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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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Sistem Keamanan Ruangan Berbasis Internet of Things Menggunakan Single Board Computer Rima Dias Ramadhani; Afandi Nur Aziz Thohari; Novanda Alim Setya Nugraha
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 4, No 2 (2020): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v4i2.2338

Abstract

Closed Circuit Television (CCTV) is a security system to monitoring a room. In recent years, the use of CCTV is becoming less effective. CCTV usually have expensive rental fees and expensive device. Surveillance system using CCTV still need security officer to monitoring room condition through TV Screen. In this research purposed to build surveillance system using artificial intelligence method. The system features are detect object and send notification through Short Message Service (SMS). Single Board Computer (SBC) is used to processing video data. Technique for detecting objects is Structural Similarity (SSIM). Thought this technique, system have more accuration because it can't read shadow as object. Based on testing result obtained that system can detect object and send notification to user through SMS. System can't read object if low light intensity, but if high intensity of light the system can detect objects that have far position. Maximum frame rate that used to capture video is 60 fps, because limitation of SBC that used.
Sistem Pengawasan Berbasis Deteksi Gerak Menggunakan Single Board Computer Afandi Nur Aziz Thohari; Rima Dias Ramadhani
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 1: Februari 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1112.391 KB)

Abstract

Monitoring is the important thing for the security of an area. Based on the monitoring, the condition of the area, events, and objects can be observed. Monitoring of an area generally uses Closed Circuit Television (CCTV). But CCTV cameras only function as passive supervisor which are unable to detect the appearance of objects. Therefore, the motion detection techniques need to be applied to detect the appearance of the objects. In this paper, a Gaussian blur and accumulative frame difference method was applied to detect the appearance of the objects. The method works by comparing the reference frame as a benchmark with the target frame which is filled by the objects. Based on the results of the test, the system is able to detect the objects that appear by raising a segmentation line on the objects. Then, the time of objects appearance will be recorded in a *.csv file and the system visualizes the appearance of the objects in time-series graphs. Objects appearance examination at a distance of 1 to 10 meters can work well during a bright conditions. However, in dark environments (less than 40 lux), the system has not been able to detect the appearance of an object because it depends on the specification of camera used by the users. Then, in testing the number of the objects, the system can detect multiple objects. However, if there are several objects that are too close, those objects will be merged as one object.
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.
Analisis Value chain Dalam Desain Alert System Pengajuan Jabatan Fungsional Dosen Citra Wiguna; Afandi Nur Aziz Thohari
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i1.1249

Abstract

Information and communication technology (ICT) currently become one of the important things to increasing excellence in various fields, where one of field is education. Institut Teknologi Telkom Purwokerto (ITTP) is an educational institution that has a focus on ICT technology development.One of the ICT development conducted by ITTP is the existence of an alert system for submitting functional lecturer position. This alert system can produce competent lecturer and can pass the qualifications according to the rules set. In the construction of alert system, absolutely must be through desain, and corresponding with requirement and business process that exist in ITTP. Therefore in this study was conducted alert system design analysis for the submission of functional lecturer position. The analytical method that used is a Value chain which has been proven to increase the strategic step of the product. The result of this research is strength weakness analysis in the alert system design that useful for institution and also lecturer in order to improve the quality and level that is controlled and directed.
Co-Authors Andika Elok Amalia Citra Wiguna Gregorius Airlangga Nugraha, Novanda Alim Setya Ramadhani, Rima Dias Rifki Adhitama