2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)最新文献_第5页

Recognition of Real-Time BISINDO Sign Language-to-Speech using Machine Learning Methods 基于机器学习方法的实时BISINDO手语语音识别

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127743

Muhammad Zulfikar Fauzi, R. Sarno, S. Hidayati

引用次数: 1

Comparison of Face Recognition Accuracy of ArcFace, Facenet and Facenet512 Models on Deepface Framework Deepface框架下ArcFace、Facenet和Facenet512模型人脸识别精度比较

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127799

A. Firmansyah, T. F. Kusumasari, E. N. Alam

{"title":"Comparison of Face Recognition Accuracy of ArcFace, Facenet and Facenet512 Models on Deepface Framework","authors":"A. Firmansyah, T. F. Kusumasari, E. N. Alam","doi":"10.1109/ICCoSITE57641.2023.10127799","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127799","url":null,"abstract":"Face recognition is one of the biometric-based authentication methods known for its reliability. In addition, face recognition is also currently very concerning, especially with the growing use and available technology. Many frameworks can be used for the face recognition process, one of which is DeepFace. DeepFace has many models and detectors that can be used for face recognition with an accuracy above 93%. However, the accuracy obtained needs to be tested, especially when faced with a dataset of Indonesian faces. This research will discuss the accuracy comparison of the Facenet model, Facenet512, from ArcFace, available in the DeepFace framework. From the comparison results, it is obtained that Facenet512 has a high value in accuracy calculation which is 0.974 or 97.4%, compared to Facenet, which has an accuracy of 0.921 or 92.1%, and ArcFace, which has an accuracy of 0.878 or 87.8%. The benefit of this research is to test how high the accuracy of the existing model in DeepFace is if tested with the Indonesian dataset. In this test, Facenet512 is the model that has the highest accuracy when compared to ArcFace and Facenet. This research is expected to help DeepFace users determine the best model to use and provide references to DeepFace developers for future development.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116498131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Feature Extraction in Hierarchical Multi-Label Classification for Dangerous Speech Identification on Twitter Texts 基于层次多标签分类的Twitter文本危险语音识别特征提取

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127774

D. Purwitasari, D. A. Navastara, Y. Findawati, Kresna Adhi Pramana, Agus Budi Raharjo

{"title":"Feature Extraction in Hierarchical Multi-Label Classification for Dangerous Speech Identification on Twitter Texts","authors":"D. Purwitasari, D. A. Navastara, Y. Findawati, Kresna Adhi Pramana, Agus Budi Raharjo","doi":"10.1109/ICCoSITE57641.2023.10127774","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127774","url":null,"abstract":"Dangerous speech is a strong hate speech that causes negative impacts, such as violence, crime, social pressure, trauma, and despair, and can lead to conflicts between groups. Raw data of Twitter texts need the necessary preprocess to obtain the proper training datasets for hate speech or even dangerous one. One reason is how to express hate speech related to mentions or hashtags. Because of the variants of context messages in raw Twitter posts which could be hate speech or not, the problem here is hierarchical and multi-label classification with three label types of hate speech status, issues, and dangerous levels. The issues in this work are about religion, ethnicity, and others. After handling preprocess, the word embedding includes data under-sampling because the dataset is not balanced. Additional stop-word dictionaries to overcome language-related vocabularies are also incorporated. To observe the preprocess effects in the classification problem, some methods of machine learning and deep learning, such as SVM, Bi-LSTM, and BERT are explored. Then we examined after hyper-parameter settings with performance indicators of subset accuracy and Hamming lost for imbalanced, in addition to F1 scores of micro and macro averages.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115326834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Convolutional Neural Network (CNN) Algorithm for Geometrical Batik Sade’ Motifs 几何蜡染图案的卷积神经网络(CNN)算法

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127829

Ni Wayan Parwati Septiani, Hendy Agung Setiawan, Mei Lestari, Irwan Agus, Rayung Wulan, A. Irawan, Sutrisno

{"title":"Convolutional Neural Network (CNN) Algorithm for Geometrical Batik Sade’ Motifs","authors":"Ni Wayan Parwati Septiani, Hendy Agung Setiawan, Mei Lestari, Irwan Agus, Rayung Wulan, A. Irawan, Sutrisno","doi":"10.1109/ICCoSITE57641.2023.10127829","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127829","url":null,"abstract":"In Indonesia, batik was not popular among all socio-economic groups until the 20th century. Recently, batik has been considered an essential part of Indonesian culture and heritage. Geometric batik patterns are recognized by their symmetry, horizontal repetition, and vertical and diagonal angles between shapes. Sade is one village located south of Lombok island. Woven fabrics typical of Sade Village have distinctive motifs that differ from those of Sukarara Village, Central Lombok. Sade's batik mostly has geometric patterns that are almost similar. There are 5 motifs in Sade, namely Selolot, kembang komak, tapok kamalo, ragi genep and batang empat. The Sade village’s economy, which mostly relied on the sales of its fabric production, has been placed under an enormous burden by the COVID-19 pandemic. There must be a new and creative way in order to sustain its market penetration. One possible approach is by linking the community of Sade village fabric producers to the nationwide established marketplace. We propose an ML-based mobile web application that is supposed to be used by ordinary users, not only the tourists who visited Sade village. This mobile web main feature is to do the image classification of the aforementioned motifs and to provide a list of Sade village fabric sellers on the marketplace so that interested users may purchase the product. Models were created using the CNN algorithm to classify batik-sade images. CNN is one frequently used deep learning algorithm for image classification. Image datasets consist of training, testing, and validation datasets. The training datasets contain 2398 photos, while the testing and validation datasets each have 480 data. Ten epochs of experimental data revealed that the suggested CNN model has a training loss of 0.0560 and a training accuracy of 0.9805.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123335197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Role of AI in the Education Sector in the Kingdom of Bahrain 人工智能在巴林王国教育部门的作用

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127838

Ghadeer Ismail Khalil, Hafsa Mohammad Sajjad, Manal Sohail, Zahra Ishfaq

{"title":"Role of AI in the Education Sector in the Kingdom of Bahrain","authors":"Ghadeer Ismail Khalil, Hafsa Mohammad Sajjad, Manal Sohail, Zahra Ishfaq","doi":"10.1109/ICCoSITE57641.2023.10127838","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127838","url":null,"abstract":"Machines can learn through experience, adapt to new input information, and carry out the necessary human-like duties thanks to artificial intelligence (AI). AI adaptation in the education industry has become more significant. This research aimed to determine the role of Artificial Intelligence (AI) on education in the Kingdom of Bahrain from a student-teacher perspective and examine its factors by adapting Technology Acceptance Model (TAM). To fulfil the objectives of this research, efficiency and convenience of implementing AI within education has been examined to further investigate the challenges faced by students and educators. A quantitative and qualitative approach was used to gather data from the universities in Bahrain, with a sample size of 383 determined by the Stratified Sampling method and Purposive Sampling. The analysis of the responses to the conducted survey resulted in a total of 501 responses. The results analysis revealed that both students and instructors believe security and privacy issues to be the most prevalent obstacle to the use of AI in education. Although AI tools and applications cover most of the ethical aspects, data privacy and security issues remain to be important concerns for users. Furthermore, both students and instructors agree that AI supports self- dependent learning, but it might be complex to use without a set of skills and some experience. In addition, the main limitation was the time consumed in collecting data. The research suggests methods to improve the results and overcome future challenges.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"40 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123737592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Systematic Literature Review of Generative Adversarial Network Potential In AI Artwork 人工智能艺术作品中生成对抗网络潜力的系统文献综述

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127706

Farrel Rasyad, Hardi Andry Kongguasa, Nicholas Christandy Onggususilo, Anderies, Afdhal Kurniawan, A. A. Gunawan

{"title":"A Systematic Literature Review of Generative Adversarial Network Potential In AI Artwork","authors":"Farrel Rasyad, Hardi Andry Kongguasa, Nicholas Christandy Onggususilo, Anderies, Afdhal Kurniawan, A. A. Gunawan","doi":"10.1109/ICCoSITE57641.2023.10127706","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127706","url":null,"abstract":"Humans have studied calligraphy and calculated programs to foster creativity for years. Image generation technology using artificial intelligence and Generative Adversarial Networks is currently reaching the peak of its performance. While there are newer and newer algorithms to improve the image generation system, the output of the images is still suitable at best and only excels in their category. While it is true that some of the images generated are good enough to be used, it is still unclear whether the capabilities of AI image generation can outperform their creative human counterparts. Therefore, this literature study aims to explore the basics of AI image generation, how they work, and what factors contribute to creating art such as simple pictures. Previous studies from several years ago show that most generated images are not good enough for creative usage because they only replicate traces of their dataset. The most significant factor contributing to this is the algorithm used and how it is used to create new images. In general, the concluded that while current AI-generated images are improving, they are still not creative enough to replace human creativity.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128393549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Reference Adaptive Control Design for CubeSat with Magnetorquer 磁致调速器立方体卫星模型参考自适应控制设计

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127853

A. T. Santoso, M. R. Rosa, Edwar

引用次数: 0

Classification of Emotions on Song Lyrics using Naïve Bayes Algorithm and Particle Swarm Optimization 基于Naïve贝叶斯算法和粒子群优化的歌词情感分类

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127851

Gerry Samhari Ramadhan, Budhi Irawan, C. Setianingsih, Figo Plambudi Dwigantara

{"title":"Classification of Emotions on Song Lyrics using Naïve Bayes Algorithm and Particle Swarm Optimization","authors":"Gerry Samhari Ramadhan, Budhi Irawan, C. Setianingsih, Figo Plambudi Dwigantara","doi":"10.1109/ICCoSITE57641.2023.10127851","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127851","url":null,"abstract":"A song is a unity of sound that contains a tone and lyrics. A song can contain a variety of emotions. Emotions in the song can arise because of the combination of lyrics and tones that create a beautiful sound and harmony. This research is about the emotional content of the song lyrics. This research began with collecting datasets in the form of song lyrics from kapanlagi.com, liriklaguindonesia.net, and liriklaguanak.com as a provider of song lyrics. Then preprocessing data consists of case folding, tokenizing, stop removal, and stemming. After that, the part of speech (POS) tagging process automatically labels the word in the text according to the word class. Labeling a word, whether it's a verb, adjective, or description, to be able to determine the song's emotional lyrics according to what we listen to takes the right method. The method used is the Naive Bayes Classifier and Particle Swarm Optimization methods, as methods used in performing text classification. In some studies, it was mentioned that the Naive Bayes Classifier method shows good results in the case of the classification of Indonesian text information, with an accuracy of 90%–96% using an inertia weight score of 1.0.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124890137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Attitude, Trust, and Subjective Norm Impact on Intention to Use Profile Verification in Dating Applications in Indonesia 态度、信任和主观规范对印度尼西亚约会应用中使用个人资料验证意图的影响分析

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127777

Kenny Prasetyo, Xenia Dharmawan, Erwin Ardianto Halim, Marylise Hebrard

{"title":"Analysis of Attitude, Trust, and Subjective Norm Impact on Intention to Use Profile Verification in Dating Applications in Indonesia","authors":"Kenny Prasetyo, Xenia Dharmawan, Erwin Ardianto Halim, Marylise Hebrard","doi":"10.1109/ICCoSITE57641.2023.10127777","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127777","url":null,"abstract":"Despite the popularity of online dating Application, there are increasing security issues and challenges with them, such as the creation of fake accounts and phishing, which are commonly called romance scams, one of which is fake user data or even completely fake profiles. This research will discuss the profile verification technology that has been developed in several online dating applications to verify the authenticity of user profiles using an algorithm capable of detecting fake profiles. This study used Sequential Equation Modeling (SEM) method and SMART PLS as a statistical tool. A total of 561 data from online dating application users in Indonesia were collected in October 2022. The purpose of this study was to determine the impact of Attitude, Trust, and Subjective Norm to intention to use profile verification in Dating Application in Indonesia. Attitude, Trust, and Subjective Norms will be special variables that affect the user's intention to use Profile Verification on Dating Applications in Indonesia. The results of the study found that all research hypotheses had a significant effect on each variable relationship in the research model.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126367225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Employee Ranking Based On Work Performance Using AHP and VIKOR Methods 基于AHP和VIKOR方法的员工工作绩效排名

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127814

Muhammad Yusuf Firdaus, Septi Andryana

{"title":"Employee Ranking Based On Work Performance Using AHP and VIKOR Methods","authors":"Muhammad Yusuf Firdaus, Septi Andryana","doi":"10.1109/ICCoSITE57641.2023.10127814","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127814","url":null,"abstract":"Employee ranking is an activity carried out by companies to rank employees based on the results of criteria that have been assessed. This is done to give an idea to the company how the value results from the criteria that have been obtained by employees. Related to this research, a Decision Support System is needed to rank the best employees, which uses a combination of 2 methods, namely the Analytical Hierarchy Process (AHP) method is used to weight each criterion and to test the consistency between criteria and Višekriterijumsko Kompromisno Rangiranje (VIKOR) is used to solve complex multi-criteria system problems that focus on ranking and selection of an alternative and determining the ideal solution. The criteria used in this research are Work Behavior Value (C1), SKP value (C2) and Work Performance Value (C3). For alternative data, employee data is used. The results of this study indicate that the employee with the highest rank is Hanung Harimba (KR1) with a value of Q = 0 and the employee with the lowest rank is Christina Thiveny (KR8) with a value of Q = 1.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114317360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0