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All Journal Jurnal Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) International Journal of Advances in Intelligent Informatics Proceeding of the Electrical Engineering Computer Science and Informatics International Journal of Artificial Intelligence Research Signal and Image Processing Letters
Adhi Prahara
Universitas Ahmad Dahlan
Biochemistry, Genetics & Molecular Biology Computer Science & IT Electrical & Electronics Engineering Engineering Neuroscience

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Texton Based Segmentation for Road Defect Detection from Aerial Imagery Adhi Prahara; Son Ali Akbar; Ahmad Azhari
International Journal of Artificial Intelligence Research Vol 4, No 2 (2020): December 2020
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1055.466 KB) | DOI: 10.29099/ijair.v4i2.179

Abstract

Road defect such as potholes and road cracks, became a problem that arose every year in Indonesia. It could endanger drivers and damage the vehicles. It also obstructed the goods distribution via land transportation that had major impact to the economy. To handle this problem, the government released an online complaints system that utilized information system and GPS technology. To follow up the complaints especially road defect problem, a survey was conducted to assess the damage. Manual survey became less effective for large road area and might disturb the traffic. Therefore, we used road aerial imagery captured by Unmanned Aerial Vehicle (UAV). The proposed method used texton combined with K-Nearest Neighbor (K-NN) to segment the road area and Support Vector Machine (SVM) to detect the road defect. Morphological operation followed by blob analysis was performed to locate, measure, and determine the type of defect. The experiment showed that the proposed method able to segment the road area and detect road defect from aerial imagery with good Boundary F1 score.
Real-time Facial Expression Recognition to Track Non-verbal Behaviors as Lie Indicators During Interview Arif Budi Setiawan; Kaspul Anwar; Laelatul Azizah; Adhi Prahara
Signal and Image Processing Letters Vol. 1 No. 1: March 2019
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v1i1.144

Abstract

During interview, a psychologist should pay attention to every gesture and response, both verbal and nonverbal language/behaviors, made by the client. Psychologist certainly has limitation in recognizing every gesture and response that indicates a lie, especially in interpreting nonverbal behaviors that usually occurs in a short time. In this research, a real time facial expression recognition is proposed to track nonverbal behaviors to help psychologist keep informed about the change of facial expression that indicate a lie. The method tracks eye gaze, wrinkles on the forehead, and false smile using combination of face detection and facial landmark recognition to find the facial features and image processing method to track the nonverbal behaviors in facial features. Every nonverbal behavior is recorded and logged according to the video timeline to assist the psychologist analyze the behavior of the client. The result of tracking nonverbal behaviors of face is accurate and expected to be useful assistant for the psychologists.
Vehicle pose estimation for vehicle detection and tracking based on road direction Adhi Prahara; Ahmad Azhari; Murinto Murinto
International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i1.88

Abstract

Vehicle has several types and each of them has different color, size, and shape. The appearance of vehicle also changes if viewed from different viewpoint of traffic surveillance camera. This situation can create many possibilities of vehicle poses. However, the one in common, vehicle pose usually follows road direction. Therefore, this research proposes a method to estimate the pose of vehicle for vehicle detection and tracking based on road direction. Vehicle training data are generated from 3D vehicle models in four-pair orientation categories. Histogram of Oriented Gradients (HOG) and Linear-Support Vector Machine (Linear-SVM) are used to build vehicle detectors from the data. Road area is extracted from traffic surveillance image to localize the detection area. The pose of vehicle which estimated based on road direction will be used to select a suitable vehicle detector for vehicle detection process. To obtain the final vehicle object, vehicle line checking method is applied to the vehicle detection result. Finally, vehicle tracking is performed to give label on each vehicle. The test conducted on various viewpoints of traffic surveillance camera shows that the method effectively detects and tracks vehicle by estimating the pose of vehicle. Performance evaluation of the proposed method shows 0.9170 of accuracy and 0.9161 of balance accuracy (BAC).
Bottom-up visual attention model for still image: a preliminary study Adhi Prahara; Murinto Murinto; Dewi Pramudi Ismi
International Journal of Advances in Intelligent Informatics Vol 6, No 1 (2020): March 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v6i1.469

Abstract

The philosophy of human visual attention is scientifically explained in the field of cognitive psychology and neuroscience then computationally modeled in the field of computer science and engineering. Visual attention models have been applied in computer vision systems such as object detection, object recognition, image segmentation, image and video compression, action recognition, visual tracking, and so on. This work studies bottom-up visual attention, namely human fixation prediction and salient object detection models. The preliminary study briefly covers from the biological perspective of visual attention, including visual pathway, the theory of visual attention, to the computational model of bottom-up visual attention that generates saliency map. The study compares some models at each stage and observes whether the stage is inspired by biological architecture, concept, or behavior of human visual attention. From the study, the use of low-level features, center-surround mechanism, sparse representation, and higher-level guidance with intrinsic cues dominate the bottom-up visual attention approaches. The study also highlights the correlation between bottom-up visual attention and curiosity.
GPU Accelerated Number Plate Localization in Crowded Situation Adhi Prahara; Andri Pranolo; Rafał Dreżewski
International Journal of Advances in Intelligent Informatics Vol 1, No 3 (2015): November 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i3.46

Abstract

Number Plate Localization (NPL) has been widely used as part of Automatic Number Plate Recognition (ANPR) system. NPL method determines the accuracy of ANPR system. Although it is a mature research, the challenge stills persist especially in crowded situation where many vehicles present. Therefore, a method is proposed to localize number plate in crowded situation. The proposed NPL method uses vertical edge density to extract potential region of number plate then detect the number plate using combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM). The method employs GPU to deal with multiple number plate detection, to handle multi-scale detection window, and to perform real time detection. The test result shows good results, 0.9883 value of AUC (Area Under Curve), and 0.9362 of BAC (Balance Accuracy). Moreover, potential real time detection is foreseen because total process is executed in less than 50 ms. Errors are mainly caused by background that contain letters, non-standard number plate and highly covered number plate
Motorcycles detection using Haar-like features and Support Vector Machine on CCTV camera image Imam Teguh Mulyawan; Adhi Prahara
Jurnal Informatika Vol 13, No 2 (2019): July 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (724.417 KB) | DOI: 10.26555/jifo.v13i2.a13194

Abstract

Traffic monitoring system allows operators to monitor and analyze each traffic point via CCTV camera. However, it is difficult to monitor each traffic point all the time. This problem leads to the development of intelligent traffic monitoring system using computer vision technology which one of the features is vehicle detection. Vehicle detection still poses a challenge especially when dealing with motorcycles that occupy the majority of the road in Indonesia. In this research, a motorcycle detection method using Haar-like features and Support Vector Machine (SVM) on CCTV camera image is proposed. A set of preprocessing procedure is performed on the input image before Haar-like features extraction. The features then classified using trained SVM model via sliding window technique to detect motorcycles. The test result shows 0.0 log average miss rate and 0.9 average precision. From the low miss rate and high precision, the proposed method shows promising solution in detecting motorcycle from CCTV camera image.
Rekonstruksi 3D Untuk Model Wajah Virtual Akademik Menggunakan Sensor Kinect 2 Siti Sofia Rani; Adhi Prahara
Jurnal Sarjana Teknik Informatika Vol 9, No 1 (2021): Februari
Publisher : Teknik Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v1i1.19014

Abstract

Massive multiplayer online game (MMOG) seperti world of warcraft, aion atau second life telah mendapatkan perhatian luar biasa pada perkembangan game vitual. Salah satu kelebihan MMOG pada game virtual setiap player dapat berkomunikasi secara langsung yang di wakili dengan karakter visual tiga dimensi. MMOG juga mendukung grafik permainan pada komputer hingga permainan yang digunakan menggunakan karakter visual tiga dimensi menjadi terlihat nyata.Penelitian ini memanfaatkan alat sensor kinect 2 dan Microsoft Kinect yang membantu untuk merekam avatar tiga dimensi yang dapat dipersonalisasikan. Dari perkembangan alat sensor yang bernama Kinect 2 sensor dapat mempermudah rekontruksi 3D untuk model wajah pada avatar game virtual dan di proses menggunakan teknik modeling 3D hingga visual dari hasil sensor Kinect 2 menggambarkan tampak nyata dari player dalam bentuk visual.Penelitian ini menghasilkan rekontruksi 3D untuk model wajah pada avatar game virtual akademik menggunakan sensor Kinect 2. Hasil pengujian SUS untuk uji modelling dan visual avatar 3D menghasilkan nilai rata-rata 41,6 dari sekala 5, maka masuk kategori acceptable yang artinya aplikasi dapat diterima. 
Analisis Fitur Warna dan Tekstur untuk Metode Deteksi Jalan Adhi Prahara; Ahmad Azhari
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 2, No 2 (2016)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (350.033 KB) | DOI: 10.26555/jiteki.v2i2.5506

Abstract

Deteksi jalan digunakan untuk mengidentifikasi area jalan pada citra atau frame video. Tantangan dalam mendeteksi jalan diantaranya warna dan tekstur jalan yang beragam serta masalah pencahayaan. Oleh karena itu diperlukan fitur yang sesuai untuk menghadapi permasalahan tersebut. Pada penelitian ini dilakukan analisis fitur warna dan tekstur untuk mendeteksi jalan. Kumpulan 50 sampel jalan diambil untuk diekstrak fitur warna di tiga ruang warna yang berbeda yaitu RGB (Red-Green-Blue), HSV (Hue-Saturation-Value), dan CIE L*a*b* serta diekstrak fitur teksturnya dengan GLCM (Gray Level Co-occurrence Matrix). Fitur-fitur tersebut kemudian dianalisis untuk didapatkan fitur dengan variasi yang rendah dari semua sampel jalan yang digunakan untuk menentukan threshold warna maupun tekstur. Hasil pengujian metode deteksi jalan dari 150 citra uji jalan menggunakan batasan fitur hasil analisis menunjukkan akurasi 90,54%.
Keystroke-Level Model to Evaluate Chatbot Interface for Reservation System Supriyanto Supriyanto; Adhi Prahara; Tri Susanto Saputro
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1966

Abstract

The tour package reservation system is an important part of improving tourism services. Reservations must be able to meet the information needs of prospective customers and can serve the desired tour package bookings. A reservation system is usually a form that must be filled in sequence by prospective visitors. This paper discusses the evaluation of the application of the chatbot interface on the reservation system with the keystroke-level model. Changing the interaction design that previously did the task fills out the form into a conversation interaction. The aim is to increase the speed of the ordering process through the system. Prospective visitors do not need to fill in the form, they only need to have a conversation with the system while entering the order data. The evaluation results using the keystroke-level model show that the chatbot interface can increase the speed of the process by shortening steps.
Co-Authors Andri Pranolo Arif Budi Setiawan Azhari, Ahmad Dewi Pramudi Ismi Imam Teguh Mulyawan Kaspul Anwar Laelatul Azizah Murinto Murinto Rafał Dreżewski Siti Sofia Rani Son Ali Akbar Tri Susanto Saputro Yundari, Yundari