyanto Yuniarno Pambudi, Sevito Fernanda Suciningtyas, Laras