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White Bread Mold Detection using K-Means Clustering Based on Grey Level Co-Occurrence Matrix and Region of Interest

White Bread Mold Detection using K-Means Clustering Based on...

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2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Putra, Qori Alfatah Sari, Christy Atika Rachmawanto, Eko Hari Cahyo, Nur Ryan Dwi Mulyanto, Edy Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Department of Informatics Engineering Semarang Indonesia National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

This research paper presents a bread mold identification system that utilizes digital image processing techniques, specifically K-means clustering and thresholding, to accurately detect and classify mold-infected areas on bread. The system aims to provide valuable information regarding the safety of consuming mold-contaminated bread, enabling consumers to make informed decisions and reduce the risk of health issues associated with consuming mold-infested bread. the K-means clustering algorithm for mold classification, considering factors such as the number of iterations and the distance metric within the feature space to determine its accuracy. The GLCM feature extraction technique is employed to extract texture information from bread images, encompassing features such as standard deviation (110.62), contrast (1.46), energy, and homogeneity (0.96 and 0.77, respectively). Experimental results demonstrate that the Euclidean Distance yielded the highest result of 72.73, the Cosine Distance obtained the highest result of 8.25, and the City Block Distance obtained the highest result of 92.11. These findings showcase the effectiveness of the system in accurately detecting and classifying mold-infected areas on bread, thereby aiding in ensuring food safety and reducing health risks for consumers. © 2023 IEEE.

关键词： Image segmentation

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Mammogram Breast Cancer Classification Based on Deep-Convolutional Neural Network

Mammogram Breast Cancer Classification Based on Deep-Convolu...

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2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Amadea, Avissa Aurellia Sari, Christy Atika Rachmawanto, Eko Hari Sari, Wellia Shinta Noori, Mohammed S. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Based on WHO's data, breast cancer is one of the most deadly diseases that has claimed many victims, especially women. This disease begins with the presence of an undetected and eventually turns into malignant (cancer). This happens due to ignorance of the importance of having a medical check-up even though in good health. Doctors and researchers can prevent the development of tumor cells through treatment that begins with radiological examinations to identify the possibility of a person being affected by this disease. One of the most frequently used techniques is Mammography. This technique can detect the presence of tumor cells using advanced technology and several methods in displaying the patient's diagnostic results on low-dose X-rays in the form of mammogram images. The technology is inseparable from the methods used to identify the presence of tumor cells. In this study, we have proposed the CNN method based on the deep-CNN model to identify mammogram images in the detection of breast cancer cells with average evaluation results in terms of accuracy, precision, recall, specificity, and f-measure on mammogram image datasets of 99.52%, 99.72%, 99.31%, 99.72%, and 99.5%. These results showed that this method has a good performance in breast cancer detection. © 2023 IEEE.

关键词： Diseases

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

引用

2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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Decision Support System in Determining the Achievement of Widyaiswara Value Using WASPAS and TOPSIS Algorithm 1

Decision Support System in Determining the Achievement of Wi...

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1st International Conference on technology Innovation and Its Applications, ICTIIA 2022

作者： Pratama, Yudhistira Adhitya Iswara, Bagus Ajie Nababan, Adli Abdillah Information System Studies Program Pelita Harapan University Medan Campus Faculty Of Computer Science Medan Indonesia Master's Study Program Informatics Engineering Universitas Sumatera Utara Faculty Of Computer Science And Information Technology Medan Indonesia Digital Business Study Program Stmik Pelita Nusantara Medan Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material by the BPSDM PROVSU. However, the assessment process that occurs is still not precise and time-consuming. Therefore, to minimize this, a decision support system is needed that can minimize time errors and data processing in decision-making so that the assessment runs well and accurately. This system was built by applying the WASPAS method and the TOPSIS method. Based on the results of tests carried out five times, the results of the WASPAS method processing time resulted in an average processing time of 0.00029791 ms and an average memory usage value of 2.836.44 kb, while the results of the TOPSIS method processing time test resulted in an average processing time - an average of 0.000296428 ms and an average memory usage value of 2.862.34 kb. © 2022 IEEE.

关键词： Decision support systems

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Actor and Use Case Extraction from Text-Based Requirement Specification

Actor and Use Case Extraction from Text-Based Requirement Sp...

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International Conference Image Processing, Computers and Industrial Engineering (ICICIE’2014, Kuala Lumpur)

作者： Elisa Margareth Sibarani Andry Hutagaol Deppy Simarmata Juniaty Manihuruk Del Institute of Technology the Informatics Engineering Study Program Del Institute of Technology

Initial stage in software development lifecycle is requirements gathering steps which results a text-based requirements specification *** problem in analyzing those requirements is the difficulty of identifying the functionality of the software,especially when there are so many descriptions elicited from the gathering *** objective of this research is analyzing the process to identify actor and use case of the system to be *** the requirements were described in the form of natural language,therefore it needs natural language *** proposed solution is simplification form by only doing the syntax analysis to provide a quick *** tool is built in Java by accept active sentences in *** evaluation result proves that the tool is able to list actor and use cases from a given system *** future work is able to process passive sentence with complex structure not only in the Subject-Predicate-Object form.

关键词： Software requirements actor use case syntax analysis

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Sinergy of art and animation technology in multimedia performance art creation entitled sad ripu

Sinergy of art and animation technology in multimedia perfor...

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Conference on New Media Studies (CoNMedia)

作者： I Made Marthana Yusa Putu Satria Udyana Putra I Nyoman Agus Suarya Putra Study Program of Informatics Technology STMIK STIKOM Indonesia Denpasar INDONESIA Study Program of Informatics Technology : Multimedia Design Subject STMIK STIKOM Indonesia Denpasar Bali-Indonesia

ISBN: (纸本)9781509062850

This research is aimed to create synergistic creation between art and technology in form of multimedia performance art. It was formed in combination of motion graphic animation from contemporary Balinese ethnic designed style mask, packed in a contemporary dance performance package. This collaborative project also tries to explore the potential of ontological and terminology on multimedia, which is previously used in the performing arts world. The kinesics aesthetic aspects are explored, by aligning the motion of the contemporary dancers, with motion graphic showing the animation of the composition of the mask part, into a whole contemporary Balinese style mask. The final result of this collaborative project is able to propose a formulation of a collaborative multimedia performance art that considers the kinesics aspect as an important element that synergizes dance motion with contemporary motion graphic mask animation.

关键词： Art Animation Multimedia communication Visualization Media Collaboration

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Development of customizable analytical derivation tool for algebraic function

Development of customizable analytical derivation tool for a...

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International Conference of Advanced informatics: Concept, Theory and Application (ICAICTA)

作者： Hendra Hadhil Choiri Nur Ulfa Maulidevi Informatics Engineering Study Program Institute of Technology Bandung Bandung Indonesia

One of the major problems in differential calculus is determining the derivative value of a function. A commonly used method is numerical derivative. The value obtained by this method is just approximation value. More accurate derivative value is obtained through analytic approach, by looking for general forms of the derivative function. Problem solving agent approach can be utilized to develop such tool, where the operators and constants in the function should be easily customized. It requires four steps in deriving function: parsing, deriving, simplification, and output returning step. User enters the function in a string, and it will be converted into an abstract syntax tree. This tree is traced by DFS algorithm to be derived and simplified. Based on the test results, the analytical derivation requires short processing time. Derivative results are correct, but simplifications are less optimal in some test cases. The modification of constants, operators, and the derivative rules can be done easily.

关键词： Syntactics Calculus Abstracts MATLAB informatics Problem-solving Polynomials

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AlexNet Architecture Based Convolution Neural Network for Realtime Audio to Text Translator of Bisindo Hand Sign

AlexNet Architecture Based Convolution Neural Network for Re...

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2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Sujatmiko, Dhiki Sari, Christy Atika Rachmawanto, Eko Hari Krismawan, Andi Danang Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Animation Semarang Indonesia Mosul University Presidency University of Mosul Department of Computer Science Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Deafness is a condition that results in the loss of hearing function, hindering the reception of information such as oral communication that relies on auditory senses. Consequently, individuals with hearing impairment experience communication barriers and may have limited or no ability to respond. One solution is the use of sign language. In Indonesia, there are two known sign languages: Sibi and Bisindo. Both serve the same function but differ in their style of movement and expression. Bisindo is considered more flexible as it conveys meaning based on the Indonesian language. However, the universal understanding of this language solution is still limited among many people. Therefore, a program is needed to facilitate translation between deaf individuals who use sign language and their counterparts who do not communicate through sign language. CNN (Convolutional Neural Network) is a deep learning algorithm used for training visual input data recognition by computer systems. There are various CNN-based architectures, and one of them is AlexNet. Based on the author's testing, the AlexNet architecture proves to be suitable for real-time sign language translation. The evaluation of the system involved 7,800 datasets and 520 testing instances, with an average accuracy of 468 correct translations. When averaged, the system achieved a 90% accuracy rate, representing a 100% increase in accuracy compared to previous approaches. © 2023 IEEE.

关键词： Audition

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Optimization of hyper parameter bandwidth on naïve Bayes kernel density estimation for the breast cancer classification 2

Optimization of hyper parameter bandwidth on naïve Bayes ke...

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2nd International Conference on Information and Communications technology, ICOIACT 2019

作者： Sasongko, Theopilus Bayu Arifin, Oki Al Fatta, Hanif Information Technology Department Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Management of Informatics Study Program Economy and Business Departement Politeknik Negeri Lampung Lampung Indonesia

ISBN: (纸本)9781728116556

Cancer is viewed as the most harmful disease in the world. One of the most deadly cancer diseases attacking the women is breast cancer. In this paper, used Naïve Bayes classifier Kernel Density Estimation in breast cancer Wisconsin dataset take from UCI data repository. Naïve Bayes with Kernel Density Estimation was used as it could enable the Naïve Bayes to process the quantitative data. However, the performance of KDE (kernel density estimation) highly depends upon the size of the bandwidth parameter used to control the curve. The problem an accurate choice of parameter bandwidth (h) using trial and error technique requires a long process. A large bandwidth (h) will over-smooth the density and mask the structure in the data, a small bandwidth (h) will yield a density estimate that is spiky and very hard to interpret. The aim of this research is to compare the optimization of grid search parameter with the genetic algorithm to determine the bandwidth parameter (h) on the Naïve Bayes Kernel Density Estimator algorithm. The parameters used to compare the two optimization methods included accuracy, AUC (Area under Curve), and computation time. The experiment results on the test of the significance value on the comparison of grid search and algorithm in determination of the bandwidth parameter (h) naïve Bayes kernel density used Mann-Whitney Test. The result of the significance ranking showed that mean rank of the genetic algorithm accuracy was 489.95 better than the mean value of the rank of grid search accuracy at only 189.05, mean rank of AUC genetic algorithm was 491.82 better than mean rank of AUC grid search only at 187.18. The mean rank of computation time grid search was 243.37 faster than mean rank of computation time genetic algorithm at 435.63. © 2019 IEEE

关键词： Classification (of information)

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Stabilization of nonlinear systems with coarse quantization

Stabilization of nonlinear systems with coarse quantization

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World Congress on Intelligent Control and Automation (WCICA)

作者： Wei Ren Junlin Xiong Informatics Engineering Study Program Institute of Technology Bandung Bandung Indonesia

This paper addresses feedback stabilization problem for nonlinear dynamic systems with quantized measurements and delays in the presence of external disturbances. In the context, the quantizer has two parameters to adjust the center and the range. The applied controller switches between zooming out phase and zooming in phase repeatedly. Both two phases are divided into two modes. First, based on the trajectory and mechanism of the whole closed-loop system, both the state feedback stabilization and the output feedback stabilization are studied and the results on ISS property are given. Further, we consider the cases with delays, and achieve stabilizable results.

关键词： Quantization (signal) Nonlinear systems Delays State estimation Closed loop systems Output feedback

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