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All Journal Humaniora ComTech: Computer, Mathematics and Engineering Applications Engineering, Mathematics and Computer Science Journal (EMACS)
Alexander A. S. Gunawan
Bina Nusantara University
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics

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Journal : ComTech: Computer, Mathematics and Engineering Applications

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Pengembangan Program Aplikasi Enhanced Machine Control dengan Python untuk Metode Interpolasi Newton Alexander A. S. Gunawan; Jimmy Linggarjati
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.v3i1.2396

Abstract

Nowadays, one of industrial main problems is the flexibility of machines to be customized since they are designed based on certain standard. This research develops software for CNC (Computer Numerically Controlled) machine in order to execute the Newton Interpolation using Python. The platform used in the CNC machine is EMC (Enhanced Machine Control) and GUI (Graphical User Interface) AXIS on the operating system Linux Ubuntu. The Newton interpolation is used to create a curve based on several point determined by user. By converting this curve into G-Code, which could be read by CNC machine, the machine can move according to curve designed by user. This research is an initial study to customize the CNC machine and will continue to fulfill the user needs. This research obtained a program that is able to run well up to 4 input pairs. The higher number inputs will cause the oscillation in the interpolation curve.
Pendeteksian Bagian Tubuh Manusia untuk Filter Pornografi dengan Metode Viola-Jones Benny Senjaya; Alexander A. S. Gunawan; Jerry Pratama Hakim
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.v3i1.2447

Abstract

Information Technology does help people to get information promptly anytime and anywhere. Unfortunately, the information gathered from the Internet does not always come out positive. Some information can be destructive, such as porn images. To mitigate this problem, the study aims to create a desktop application that could detect parts of human body which can be expanded in the future to become an image filter application for pornography. The detection methodology in this study is Viola-Jones method which provides a complete framework for extracting and recognizing image features. A combination of Viola-Jones method with Haar-like features, integral image, boosting algorithm, and cascade classifier provide a robust detector for the application. First, several parts of the human body are chosen to be detected as the data training using the Viola-Jones method. Then, another set of images (similar body parts but different images) are run through the application to be recognized. The result shows 86.25% of successful detection. The failures are identified and show that the inputted data are completely different with the data training.
Co-Authors Benny Senjaya Heri Ngarianto Jerry Pratama Hakim Jimmy Linggarjati Muhammad Aras