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All Journal InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal INFOTEL Jurnal Informatika: Jurnal Pengembangan IT
Afandi Nur Aziz Thohari
Institut Teknologi Telkom Purwokerto
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : Jurnal INFOTEL

 1 
Segmentasi Citra Kanker Payudara Menggunakan K-Means Clustering Berbasis Komputasi Parallel GPU Cuda Andika Elok Amalia; Gregorius Airlangga; Afandi Nur Aziz Thohari
JURNAL INFOTEL Vol 10 No 1 (2018): February 2018
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v10i1.344

Abstract

Image processing technology is now widely used in the health area, one example is to help the radiologist to analyze the result of MRI (Magnetic Resonance Imaging), CT Scan and Mammography. Image segmentation is a process which is intended to obtain the objects contained in the image by dividing the image into several areas that have similarity attributes on an object with the aim of facilitating the analysis process. The increasing amount of patient data and larger image size are new challenges in segmentation process to use time efficiently while still keeping the process quality. Research on the segmentation of medical images have been done but still few that combine with parallel computing. In this research, K-Means clustering on the image of mammography result is implemented using two-way computation which are serial and parallel. The result shows that parallel computing gives faster average performance execution up to twofold.
Real-Time Object Detection For Wayang Punakawan Identification Using Deep Learning Afandi Nur Aziz Thohari; Rifki Adhitama
JURNAL INFOTEL Vol 11 No 4 (2019): November 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i4.455

Abstract

Indonesia is a country that has a variety of cultures, one of which is wayang kulit. This typical javanese performance art must continue to be preserved so that to be known by future generations. There are many wayang figures in Indonesia, and the most famous is punakawan. Wayang punakawan consists of four character namely semar, gareng petruk, and bagong. To preserve wayang punakawan to be known by the next generation, then in this study created a system that is able to identify real-time punakawan object using deep learning technology. The method that used is Single Shot Multiple Detector (SSD) as one of the models of deep learning that has a good ability in classifying data with three-dimensional structures such as real-time video. SSD model with MobileNet layer can work in slight computation, so that it can be run in real-time system. To classify object there are two steps that must be done such as training process and testing process. Training process takes 28 hours with 100.000 steps of iteration.The result of training process is a model which used to identify object. Based on the test result obtained an accuracy to detect object was 98,86%. This prove that the system has been able to optimize object in real-time accurately.
Co-Authors Andika Elok Amalia Citra Wiguna Gregorius Airlangga Nugraha, Novanda Alim Setya Ramadhani, Rima Dias Rifki Adhitama