Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664877
Dede Sukmawan, D. Handayani, D. A. Dewi
Sukabumi Regency is one of the largest regencies on the island of Java. With a large area and a fairly dense population, it creates its own problems, such as in managing the potential of places and communities. The purpose of this research is to explore the potential of Sukabumi Regency through Instagram social media with #sukabumiupdate. Data collection is done by taking pictures from social media Instagram, the data taken is 6,970 images. Each data that has been collected is divided into 4 (four) class categories based on the type of image, namely Tourism class, culture class, culinary class, and handicrafts. Then the data is classified using a deep learning approach with three methods, namely CNN, VGG16, and VGG19. These three models are very good at image processing. From the results of data processing through the CNN approach, the accuracy value is up to 91%, then the VGG16 approach has an accuracy value of 99%, and finally, through the VGG19 approach, the accuracy is 95%. So it can be ascertained that from the three models of the deep learning approach the best accuracy value is VGG16.
{"title":"Deep Learning Approaches to Identify Sukabumi Potentials Through Images on Instagram","authors":"Dede Sukmawan, D. Handayani, D. A. Dewi","doi":"10.1109/ICCED53389.2021.9664877","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664877","url":null,"abstract":"Sukabumi Regency is one of the largest regencies on the island of Java. With a large area and a fairly dense population, it creates its own problems, such as in managing the potential of places and communities. The purpose of this research is to explore the potential of Sukabumi Regency through Instagram social media with #sukabumiupdate. Data collection is done by taking pictures from social media Instagram, the data taken is 6,970 images. Each data that has been collected is divided into 4 (four) class categories based on the type of image, namely Tourism class, culture class, culinary class, and handicrafts. Then the data is classified using a deep learning approach with three methods, namely CNN, VGG16, and VGG19. These three models are very good at image processing. From the results of data processing through the CNN approach, the accuracy value is up to 91%, then the VGG16 approach has an accuracy value of 99%, and finally, through the VGG19 approach, the accuracy is 95%. So it can be ascertained that from the three models of the deep learning approach the best accuracy value is VGG16.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"34 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81894846","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664792
Mukhlis Ali, Dwi M Lestari, Taufik Rahman
The rooftop photovoltaic system is one of the renewable energy sources which is pushed by the Indonesian government to use as alternative energy in public and private buildings. But, the use of PV rooftops in small public housing is still low due to the lack of design standards which makes banking and financial institution do not have the interest to make special loan schemes for PV rooftops. This research wants to propose a design standard that is suitable for 30/60-type houses, a small public housing which popular in Indonesia due to the subsidized loan scheme from the government, using PVSyst simulation. The location is set in Ujung Genteng, Sukabumi because it has good solar energy potential (DNI=3.502kWh/m2 per day). The results of this research based on the PVSyst simulation, the PV rooftop design which is suitable for a 30/60-type house is consists of 4 units of 275Wp PV panel, Inverter 450Vac, and 2 units of 12V/200Ah battery.
{"title":"Design of Rooftop Photovoltaic System for 30/60- type House in Sukabumi, Indonesia using PVSyst Simulation","authors":"Mukhlis Ali, Dwi M Lestari, Taufik Rahman","doi":"10.1109/ICCED53389.2021.9664792","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664792","url":null,"abstract":"The rooftop photovoltaic system is one of the renewable energy sources which is pushed by the Indonesian government to use as alternative energy in public and private buildings. But, the use of PV rooftops in small public housing is still low due to the lack of design standards which makes banking and financial institution do not have the interest to make special loan schemes for PV rooftops. This research wants to propose a design standard that is suitable for 30/60-type houses, a small public housing which popular in Indonesia due to the subsidized loan scheme from the government, using PVSyst simulation. The location is set in Ujung Genteng, Sukabumi because it has good solar energy potential (DNI=3.502kWh/m2 per day). The results of this research based on the PVSyst simulation, the PV rooftop design which is suitable for a 30/60-type house is consists of 4 units of 275Wp PV panel, Inverter 450Vac, and 2 units of 12V/200Ah battery.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"35 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86115511","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664852
Ryan Ahasan Al-Helal, Agung Ginanjar, M. A. Ayu
Social media has been growing in popularity over the past few years. Many activities done in social media platforms, and some of those activities may affect individual’s perception and self-esteem. Changes in self-esteem can affect the way people approaching their lives. This study aims to identify the correlation between some factors related to the use of social media and individual’s self-esteem. Data were collected through survey-questionnaire which was distributed through Google Form. It is found that social comparisons influences individual’s self-esteem. However, this effect differs between males and females. Correlational analysis also show that social comparison’s impacts and behaviors are prominent mainly in females. As well, females who score: higher in Neuroticism tend to socially compare more and are prone to lower self-perception; higher in Extraversion are likely to do social comparison behaviors; and higher in Conscientiousness are likely to have better self-esteem. Overall, time spent on social media, narcissism, and age generally do not influence social comparison, but engagement in life may affect it.
{"title":"Impacts on Individual’s Self-Esteem from the Use of Social Media","authors":"Ryan Ahasan Al-Helal, Agung Ginanjar, M. A. Ayu","doi":"10.1109/ICCED53389.2021.9664852","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664852","url":null,"abstract":"Social media has been growing in popularity over the past few years. Many activities done in social media platforms, and some of those activities may affect individual’s perception and self-esteem. Changes in self-esteem can affect the way people approaching their lives. This study aims to identify the correlation between some factors related to the use of social media and individual’s self-esteem. Data were collected through survey-questionnaire which was distributed through Google Form. It is found that social comparisons influences individual’s self-esteem. However, this effect differs between males and females. Correlational analysis also show that social comparison’s impacts and behaviors are prominent mainly in females. As well, females who score: higher in Neuroticism tend to socially compare more and are prone to lower self-perception; higher in Extraversion are likely to do social comparison behaviors; and higher in Conscientiousness are likely to have better self-esteem. Overall, time spent on social media, narcissism, and age generally do not influence social comparison, but engagement in life may affect it.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"9 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90776546","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664862
Surjandy, Meyliana, K. Oktriono, A. W. Kusumaningtyas, G. H. Prakosa
Blockchain technology, as appeared in several studies, is perceived to improve organizational performance. Historically, previous research indicated that technology is one of four essential aspects of organizational behavior. However, the research on the impact of Blockchain technology's influence on organizational behavior is in the early phase. This qualitative research with bibliography technique is facilitated by Publish and Perish tools aiming to explore the essential factors of Blockchain Technology that influence four essential factors (people, structure, environment, and technology) of Organizational Behavior including confidentiality, reliability, and authenticity of data. In this frame, the research collected 34 selected papers — the 16 essential factors found in this study impacted the behavioral organization directly. The study result is essential for the industry that will implement Blockchain to prepare the strategy and provide a clear picture of Blockchain technology's impact on industry behavioral organization
区块链技术，正如在几项研究中出现的那样，被认为可以提高组织绩效。以往的研究表明，技术是组织行为的四个基本方面之一。然而，关于区块链技术对组织行为影响的研究还处于早期阶段。采用文献技术的定性研究是通过Publish and destroy工具来进行的，旨在探索区块链技术的基本因素，这些因素影响组织行为的四个基本因素(人、结构、环境和技术)，包括数据的保密性、可靠性和真实性。在这个框架下，本研究收集了34篇精选论文——本研究中发现的16个基本因素直接影响了行为组织。研究结果对实施区块链技术的行业制定区块链战略具有重要意义，为区块链技术对行业行为组织的影响提供了清晰的图景
{"title":"The Influence of Blockchain Technology Factors on the Four Aspects of Organizational Behavior","authors":"Surjandy, Meyliana, K. Oktriono, A. W. Kusumaningtyas, G. H. Prakosa","doi":"10.1109/ICCED53389.2021.9664862","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664862","url":null,"abstract":"Blockchain technology, as appeared in several studies, is perceived to improve organizational performance. Historically, previous research indicated that technology is one of four essential aspects of organizational behavior. However, the research on the impact of Blockchain technology's influence on organizational behavior is in the early phase. This qualitative research with bibliography technique is facilitated by Publish and Perish tools aiming to explore the essential factors of Blockchain Technology that influence four essential factors (people, structure, environment, and technology) of Organizational Behavior including confidentiality, reliability, and authenticity of data. In this frame, the research collected 34 selected papers — the 16 essential factors found in this study impacted the behavioral organization directly. The study result is essential for the industry that will implement Blockchain to prepare the strategy and provide a clear picture of Blockchain technology's impact on industry behavioral organization","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"36 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84197622","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664883
Ivana Lucia Kharisma, R. Handayanto, D. A. Dewi
The Coronavirus or Covid-19 has spread widely throughout the world since the beginning of 2020. WHO provides basic guidance in preventing the spread of the virus that can be done by the community. One of them is the use of masks when doing activities outside the home. Lack of awareness in mask usage become the obstacle in the process of efforts to prevent the spread of covid 19. The aim of this research is to develop a face mask detection model by implementing the convolutional neural network and pre trained CNN algorithm. The accuracy of the proposed models in training process, the accuracy of CNN, VGG16, and VGG19 are 97.79%, 99.87% and 100%, respectively. The proposed models evaluated using confusion matrix using testing datasets given.
{"title":"Face Mask Detection In The Covid-19 Pandemic Era by Implementing Convolutional Neural Network and Pre-Trained CNN Models","authors":"Ivana Lucia Kharisma, R. Handayanto, D. A. Dewi","doi":"10.1109/ICCED53389.2021.9664883","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664883","url":null,"abstract":"The Coronavirus or Covid-19 has spread widely throughout the world since the beginning of 2020. WHO provides basic guidance in preventing the spread of the virus that can be done by the community. One of them is the use of masks when doing activities outside the home. Lack of awareness in mask usage become the obstacle in the process of efforts to prevent the spread of covid 19. The aim of this research is to develop a face mask detection model by implementing the convolutional neural network and pre trained CNN algorithm. The accuracy of the proposed models in training process, the accuracy of CNN, VGG16, and VGG19 are 97.79%, 99.87% and 100%, respectively. The proposed models evaluated using confusion matrix using testing datasets given.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"43 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82723703","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}
It's even one year since the COVID-19 pandemic hit Indonesia, to anticipate it, the government brought in a COVID-19 vaccine. Various types of COVID-19 vaccine have been introduced to Indonesia, including which ones will be considered the best according to the community through the Twitter platform. One of the venues that creates the most public sentiment is Twitter. It can be determined whether the public fully approves or rejects the existence of vaccination in Indonesia by analyzing public sentiment surrounding the COVID-19 vaccine. Data acquisition using a crawling procedure by connecting the Twitter API, pre-processing, sentiment categorization, and sentiment analysis outcomes are the stages of the sentiment analysis process to become a sentiment analysis application. The PHP and MySQL programming languages are used to create the database for the sentiment analysis application. After the application has been fully implemented, it can do sentiment analysis from each dictionary probability using the Naive Bayes Classifier approach. The study of the two keywords "vaksin covid" and "vaksin corona" yielded the following results. It has 93% positive sentiment results, 72% negative sentiment results, and 35% neutral sentiment outcomes, with an accuracy of 94.74% and 75.47% per keyword. Meanwhile, the Sinopharm vaccine, which has the most positive attitude with the terms "vaksin sinovac," "vaksin astrazeneca," "vaksin sinopharm," and "vaksin nusantara," has 84 percent tweets with a 74.23% accuracy rate.
{"title":"Indonesian Twitter Sentiment Analysis Application on The Covid l9 Vaccine Using Naive Bayes Classifier","authors":"A. Erfina, Moneyta Dholah Rosita Ndk, Rahmat Hidayat, Aris Subagja, Haerul Ramadhan, C.S.A. Teddy Lesmana, Sudin Saepudin, Muhamad Muslih","doi":"10.1109/ICCED53389.2021.9664864","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664864","url":null,"abstract":"It's even one year since the COVID-19 pandemic hit Indonesia, to anticipate it, the government brought in a COVID-19 vaccine. Various types of COVID-19 vaccine have been introduced to Indonesia, including which ones will be considered the best according to the community through the Twitter platform. One of the venues that creates the most public sentiment is Twitter. It can be determined whether the public fully approves or rejects the existence of vaccination in Indonesia by analyzing public sentiment surrounding the COVID-19 vaccine. Data acquisition using a crawling procedure by connecting the Twitter API, pre-processing, sentiment categorization, and sentiment analysis outcomes are the stages of the sentiment analysis process to become a sentiment analysis application. The PHP and MySQL programming languages are used to create the database for the sentiment analysis application. After the application has been fully implemented, it can do sentiment analysis from each dictionary probability using the Naive Bayes Classifier approach. The study of the two keywords \"vaksin covid\" and \"vaksin corona\" yielded the following results. It has 93% positive sentiment results, 72% negative sentiment results, and 35% neutral sentiment outcomes, with an accuracy of 94.74% and 75.47% per keyword. Meanwhile, the Sinopharm vaccine, which has the most positive attitude with the terms \"vaksin sinovac,\" \"vaksin astrazeneca,\" \"vaksin sinopharm,\" and \"vaksin nusantara,\" has 84 percent tweets with a 74.23% accuracy rate.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"27 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91261899","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664881
Yusuf Setiadi, A. Hidayanto, F. Rachmawati, Adhi Yuniarto Laurentius Yohannes
Data has increasingly become more imperative in organization’s decision-making process. Low data quality can cause extensive organizational problems, such as inaccurate decision-making and dropped business possibilities. This is because low-quality data does not present a clear description of the actual situation. In Human Resource (HR) management, low data quality can cause recruitment, career development, remuneration, and retirement processes. Therefore, proper data quality management must be implemented to produce data that suits the organization's needs. To determine how far the implementation of data quality management in the organization, measurement of the maturity level in data quality management is conducted. This study presented an evaluation of data quality management maturity level in HR of higher education, applying the Loshin data quality management maturity framework. The results of this study indicate that the maturity level in the Data quality expectations area is 2.17, the maturity level in the Data quality dimensions area is 2.16, the maturity level in the Policies area is 1.22, the maturity level in the Data quality protocols area is 2, 11, the maturity level in the Data governance area is 1.77, the maturity level in the Data standards area is 1.67, the maturity level in the Technology area is 1.44, and the maturity level in the Performance management area is 1.67. The result shows that the Policies area is the lowest due to the lack of regulations and good documentation regarding data management. It can be a concern in conducting evaluations for improving data quality management.
{"title":"Data Quality Management Maturity Model : A Case Study in Higher Education’s Human Resource Department","authors":"Yusuf Setiadi, A. Hidayanto, F. Rachmawati, Adhi Yuniarto Laurentius Yohannes","doi":"10.1109/ICCED53389.2021.9664881","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664881","url":null,"abstract":"Data has increasingly become more imperative in organization’s decision-making process. Low data quality can cause extensive organizational problems, such as inaccurate decision-making and dropped business possibilities. This is because low-quality data does not present a clear description of the actual situation. In Human Resource (HR) management, low data quality can cause recruitment, career development, remuneration, and retirement processes. Therefore, proper data quality management must be implemented to produce data that suits the organization's needs. To determine how far the implementation of data quality management in the organization, measurement of the maturity level in data quality management is conducted. This study presented an evaluation of data quality management maturity level in HR of higher education, applying the Loshin data quality management maturity framework. The results of this study indicate that the maturity level in the Data quality expectations area is 2.17, the maturity level in the Data quality dimensions area is 2.16, the maturity level in the Policies area is 1.22, the maturity level in the Data quality protocols area is 2, 11, the maturity level in the Data governance area is 1.77, the maturity level in the Data standards area is 1.67, the maturity level in the Technology area is 1.44, and the maturity level in the Performance management area is 1.67. The result shows that the Policies area is the lowest due to the lack of regulations and good documentation regarding data management. It can be a concern in conducting evaluations for improving data quality management.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"24 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89587214","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664866
R. Angelova, D. Sofronova
The production of woven textiles is a highly complex process that involves several steps. The CAD/CAM systems allow to design and produce high-quality apparel textiles, upholsteries, carpets, blankets, furnishing fabrics, reducing human efforts tremendously. The designers’ imagination is supported by Computer-Aided Design (CAD). On the other hand, the Computer-Aided Manufacturing (CAM) efficiency is so high that the required output could be produced in minutes. Our paper summarises the existing CAD/CAM systems that are mostly in use in the design of woven textiles. An analysis of the new features in woven textiles’ design is made. The advantages of the CAD/CAM systems over traditional manual design are outlined. Three design software packages are applied in the designing of textiles with two different weave patterns: plain weave and complex twill weave.
{"title":"Application of CAD/CAM Systems in the Design of Woven Textiles","authors":"R. Angelova, D. Sofronova","doi":"10.1109/ICCED53389.2021.9664866","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664866","url":null,"abstract":"The production of woven textiles is a highly complex process that involves several steps. The CAD/CAM systems allow to design and produce high-quality apparel textiles, upholsteries, carpets, blankets, furnishing fabrics, reducing human efforts tremendously. The designers’ imagination is supported by Computer-Aided Design (CAD). On the other hand, the Computer-Aided Manufacturing (CAM) efficiency is so high that the required output could be produced in minutes. Our paper summarises the existing CAD/CAM systems that are mostly in use in the design of woven textiles. An analysis of the new features in woven textiles’ design is made. The advantages of the CAD/CAM systems over traditional manual design are outlined. Three design software packages are applied in the designing of textiles with two different weave patterns: plain weave and complex twill weave.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"9 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89304633","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664849
Xiaoxi Kang, D. Handayani, M. H. Kit
Through the development of civilization, there are different addictive behaviour. With the new technologies living in our daily life, Internet addiction has shown growth, especially for children. Among all the Internet addiction behaviours, porn addiction may raise attention to people since it may cause children with learning disabilities, depression, and social skills. Usually, the psychologist will identify the children with porn addiction with the results of the questionnaire and third-party observers. These methods depend on the first-party experience, and they may often overlook. From the review, we know that addictive behaviour is detectable by brain activity. Some research found that functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) are able to display the difference for addictive subjects. Hence, we want to use the EEG signals to identify pornography addiction among children. We use the bandpass as the preprocessing method. Wavelet Packet Decomposition (WPD) as feature extraction, and support vector machine (SVM) as classification methods to process the data to do the prediction model. This research is related to the government campaign under the MCMC, namely "Klik dengan bijak.".
通过文明的发展，出现了不同的成瘾行为。随着新技术在我们的日常生活中出现，网瘾呈增长趋势，尤其是儿童。在所有的网络成瘾行为中，色情成瘾可能引起人们的关注，因为它可能导致儿童有学习障碍、抑郁和社交技能。通常，心理学家会根据问卷调查的结果和第三方观察者来识别色情成瘾儿童。这些方法依赖于第一方的经验，他们可能经常忽略。从这篇综述中，我们知道成瘾行为是可以通过大脑活动检测到的。一些研究发现，功能磁共振成像(fMRI)和脑电图(EEG)能够显示成瘾受试者的差异。因此，我们想用脑电图信号来识别儿童的色情成瘾。我们使用带通作为预处理方法。小波包分解(WPD)作为特征提取，支持向量机(SVM)作为分类方法对数据进行处理，做预测模型。本研究与MCMC下的政府运动有关，即“Klik dengan bijak”。
{"title":"Machine Learning Classification Model for Identifying Pornography Addiction Among Children","authors":"Xiaoxi Kang, D. Handayani, M. H. Kit","doi":"10.1109/ICCED53389.2021.9664849","DOIUrl":"https://doi.org/10.1109/ICCED53389.2021.9664849","url":null,"abstract":"Through the development of civilization, there are different addictive behaviour. With the new technologies living in our daily life, Internet addiction has shown growth, especially for children. Among all the Internet addiction behaviours, porn addiction may raise attention to people since it may cause children with learning disabilities, depression, and social skills. Usually, the psychologist will identify the children with porn addiction with the results of the questionnaire and third-party observers. These methods depend on the first-party experience, and they may often overlook. From the review, we know that addictive behaviour is detectable by brain activity. Some research found that functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) are able to display the difference for addictive subjects. Hence, we want to use the EEG signals to identify pornography addiction among children. We use the bandpass as the preprocessing method. Wavelet Packet Decomposition (WPD) as feature extraction, and support vector machine (SVM) as classification methods to process the data to do the prediction model. This research is related to the government campaign under the MCMC, namely \"Klik dengan bijak.\".","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"623 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91456798","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}
Pub Date : 2021-08-05DOI: 10.1109/ICCED53389.2021.9664863
Utkarsh Alset, Atul Kulkarni, Hrishikesh Mehta
Emergence of Internet of Things (IoT) has enabled convergence in various research areas like wearable electronics, wireless networks, sensors, control systems and embedded systems. Important application areas of healthcare and agriculture are largely benefited with IoT. Remote monitoring of water quality parameters is one such area where IoT can be largely deployed. A Long-range communication (LoRa) is a recent addition to IoT which covers large areas under its wireless network and has ultra-low power consumption. In this paper, a LoRa based monitoring system for measuring water quality parameters of a water reservoir in Symbiosis University’s Lavale Campus is implemented. A wireless floating LoRa transmitter is placed in the reservoir to hourly measure water quality parameters like water temperature, turbidity and pH. A study on effect of various configuration parameters of a LoRa device on time on air (ToA) and battery life is also presented.
物联网(IoT)的出现使可穿戴电子产品，无线网络，传感器，控制系统和嵌入式系统等各个研究领域的融合成为可能。医疗和农业等重要应用领域在很大程度上受益于物联网。水质参数的远程监控是物联网可以大量部署的一个领域。远程通信(LoRa)是物联网的新成员，它在无线网络下覆盖大面积，并且具有超低功耗。本文实现了一种基于LoRa的共生大学Lavale校区水库水质参数监测系统。在水库中放置一个无线浮动LoRa发射机，每小时测量水温、浊度和ph等水质参数，并研究了LoRa设备的各种配置参数对ToA (time on air)和电池寿命的影响。
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