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Representations as basis of cognitive processes 20th

引用

20th Annual German Conference on Artificial Intelligence, KI 1996

作者： Habel, Christopher University of Hamburg Computer Science Department and Doctoral Program in Cognitive Science Vogt-Kölln-Str. 30 Hamburg Germany

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Support vector machine and neural network algorithm approach to classifying facial expression recognition 5

Support vector machine and neural network algorithm approach...

引用

5th International Conference on Informatics and Computing, ICIC 2020

作者： Fatchan, Muhamad Hery Purnomo, Mauridhi Affandy Zainul Fanani, Ahmad Marlinda, Linda Doctoral Program of Computer Science Universitas Dian Nuswantoro Semarang Indonesia Institut Teknologi Sepuluh Nopember Computer Engineering Department Surabaya Indonesia

ISBN: (纸本)9781728180472

One of the obstacles to detecting facial emotions is the lack of analysis in the process of emotional expression on human faces based on a photo camera. Identifying features and implementing different feature combinations can improve accuracy, in most cases. Trial detection through the use of feature vectors with higher dimensions that contain facial emotions can provide a lot of information on the accuracy of the data. The purpose of this study is to determine the highest accuracy results from the comparison of Support Vector Machine and Neural Network Algorithms. It can be seen that the Support Vector Machine has the highest accuracy value, which is 87%, while the Neural Network algorithm only has an accuracy of 85%. The results of the ROC Curve show that the Support Vector Machine achieves the best AUC value, namely 0.97. Comparison between Neural Network algorithm and Support Vector Machine for prediction of emotions using data types with many variations of emotions including anger, sadness, happy and surprise. The Support Vector Machine method is an accurate algorithm and this method is also very dominant over other methods. Based on the Accuracy, AUC, and T-test method, this method falls into the best classification. © 2020 IEEE.

关键词： Face recognition

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Survey of data mining techniques for intrusion detection systems 5

Survey of data mining techniques for intrusion detection sys...

引用

5th International Conference on Informatics and Computing, ICIC 2020

作者： Cahyo, Aditya Nur Winarko, Edi Musdholifah, Aina Doctoral Program of Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Universitas Gadjah Mada Department of Computer Sciences and Electronic Yogyakarta Indonesia

ISBN: (纸本)9781728180472

Nowadays, the number of cyber-attacks is increasing;therefore, it is important for companies or organizations to secure their networks. Intrusion Detection System (IDS) is one of the core components used to secure networks. IDS's role is to detect an attack or attempted attack. The security tools are growing rapidly, along with the increasing number and variety of attacks carried out. The same with the development of IDS, a lot of research has been done to improve the ability of IDS to detect an attack. Many studies have used data mining techniques on IDS. This paper aims to conduct a comprehensive survey on the use of data mining techniques on IDS in the last five years. In this survey, we category the techniques used into several categories, and discuss each category in detail. © 2020 IEEE.

关键词： Surveys

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Musical Analysis of a computer Music Project, by computer-Assistance, for computer Music Applications 26

Musical Analysis of a Computer Music Project, by Computer-As...

引用

26th International computer Music Conference, ICMC 2000

作者： Liu, Jian-Li Hiraga, Rumi Igarashi, Shigeru Doctoral Program in Engineering University of Tsukuba Japan Bunkyo University Japan Department of Computer Science University of Tsukuba Japan

Daphne is a computer-assisted musical analysis system that analyzes musical structure and other information necessary for computer music applications, especially for performance synthesis. The obtained analysis results are stored in a style which extends the information of a note event so that application systems can share analysis information. Providing sheets of real musical scores, Daphne’s design includes a unique function of analysis database which stores analysis result of multiple editions of a piece. Users can make use of the database to consider how performance is generated based on the interpretation of each edition. In this paper, we describe how analysis information is stored and shared among computer music applications — performance synthesis with rules, performance visualization, and automated accompaniment. © 2000 ICMC. All Rights Reserved.

关键词： computer music

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Improving random forest method to detect hatespeech and offensive word 2

Improving random forest method to detect hatespeech and offe...

引用

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

作者： Nugroho, Kristiawan Noersasongko, Edy Purwanto Muljono Fanani, Ahmad Zainul Affandy Basuki, Ruri Suko Doctoral Program Dian Nuswantoro University Semarang Indonesia Faculty of Computer Science Dian Nuswantoro University Semarang Indonesia

ISBN: (纸本)9781728116556

Hate Speech is a problem that often occurs when someone communicates with each other using social media on the Internet. Research on hate speech is generally done by exploring datasets in the form of text comments on social media such as Twitter, Facebook and MySpace. This study aims to improve the performance of the Random Forest method in detecting hatespeech and crude speech. In this paper the researcher uses a twitter hate speech and offensive identification dataset that is classified using the Random Forest method which will be compared with the results of its accuracy with AdaBoost and Neural Network to detect hatespeech and crude speech. The detection results of hatespeech and crude speech identification resulted in an accuracy of 0.722 for the Random Forest method and 0.708 using AdaBoost and 0.596 using Neural Network method. © 2019 IEEE

关键词： Adaptive boosting

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Analysis Perceptions Regarding Student Exchange Using Simple Random Sampling and Analytical Hierarchy Process (AHP) Methods 9

Analysis Perceptions Regarding Student Exchange Using Simple...

引用

9th International Conference on Electrical Engineering, computer science and Informatics, EECSI 2022

作者： Octaria, Orissa Hartomo, Kristoko Dwi Sembiring, Irwan Purnomo, Hindriyanto Dwi Iriani, Ade Sediyono, Eko Computer Science Doctoral Program Universitas Kristen Satya Wacana Universitas Multi Data Palembang Palembang Indonesia Computer Science Doctoral Program Universitas Kristen Satya Wacana Salatiga Indonesia

ISBN: (数字)9786239213565

ISBN: (纸本)9781665470438

Student exchange is a system for students to be able to try education abroad for a certain period of time. The time period has a wide range of time ranging from a month to an academic year, depending on the type of exchange the student participating in. Students who qualify for an exchange program must be educated, knowledgeable, and committed to undertaking a program of activities that is consistent with the expected goals. Furthermore, to find out the perception of students at Multi Data Palembang University on student exchange, the Analytic Hierarchy Process (AHP) method was used as a decision-making tool. This study uses questionnaires as a data collection medium, questionnaires are distributed to students by taking samples using the simple random sampling method. The test variables will also be tested for validity and reliability, to measure variables that can be used for research. The whole process that was achieved was aimed at getting students' views on student exchange in the Merdeka Belajar Kampus Merdeka (MB-KM). At the AHP stage, it can be said that students do not understand what MB-KM and student exchange are. The value obtained is 'do not know' of 0.875 and 'improved' by 0.860. According to students, most student exchanges can improve individual abilities. © 2022 Institute of Advanced Engineering and science (IAES).

关键词： AHP reliability simple random sampling validity

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A Novel Approach to Collect and Analyze Market Customer Behavior Data on Online Shop 2

A Novel Approach to Collect and Analyze Market Customer Beha...

引用

2nd International Conference on Innovative and Creative Information Technology, ICITech 2021

作者： Somya, Ramos Winarko, Edi Privanta, Sigit Doctoral Program in Computer Science FMIPA UGM Universitas Gadjah Mada Yogyakarta Indonesia FMIPA UGM Universitas Gadjah Mada Department of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9781728197463

Online shopping activities are currently experiencing a significant increase due to the development of the reach of the internet services and the changed activities from offline to online. The data analysis generated from online shopping activities is necessary to determine the right sales strategy. One of the types of data that needs to be analyzed is market consumer behavior data in online shops, generated in the form of clickstream data. Currently, there was not any research that examines the determination of clickstream data components, clickstream data recording mechanism, and how to analyze clickstream data components in online shops properly. This paper describes the architecture of the proposed online shop application, the module to record the clickstream data, and the method to analyze the clickstream data. Based on our evaluation, eight clickstream data components were successfully recorded in the database using Asynchronous JavaScript and XML (AJAX) technology. The clickstream data component that contains market customer behavior data is Multi-Criteria Decision Making (MCDM) data and has been analyzed using the Simple Additive Weighting (SAW) ranking method. © 2021 IEEE.

关键词： Consumer behavior

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Systematic Literature Review of Text Feature Extraction 7

Systematic Literature Review of Text Feature Extraction

引用

7th International Conference on Informatics and Computing, ICIC 2022

作者： Mulyanto, Agus Hartati, Sri Wardoyo, Retantyo Universitas Gadjah Mada Doctoral Program in Computer Science Yogyakarta Indonesia Universitas Gadjah Mada Faculty of Mathematics and Natural Sciences Department of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Text data has essential information in it depending on a party who can process the data. Text feature extraction techniques have opened various ways to carry out the analysis process from structured to unstructured data. Based on the development of text extraction, which is widely used today. This Systematic Literature Review (SLR) paper analyzes the methods widely used in current text extraction research studies. Writing this SLR implements the PICOC method. Trends in previous studies regarding text extraction have been analyzed in this study. The total publications used are 23 articles that have been carefully observed in a systematic literature review to answer the research questions that have been formulated. © 2022 IEEE.

关键词： Feature extraction

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New Architecture Quantum Perceptron using Quantum Circuit

New Architecture Quantum Perceptron using Quantum Circuit

引用

2021 International Conference on Data science, Artificial Intelligence, and Business Analytics, DATABIA 2021

作者： Solikhun, Solikhun Efendi, Syahril Zarlis, Muhammad Sihombing, Poltak Universitas Sumatera Utara Doctoral Program Faculty of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia

ISBN: (纸本)9781665426800

the learning algorithm that is not optimal is due to the incomplete use of quantum in the perceptron quantum learning algorithm which is the background of this research. Previous research has shown that the proposed architectural form still needs to increase its probability value to be more optimal. The previous probability was 90.7%. The proposed model is a quantum circuit architecture in a quantum perceptron algorithm consisting of a quantum bit gate. The researchers conducted training and testing of the proposed quantum circuit architecture using quantum computer of the IBM Quantum Experience. This research produces a perceptron quantum architecture model using a quantum circuit that can solve problems regarding data classification. After measuring the proposed quantum circuit architecture, it shows a 100% probability. After training and testing, the probability is 100%, the same as that at the time of measurement. Then it produces the same output of |111100000000000000〉. The resulting probability shows a significant increase from the previous 90, 7%. © 2021 IEEE.

关键词： Probability

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Fake smile detection using linear support vector machine

Fake smile detection using linear support vector machine

引用

International Conference on Data and Software Engineering, ICODSE 2015

作者： Gede Aris Gunadi, I. Harjoko, Agus Wardoyo, Retantyo Ramdhani, Neila Computer Science Gajah Mada University Yogyakarta Indonesia Doctoral Program of Computer Science Gajah Mada University Yogyakarta Indonesia Faculty of Psychology Gajah Mada University Yogyakarta Indonesia

ISBN: (纸本)9781467384285

Fake smile is an emotional sign on the face that can be used as information for non-verbal communication. One of its functions is for lie detection purpose based on the information of emotional sign generated on the face. The emergence of fake smile indicates that there are negative emotions, uncomfortable feeling, and something hidden in a person. This research aims to detect fake smile. In fact, real smile is characterized by the contraction of zygomatic major muscle on the edge of mouth corner and obicularis oculli muscle on the eyelids. However, on a fake smile, zygomatic major muscle experiences contraction, but obicularis oculli muscle doesn't contract. Contraction of the zygomatic major muscle is identified by the appearance of wrinkles on the cheeks corner of the mouth, whereas obicularis oculli contraction is identified by the feature value of eye elongation. On the test image, segmentation of RoI (Region of Interest) is done on cheeks and eyes. On the RoI (Region of Interest) cheeks, wrinkle density is calculated;whereas elongation value is calculated on the RoI (Region of Interest) eyes. Based on the two variables above, with support vector machine linear for its classification, smile is classified into two classes, i.e. real smile and fake smile. The test result showed that the accuracy of system is 86 %, whereas the error rate is 14%. © 2015 IEEE.

关键词： Support vector machines

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