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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmu Komputer dan Informasi JURNAL SISTEM INFORMASI BISNIS Jurnal Ilmiah Teknologi dan Rekayasa Matematika: Jurnal Teori dan Terapan Majalah Ilmiah Matematika Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) CommIT (Communication & Information Technology) Journal of the Indonesian Mathematical Society Journal of Information Technology and Computer Science (JOINTECS) MIND (Multimedia Artificial Intelligent Networking Database) Journal Journal of Applied Data Sciences

Ernastuti Ernastuti

Gunadarma University

Author-ID : 260582

Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics

Published : 19 Documents Claim Missing Document

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Accelerating Compression Time of the standard JPEG by Employing The Quantized YCbCr Color Space Algorithm Trini Saptariani; Sarifudin Madenda; Ernastuti Ernastuti; Widya Silfianti
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

In this paper, we propose a quantized YCbCr color space (QYCbCr) technique which is employed in standard JPEG. The objective of this work is to accelerate computational time of the standard JPEG image compression algorithm. This is a development of the standard JPEG which is named QYCBCr algorithm. It merges two processes i.e., YCbCr color space conversion and Q quantization in which in the standar JPEG they were performed separately. The merger forms a new single integrated process of color conversion which is employed prior to DCT process by subsequently eliminating the quantization process. The equation formula of QYCbCr color coversion is built based on the chrominance and luminance properties of the human visual system which derived from quatization matrices. Experiment results performed on images of different sizes show that the computational running time of QYCbCr algorithm gives 4 up to 8 times faster than JPEG standard, and also provides higher compression ratio and better image quality.

Comparison of Three Segmentation Methods for Breast Ultrasound Images based on Level Set and Morphological Operations Dewi Putrie Lestari; Sarifuddin Madenda; Ernastuti Ernastuti; Eri Prasetyo Wibowo
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science

Breast cancer is one of the major causes of death among women all over the world. The most frequently used diagnosis tool to detect breast cancer is ultrasound. However, to segment the breast ultrasound images is a difficult thing. Some studies show that the active contour models have been proved to be the most successful methods for medical image segmentation. The level set method is a class of curve evolution methods based on the geometric active contour model. Morphological operation describes a range of image processing technique that deal with the shape of features in an image. Morphological operations are applied to remove imperfections that introduced during segmentation. In this paper, we have evaluated three level set methods that combined with morphological operations to segment the breast lesions. The level set methods that used in our research are the Chan Vese (C-V) model, the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) model and the Distance Regularized Level Set Evolution (DRLSE) model. Furthermore, to evaluate the method, we compared the segmented breast lesion that obtained by each method with the lesion that obtained manually by radiologists. The evaluation is done by four metrics: Dice Similarity Coefficient (DSC), True-Positive Ratio (TPR), True-Negative Ratio (TNR), and Accuracy (ACC). Our experimental results with 30 breast ultrasound images showed that the C-V model that combined with morphological operations have better performance than the other two methods according to mean value of DSC metrics.

Cursive Handwriting Segmentation using Ideal Distance Approach Fitrianingsih Fitrianingsih; Sarifuddin Madenda; Ernastuti Ernastuti; Suryarini Widodo; Rodiah Rodiah
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Offline cursive handwriting becomes a major challenge due to the huge amount of handwriting varieties such as slant handwriting, space between words, the size and direction of the letter, the style of writing the letter and handwriting with contour similarity on some letters. There are some steps for recursive handwriting recognition. The steps are preprocessing, morphology, segmentation, features of letter extraction and recognition. Segmentation is a crucial process in handwriting recognition since the success of segmentation step will determine the success level of recognition. This paper proposes a segmentation algorithm that segment recursive handwriting into letters. These letters will form words using a method that determine the intersection cutting point of image recursive handwriting with an ideal image distance. The ideal distance of recursive handwriting image is an ideal distance segmentation point in order to avoid the cutting of other letter’s section. The width and height of images are used to determine the accurate segmentation point. There were 999 recursive handwriting input images taken from 25 researchers used for this study. The images used are the images obtained from preprocessing step. Those are the images with slope correction. This study used Support Vector Machine (SVM) to recognize recursive handwriting. The experiments show the proposed segmentation algorithm able to segment the image precisely and have 97% success recognizing the recursive handwriting.

Wood Classification Based on Edge Detections and Texture Features Selection Achmad Fahrurozi; Sarifuddin Madenda; Ernastuti Ernastuti; Djati Kerami
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science

One of the properties of wood is a mechanical property, includes: hardness, strength, cleavage resistance, etc. Among these properties there that can be measured or estimated by visual observation on cross-sectional areas of wood, which is based on inter-fiber density, fiber size, and lines that build the annual rings. In this paper, we proposed a new wood quality classification method based on edge detections. Edge detection is applied to the wood test images with the aim to improving the characteristics of wood fibers so as to make it easier to distinguish their quality. Gray Level Co-occurrence Matrix (GLCM) used to obtain wood texture features, while the wood quality classification done by Naïve Bayes classifier. Found in our experimental results that the first-order edge detection is likely to provide a good accuracy rate and precision. The second order edge detection is highly dependent on the choice of parameters and tends to give worse classification results, as filtering the original wood image, thus blurring characteristics related to wood density. Selection of features obtained from co-occurrence matrix is also quite affected the classification results.

Co-Authors Achmad Benny Mutiara Achmad Benny Mutiara Achmad Fahrurozi Aris Gunaryati, Aris Bambang Wahyudi Belawati H Widjaya Belawati H Widjaya Cut Maisyarah Karyati D. L. Crispina Pardede Desti Riminarsih Dewi Putrie Lestari Djati Kerami Djati Kerami Djati Kerami Eri Prasetyo Wibowo, Eri Prasetyo Ericks Rachmat Swedia Erwin Harahap Fitriani, Risma Rahmalia Fitrianingsih Fitrianingsih Ghifari Prameswari Natakusumah Haryanto . Henny Widowati Farida Kristiyanto, Yogi Muhammad Agus Muljanto Norawati Norawati Pribadi, Hanafi Indra Prihandoko Prihandoko Ravi A. Salim Ravi Ahmad Salim Ravi Ahmad Salim Rodiah Rodiah Sarifuddin Madenda Sarifudin Madenda Septi Andryana Sulistyo Puspitodjati Suryarini Widodo Teddy Mantoro Trini Saptariani Widya Silfianti

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Journal : International Journal of Electrical and Computer Engineering