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All Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi JOIV : International Journal on Informatics Visualization JURNAL INTEGRASI JUTIK : Jurnal Teknologi Informasi dan Komputer Matrix : Jurnal Manajemen Teknologi dan Informatika WIDYA LAKSANA Jurnal Praksis dan Dedikasi Sosial Jurnal Manajemen dan Teknologi Informasi
Atmaja, I Made Ari Dwi Suta
Politeknik Negeri Bali
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Social Sciences Other

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Journal : JOIV : International Journal on Informatics Visualization

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Roboswab: A Covid-19 Thermal Imaging Detector Based on Oral and Facial Temperatures I Nyoman Gede Arya Astawa; I.D.G Ary Subagia; Felipe P. Vista IV; IGAK Cathur Adhi; I Made Ari Dwi Suta Atmaja
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1505

Abstract

The SARS-CoV-2 virus has been the precursor of the coronavirus disease (COVID-19). The symptoms of COVID-19 begin with the common cold and then become very severe, such as those of Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Currently, polymerase chain reaction (PCR) is used to detect COVID-19 accurately, but it causes some side effects to the patient when the test is performed. Therefore, the proposed "Roboswab" was developed that uses thermal imaging to measure non-contact facial and oral temperature. This study focuses on the performance of the proposed equipment in measuring facial and oral temperature from various distances. Face detection also involves checking whether the subject is wearing a mask or not. Image processing methods with thermal imaging and robotic manipulators are integrated into a contact-free detector that is inexpensive, accurate, and painless. This research has successfully detected masked or non-masked faces and accurately detected facial temperature. The results showed that the accurate measurement of facial temperature with a mask is 90% with an error of +/- 0.05%, while it was 100% without a mask. On the other hand, the oral temperature was measured with 97% accuracy and an error of less than 5%. The optimal distance of the Roboswab to the face for measuring temperature is an average of 60 cm. The Roboswab tool equipped with masked or non-masked face detection can be used for early detection of COVID-19 without direct contact with patients.
Comparison of the Packet Wavelet Transform Method for Medical Image Compression Atmaja, I Made Ari Dwi Suta; Triadi, Wilfridus Bambang; Astawa, I Nyoman Gede Arya; Radhitya, Made Leo
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1732

Abstract

Medical images are often used for educational, analytical, and medical diagnostic purposes. Medical image data requires large amounts of storage on computers. Three types of codecs, namely Haar, Daubechies, and Biorthogonal, were used in this study. This study aims to find the best wavelet method of the three tested wavelet methods (Haar, Daubechies, and Biorthogonal). This study uses medical images representing USG and CT-scan images as testing data. The first test is carried out by comparing the threshold ratio. Three threshold values are used, namely 30, 40, and 50. The second test looks for PSNR values with different thresholds. The third test looks for a comparison of the rate (image size) to the PSSR value. The final test is to find each medical image's compression and decompression times. The first compression ratio test results on both medical images showed that CT scan images on Haar and Biorthogonal wavelets were the best, with an average compression ratio of 40.76% and a PSNR of 33.77. The PSNR obtained is also getting more significant for testing with a larger image size. The average compression time is 0.52 seconds, and the decompression time is 2.27 seconds. Based on the test results, this study recommends that the Daubechies wavelet method is very good for compression, which is 0.51 seconds, and the Biorthogonal wavelet method is very good for medical image decompression, which is 1.69 seconds.
Co-Authors Aji Prasetya Wibawa Ambara, Made Pradnyana Ambara Bawa, I Gusti Ngurah Bagus Catur Elina Rudiastari Fachrul Kurniawan Felipe P. Vista IV Gusti Nyoman Ayu Sukerti Gusti Nyoman Ayu Sukerti, Gusti Nyoman Ayu I Dewa Gede Ary Subagia I G. N. B. Caturbawa I Made Riyan Adi Nugroho I Nyoman Gede Arya Astawa IGAK Cathur Adhi Komang Ayu Triana Indah Made Pradnyana Ambara, Made Pradnyana Ni Wayan Wisswani Putu Gde Sukarata Radhitya, Made Leo Rudiastari, Elina S.Pd. M Kes I Ketut Sudiana . Triadi, Wilfridus Bambang