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All Journal IPTEK The Journal for Technology and Science CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications
Widodo Budiharto
Bina Nusantara University
Computer Science & IT Engineering Mathematics

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The Performance of Boolean Retrieval and Vector Space Model in Textual Information Retrieval Budi Yulianto; Widodo Budiharto; Iman Herwidiana Kartowisastro
CommIT (Communication and Information Technology) Journal Vol. 11 No. 1 (2017): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v11i1.2108

Abstract

Boolean Retrieval (BR) and Vector Space Model (VSM) are very popular methods in information retrieval for creating an inverted index and querying terms. BR method searches the exact results of the textual information retrieval without ranking the results. VSM method searches and ranks the results. This study empirically compares the two methods. The research utilizes a sample of the corpus data obtained from Reuters. The experimental results show that the required times to produce an inverted index by the two methods are nearly the same. However, a difference exists on the querying index. The results also show that the numberof generated indexes, the sizes of the generated files, and the duration of reading and searching an index are proportional with the file number in the corpus and thefile size.
Designing of Medium-Size Humanoid Robot with Face Recognition Features Christian Tarunajaya; Oey, Kevin Wijaya; Reinard Lazuardi Kuwandy; Heri Ngarianto; Alexander Agung Gunawan; Widodo Budiharto
IPTEK The Journal for Technology and Science Vol 26, No 2 (2015)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (854.21 KB) | DOI: 10.12962/j20882033.v26i2.1018

Abstract

Nowadays, there have been so many development of robot that can receive command and do speech recognition and face recognition. In this research, we develop a humanoid robot system with a controller that based on Raspberry Pi 2. The methods we used are based on Audio recognition and detection, and also face recognition using PCA (Principal Component Analysis) with OpenCV and Python. PCA is one of the algorithms to do face detection by doing reduction to the number of dimension of the image possessed. The result of this reduction process is then known as eigenface to do face recognition process. In this research, we still find a false recognition. It can be caused by many things, like database condition, maybe the images are too dark or less varied, blur test image, etc. The accuracy from 3 tests on different people is about 93% (28 correct recognitions out of 30).
Sistem Kontrol Akses Berbasis Real Time Face Recognition dan Gender Information Putri Nurmala; Wikaria Gazali; Widodo Budiharto
ComTech: Computer, Mathematics and Engineering Applications Vol. 6 No. 2 (2015): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v6i2.2264

Abstract

Face recognition and gender information is a computer application for automatically identifying or verifying a person's face from a camera to capture a person's face. It is usually used in access control systemsand it can be compared to other biometrics such as finger print identification system or iris. Many of face recognition algorithms have been developed in recent years. Face recognition system and gender information inthis system based on the Principal Component Analysis method (PCA). Computational method has a simple and fast compared with the use of the method requires a lot of learning, such as artificial neural network. In thisaccess control system, relay used and Arduino controller. In this essay focuses on face recognition and gender - based information in real time using the method of Principal Component Analysis ( PCA ). The result achievedfrom the application design is the identification of a person’s face with gender using PCA. The results achieved by the application is face recognition system using PCA can obtain good results the 85 % success rate in face recognition with face images that have been tested by a few people and a fairly high degree of accuracy.
Implementasi dan Evaluasi Penerapan Globus Toolkit untuk Aplikasi Grid Computing Widodo Budiharto
ComTech: Computer, Mathematics and Engineering Applications Vol. 3 No. 1 (2012): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v3i1.2469

Abstract

Grid computing is a distributed computing technology that utilizes resources connected through a free computer network, yet coordinated with a specific mechanism. The development of grid computing infrastructure is not easy because it takes skill and experience in the installation and configuration of both Linux-based and open source program. In this study, the author built a grid computing infrastructure based on Debian 4, and used Globus Toolkit 4.1.2 on three computers. The WSRF technology was tried to run as an indication that the grid infrastructure has been successfully built. Based on some experiments in this study, grid computing can run well on the three computers with a user interface of web-based grid system using the UCLA Grid Portal. Overall the system runs fine, but it requires high experiences and comprehensions upon the Linux operating systems as well as computer networks in the installation process.
Online Training for Face Recognition System Using Improved PCA Widodo Budiharto
ComTech: Computer, Mathematics and Engineering Applications Vol. 2 No. 2 (2011): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v2i2.2952

Abstract

The variation in illumination is one of the main challenging problem for face recognition. It has been proven that in face recognition, differences caused by illumination variations are more significant than differences between individuals. Recognizing face reliably across changes in pose and illumination using PCA has proved to be a much harder problem because eigenfaces method comparing the intensity of the pixel. To solve this problem, this research proposes an online face recognition system using improved PCA for a service robot in indoor environment based on stereo vision. Tested images are improved by generating random values for varying the intensity of face images. A program for online training is also developed where the tested images are captured real-time from camera. Varying illumination in tested images will increase the accuracy using ITS face database which its accuracy is 95.5 %, higher than ATT face database’s as 95.4% and Indian face database’s as 72%. The results from this experiment are still evaluated to be improved in the future.
End-to-End Steering Angle Prediction for Autonomous Car Using Vision Transformer Ilvico Sonata; Yaya Heryadi; Antoni Wibowo; Widodo Budiharto
CommIT (Communication and Information Technology) Journal Vol. 17 No. 2 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i2.8425

Abstract

The development of autonomous cars is currently increasing along with the need for safe and comfortable autonomous cars. The development of autonomous cars cannot be separated from the use of deep learning to determine the steering angle of an autonomous car according to the road conditions it faces. In the research, a Vision Transformer (ViT) model is proposed to determine the steering angle based on images taken using a front-facing camera on an autonomous car. The dataset used to train ViT is a public dataset. The dataset is taken from streets around Rancho Palos Verdes and San Pedro, California. The number of images is 45,560, which are labeled with the steering angle value for each image. The proposed model can predict steering angle well. Then, the steering angle prediction results are compared using the same dataset with existing models. The experimental results show that the proposed model has better accuracy regarding the resulting MSE value of 2,991 compared to the CNN-based model of 5,358 and the CNN-LSTM combination model of 4,065. From the results of this experiment, the ViT model can replace the existing model, namely the CNN model and the combination model between CNN and LSTM, in predicting the steering angle of an autonomous car.
Co-Authors Alexander Agung Gunawan Antoni Wibowo Christian Tarunajaya Heri Ngarianto Ilvico Sonata Iman Herwidiana Kartowisastro Oey, Kevin Wijaya Putri Nurmala Reinard Lazuardi Kuwandy Wikaria Gazali Yaya Heryadi Yulianto, Budi