Pub Date : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127796
Feby Dahlan, S. Suyanto
Since Covid-19 has attacked the entire world, news about Covid-19 has been shared to reduce the impact of this outbreak. Social media, particularly Twitter, is a reliable source of information exchange. However, Covid-19 fake news is also being spread by irresponsible people to the public. This fact is so harmful to all parties. Hence, a fake news detector is required to tackle the problem. In this research, a Transformer-based fake news detection system is created. First, an architecture is designed using the Bidirectional Encoder Representations from Transformers (BERT). Three augmentation methods namely spell-checking-based, acronym-based, and typography-based augmentations are then developed to improve the BERT model. A comprehensive examination is performed based on 5-fold cross-validation using eleven thousand Twitter posts with four metrics: Accuracy, Precision, Recall, and F1-Score. Experimental results indicate that those three proposed augmentation methods can increase the BERT's performance detecting fake news related to Covid-19. The acronym-based augmentation gives a low improvement. Next, the spell-checking-based one provides a medium enhancement. Finally, the typography-based one offers the most significant improvement.
{"title":"Data Augmentations to Improve BERT-based Detection of Covid-19 Fake News on Twitter","authors":"Feby Dahlan, S. Suyanto","doi":"10.1109/ICCoSITE57641.2023.10127796","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127796","url":null,"abstract":"Since Covid-19 has attacked the entire world, news about Covid-19 has been shared to reduce the impact of this outbreak. Social media, particularly Twitter, is a reliable source of information exchange. However, Covid-19 fake news is also being spread by irresponsible people to the public. This fact is so harmful to all parties. Hence, a fake news detector is required to tackle the problem. In this research, a Transformer-based fake news detection system is created. First, an architecture is designed using the Bidirectional Encoder Representations from Transformers (BERT). Three augmentation methods namely spell-checking-based, acronym-based, and typography-based augmentations are then developed to improve the BERT model. A comprehensive examination is performed based on 5-fold cross-validation using eleven thousand Twitter posts with four metrics: Accuracy, Precision, Recall, and F1-Score. Experimental results indicate that those three proposed augmentation methods can increase the BERT's performance detecting fake news related to Covid-19. The acronym-based augmentation gives a low improvement. Next, the spell-checking-based one provides a medium enhancement. Finally, the typography-based one offers the most significant improvement.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"28 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":"117147337","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127669
Muhammad Izaaz Rozan, Moch. Rusli, M. A. Muslim
This paper presents a Sliding Mode Controller (SMC) applied in Two Level DC/DC Boost Converter (TLBC) for Fuel Cell (FC) application. The purpose of this paper is to control the output voltage generated by TLBC with the input voltage supplied from FC. In its implementation, the SMC method is used because it is adaptive and nonlinear so it can produce a constant voltage output even though there is a varying voltage from FC. In general, the variation of output voltage from FC caused by V-I characteristics is that the output voltage value will decrease if the output current value increases. Besides that, SMC can also overcome the nonlinear nature of TLBC where the TLBC system works based on switching, so it has different equations with different conditions (on and off). The FC output voltage specification used as the TLBC input voltage is 250V, while the TLBC output voltage is 600V. Research conducted in this paper uses a simulation system with MATLAB/Simulink software in designing the entire system and displays research results in graphic form.
{"title":"Control of Direct Current (DC) Output Voltage for Two Level DC/DC Boost Converter by Sliding Mode Controller in Application of Fuel Cell","authors":"Muhammad Izaaz Rozan, Moch. Rusli, M. A. Muslim","doi":"10.1109/ICCoSITE57641.2023.10127669","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127669","url":null,"abstract":"This paper presents a Sliding Mode Controller (SMC) applied in Two Level DC/DC Boost Converter (TLBC) for Fuel Cell (FC) application. The purpose of this paper is to control the output voltage generated by TLBC with the input voltage supplied from FC. In its implementation, the SMC method is used because it is adaptive and nonlinear so it can produce a constant voltage output even though there is a varying voltage from FC. In general, the variation of output voltage from FC caused by V-I characteristics is that the output voltage value will decrease if the output current value increases. Besides that, SMC can also overcome the nonlinear nature of TLBC where the TLBC system works based on switching, so it has different equations with different conditions (on and off). The FC output voltage specification used as the TLBC input voltage is 250V, while the TLBC output voltage is 600V. Research conducted in this paper uses a simulation system with MATLAB/Simulink software in designing the entire system and displays research results in graphic form.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"48 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":"123429478","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127686
Yuri Pamungkas, Ulfi Widya Astuti
The use of EEG to recognize human emotions has become a notable trend and breakthrough today. EEG-based emotion recognition is a form of research that uses biomedical signals to distinguish a person's psychological condition (without directly paying attention to changes in facial gestures and attitudes). However, there are many studies related to emotion recognition whose classification accuracy is still low and needs to be improved. Therefore, we propose an EEG-based recognition of positive and negative emotions in this study using the Gate Recurrent Unit (GRU) algorithm. EEG data were taken from 38 participants with four recording channels (FP1, FP2, F7, and F8). In EEG recording, a video was played to stimulate the participants' emotions (positive and negative). Then, the EEG data is processed by filtering, artefact removal, frequency band decomposition, feature extraction, and emotion classification based on signal features. Several classification scenarios (such as by varying the activation function of the classifier and the number of EEG channels) are carried out to obtain an optimal level of accuracy. Based on the emotion classification results (using the Softmax activation function) on multi-channel EEG, the accuracy values reached 98.85% (for training) and 91.45% (for testing).
{"title":"Comparison of Human Emotion Classification on Single-Channel and Multi-Channel EEG using Gate Recurrent Unit Algorithm","authors":"Yuri Pamungkas, Ulfi Widya Astuti","doi":"10.1109/ICCoSITE57641.2023.10127686","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127686","url":null,"abstract":"The use of EEG to recognize human emotions has become a notable trend and breakthrough today. EEG-based emotion recognition is a form of research that uses biomedical signals to distinguish a person's psychological condition (without directly paying attention to changes in facial gestures and attitudes). However, there are many studies related to emotion recognition whose classification accuracy is still low and needs to be improved. Therefore, we propose an EEG-based recognition of positive and negative emotions in this study using the Gate Recurrent Unit (GRU) algorithm. EEG data were taken from 38 participants with four recording channels (FP1, FP2, F7, and F8). In EEG recording, a video was played to stimulate the participants' emotions (positive and negative). Then, the EEG data is processed by filtering, artefact removal, frequency band decomposition, feature extraction, and emotion classification based on signal features. Several classification scenarios (such as by varying the activation function of the classifier and the number of EEG channels) are carried out to obtain an optimal level of accuracy. Based on the emotion classification results (using the Softmax activation function) on multi-channel EEG, the accuracy values reached 98.85% (for training) and 91.45% (for testing).","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"22 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":"125345683","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127709
N. Nurhaeni, Azhari Sn, Agus Byna
Prediction is a systematic process of determining what will happen in the future based on current historical data, which reduces inaccuracies. The purpose of this study is to predict the number of crimes in the future so that it can be used as a basis for decision support to determine time priorities for the police to carry out patrol duties. Researchers use Analytical Hierarchy Process (AHP) as one of the methods used to make decision support and Triple Exponential Smoothing as a method used to predict the number of crimes. The study's results used the Triple Exponential Smoothing method with a vulnerable time when the crime occurred at dawn, afternoon, evening, and night with an average accuracy of 63.60%. In the AHP method, the pairwise comparison assessment for each hierarchy consistently gives a CR value of less than 0.1. Thus, the priority of patrol time generated by the two methods is acceptable.
{"title":"Predicting Priority Time Patrol using Triple Exponential Smoothing and AHP","authors":"N. Nurhaeni, Azhari Sn, Agus Byna","doi":"10.1109/ICCoSITE57641.2023.10127709","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127709","url":null,"abstract":"Prediction is a systematic process of determining what will happen in the future based on current historical data, which reduces inaccuracies. The purpose of this study is to predict the number of crimes in the future so that it can be used as a basis for decision support to determine time priorities for the police to carry out patrol duties. Researchers use Analytical Hierarchy Process (AHP) as one of the methods used to make decision support and Triple Exponential Smoothing as a method used to predict the number of crimes. The study's results used the Triple Exponential Smoothing method with a vulnerable time when the crime occurred at dawn, afternoon, evening, and night with an average accuracy of 63.60%. In the AHP method, the pairwise comparison assessment for each hierarchy consistently gives a CR value of less than 0.1. Thus, the priority of patrol time generated by the two methods is acceptable.","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":"126779995","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127810
Muhammad Ichwandar Akrianto, Adhistya Erna Permanasari, Indriana Hidayah, M. Sholihin
Waqf has an important role in the development and increase in welfare. In addition to reducing dependence on funds from the Indonesian government, waqf has also had a significant impact on reviving the economy, especially since the outbreak of the COVID-19 virus. The rapid advancement of technology has also transformed waqf, one of which is that people can donate waqf money online through several digital applications. But so far, several advantages and disadvantages are felt by application users. To make it easier to get information based on user experience, we propose to develop a model that can classify sentiments into positive, negative, and neutral automatically. Text classification using word embedding is the basis for getting the best performance results. Bag of Word (BOW) is a word embedding model that is often used, but this model is considered not optimal because it has disadvantages such as dependence on certain languages. Therefore, we suggest the fastText model minimizes dependency on pre-processing words and use 2 classification methods, namely SVM and KNN. This study aims to compare the performance results using the fastText model with conventional models that are often used, namely Bag of Word (BOW) and Term Frequency – Inverse Document Frequency (TF-IDF) to find the best accuracy value produced. Based on this research, it can be interpreted that in general, the fastText model can produce better performance than BOW and TF-IDF.
Waqf在发展和增加福利方面发挥着重要作用。除了减少对印尼政府资金的依赖外，waqf还对振兴经济产生了重大影响，特别是在新冠病毒爆发以来。科技的快速发展也改变了waqf，其中之一就是人们可以通过几个数字应用程序在线捐赠waqf的钱。但是到目前为止，应用程序用户仍然感受到一些优点和缺点。为了更容易地获得基于用户体验的信息，我们建议开发一个可以自动将情绪分为积极、消极和中立的模型。使用词嵌入进行文本分类是获得最佳性能结果的基础。BOW (Bag of Word)是一种常用的词嵌入模型，但由于其对某些语言的依赖等缺点，被认为不是最优模型。因此，我们建议fastText模型最大限度地减少对预处理词的依赖，并使用2种分类方法，即SVM和KNN。本研究旨在将fastText模型的性能结果与常用的传统模型(即Word Bag (BOW)和Term Frequency - Inverse Document Frequency (TF-IDF))进行比较，以找到产生的最佳精度值。基于本研究，可以解释为总体而言，fastText模型比BOW和TF-IDF能产生更好的性能。
{"title":"Analysis of Google Play Store's Sentiment Review on Waqf Digital Platform Using Fasttext Embedding","authors":"Muhammad Ichwandar Akrianto, Adhistya Erna Permanasari, Indriana Hidayah, M. Sholihin","doi":"10.1109/ICCoSITE57641.2023.10127810","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127810","url":null,"abstract":"Waqf has an important role in the development and increase in welfare. In addition to reducing dependence on funds from the Indonesian government, waqf has also had a significant impact on reviving the economy, especially since the outbreak of the COVID-19 virus. The rapid advancement of technology has also transformed waqf, one of which is that people can donate waqf money online through several digital applications. But so far, several advantages and disadvantages are felt by application users. To make it easier to get information based on user experience, we propose to develop a model that can classify sentiments into positive, negative, and neutral automatically. Text classification using word embedding is the basis for getting the best performance results. Bag of Word (BOW) is a word embedding model that is often used, but this model is considered not optimal because it has disadvantages such as dependence on certain languages. Therefore, we suggest the fastText model minimizes dependency on pre-processing words and use 2 classification methods, namely SVM and KNN. This study aims to compare the performance results using the fastText model with conventional models that are often used, namely Bag of Word (BOW) and Term Frequency – Inverse Document Frequency (TF-IDF) to find the best accuracy value produced. Based on this research, it can be interpreted that in general, the fastText model can produce better performance than BOW and TF-IDF.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"215 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":"114901158","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127793
Y. Sari, Fajar Aina Rizky, I. Ranggadara, Nia Rahma Kurnianda, Ifan Prihandi, Suhendra
The growth process after forest fires takes a long time because much land is often burned again, and some soils are less fertile. This research was conducted in Katingan, Central Kalimantan, as an area of interest. In this case, many human resources do not realize that they are trying to re-utilize the land that was burned by fires in that location. Land that has been burned should be rechecked a few months after the fire to see vegetation density. Using Landsat 8 OLI imagery to detect changes after the fire occurred, this research needs to compare feature extraction to test the level of dryness and humidity in the burnt restoration area. The feature extraction used is Normalized Difference Drought Index for drought detection and the Normalized Difference Moisture Index for detecting post-fire humidity. Furthermore, it will be tested using the Linear Discriminant Analysis algorithm to assess the classification of results from 1 June 2020 - 31 December 2020 in the area of interest carried out. The results of this research obtained for feature extraction NDDI has a lightness level with a range of 0.01 - 0.15 to 0.15 - 0.25, which indicates moderate to a severe drought that occurred in Katingan, Central Kalimantan, with a precision value of 98.33%, Recall 98.33% and Accuracy 98%. While NDMI has humidity in the range of 0.2 to - 0.4 to 0.4 to 0.6, which shows no growth to low growth with a precision value of 68.57%, Recall 68.57% and Accuracy 68% obtained.
{"title":"Comparison of Feature Extraction to Test Dryness and Moisture Levels in Burned Restoration Areas Using Linear Discriminant Analysis","authors":"Y. Sari, Fajar Aina Rizky, I. Ranggadara, Nia Rahma Kurnianda, Ifan Prihandi, Suhendra","doi":"10.1109/ICCoSITE57641.2023.10127793","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127793","url":null,"abstract":"The growth process after forest fires takes a long time because much land is often burned again, and some soils are less fertile. This research was conducted in Katingan, Central Kalimantan, as an area of interest. In this case, many human resources do not realize that they are trying to re-utilize the land that was burned by fires in that location. Land that has been burned should be rechecked a few months after the fire to see vegetation density. Using Landsat 8 OLI imagery to detect changes after the fire occurred, this research needs to compare feature extraction to test the level of dryness and humidity in the burnt restoration area. The feature extraction used is Normalized Difference Drought Index for drought detection and the Normalized Difference Moisture Index for detecting post-fire humidity. Furthermore, it will be tested using the Linear Discriminant Analysis algorithm to assess the classification of results from 1 June 2020 - 31 December 2020 in the area of interest carried out. The results of this research obtained for feature extraction NDDI has a lightness level with a range of 0.01 - 0.15 to 0.15 - 0.25, which indicates moderate to a severe drought that occurred in Katingan, Central Kalimantan, with a precision value of 98.33%, Recall 98.33% and Accuracy 98%. While NDMI has humidity in the range of 0.2 to - 0.4 to 0.4 to 0.6, which shows no growth to low growth with a precision value of 68.57%, Recall 68.57% and Accuracy 68% obtained.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"16 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":"116234938","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127737
M. Dachyar, Yudi Fernando Silalelo
The need for easier and more affordable access to oxygen is still an obstacle in some parts of Indonesia, especially in the eastern part of Indonesia. A medical oxygen generator device can answer the problems related to the difficulty of accessing oxygen. There are frequent delays in the completion of the medical oxygen generator project, causing cost overruns and delays in providing first aid. The purpose of this study is to measure the performance of companies project management and provide suggestions for improvement strategies so that companies can improve their project performance. In this study, data collection was carried out by recapitulating some of the estimated project cost data, followed by compiling standard budgets for each project. Based on these two data, the company's project management performance is evaluated using Earned Value method with the CR as the indicator. The goal is to find the best strategies to improve the company’s project management performance based on our results. The proposed measurements provide the stages that have poor performance and then provide solutions for the company for each stage that have poor performance.
{"title":"Project Management Performance Evaluation of Medical Oxygen Generator","authors":"M. Dachyar, Yudi Fernando Silalelo","doi":"10.1109/ICCoSITE57641.2023.10127737","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127737","url":null,"abstract":"The need for easier and more affordable access to oxygen is still an obstacle in some parts of Indonesia, especially in the eastern part of Indonesia. A medical oxygen generator device can answer the problems related to the difficulty of accessing oxygen. There are frequent delays in the completion of the medical oxygen generator project, causing cost overruns and delays in providing first aid. The purpose of this study is to measure the performance of companies project management and provide suggestions for improvement strategies so that companies can improve their project performance. In this study, data collection was carried out by recapitulating some of the estimated project cost data, followed by compiling standard budgets for each project. Based on these two data, the company's project management performance is evaluated using Earned Value method with the CR as the indicator. The goal is to find the best strategies to improve the company’s project management performance based on our results. The proposed measurements provide the stages that have poor performance and then provide solutions for the company for each stage that have poor performance.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"102 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":"117294898","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127844
Refa Septiansyah Mulyana, Asep Id Hadiana, Edvin Ramadhan
Looking for an idea to differentiate a product from other sellers is not easy. Sometimes sellers of MSME products need sales recommendations on what is trending among the public. A product recommendation can help users recommend a product that is interesting and needed by that user. Recommendation systems can help users come up with previously unknown or unthinkable information, which can directly aid user knowledge in their search results. In this research, a recommendation system will be built to search for product ideas. This study uses content-based filtering and collaborative filtering methods as well as the TF-IDF algorithm to assist users in recommending the products they are looking for to assist users in finding product-selling ideas they expect. Previous research has examined the recommendation system for Modern Musical Instrument Sales using the Simple Additive Weighing method but has the drawback that the weighting calculation must use fuzzy numbers. Therefore, the content-based and collaborative filtering methods are assisted by the TF-IDF algorithm used in this study to answer these problems. After implementation, we test accuracy by dividing the test data and training data differently. System testing is done by using a confusion matrix. The results that have been tested get an accuracy of 78%. Subsequent research suggests adding MSME product data in recommending product sales ideas to MSMEs so that recommendations are more optimal.
{"title":"Recommendation System Of Product Sales Ideas For MSMEs Using Content-based Filtering and Collaborative Filtering Methods","authors":"Refa Septiansyah Mulyana, Asep Id Hadiana, Edvin Ramadhan","doi":"10.1109/ICCoSITE57641.2023.10127844","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127844","url":null,"abstract":"Looking for an idea to differentiate a product from other sellers is not easy. Sometimes sellers of MSME products need sales recommendations on what is trending among the public. A product recommendation can help users recommend a product that is interesting and needed by that user. Recommendation systems can help users come up with previously unknown or unthinkable information, which can directly aid user knowledge in their search results. In this research, a recommendation system will be built to search for product ideas. This study uses content-based filtering and collaborative filtering methods as well as the TF-IDF algorithm to assist users in recommending the products they are looking for to assist users in finding product-selling ideas they expect. Previous research has examined the recommendation system for Modern Musical Instrument Sales using the Simple Additive Weighing method but has the drawback that the weighting calculation must use fuzzy numbers. Therefore, the content-based and collaborative filtering methods are assisted by the TF-IDF algorithm used in this study to answer these problems. After implementation, we test accuracy by dividing the test data and training data differently. System testing is done by using a confusion matrix. The results that have been tested get an accuracy of 78%. Subsequent research suggests adding MSME product data in recommending product sales ideas to MSMEs so that recommendations are more optimal.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"4 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":"128473521","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 : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127755
Marliani, A. Arief, I. Gunadin
The use of renewable energy has been widely applied worldwide to reduce fossil energy use. A hybrid electric power system based on renewable energy is one of the solutions to produce maximum energy. In this paper, the hybrid systems discussed include photovoltaic (PV), wind turbine (WT), and battery storage (BS). This hybrid design system is very dependent on the load profile, potential energy sources, and geographical location of the research location. This research shows the technical design and capital cost of a hybrid electric power system that will be implemented as an alternative energy source for practical work on the Soroako Technical Academy or Akademi Teknik Soroako (ATS) vocational campus. Irradiance, temperature, average wind speed, and component sizing are the main parameters for the design. The technical analysis and capital cost design use MATLAB software with the wild horse optimization (WHO) algorithm. The results of the WHO analysis will be compared with the HOMER application. The results showed that the WHO algorithm method is better than the HOMER application, with a capital cost of $ 198,363.05 with a total of 772 PV units, 1 unit of WT, and 54 battery units.
可再生能源的使用已在世界范围内广泛应用，以减少化石能源的使用。以可再生能源为基础的混合电力系统是产生最大能量的解决方案之一。本文讨论的混合系统包括光伏(PV)、风力发电(WT)和电池储能(BS)。这种混合设计系统非常依赖于负载分布、潜在能源和研究地点的地理位置。这项研究显示了混合电力系统的技术设计和资金成本，该系统将作为Soroako技术学院或Akademi Teknik Soroako (ATS)职业校园实际工作的替代能源。辐照度、温度、平均风速和组件尺寸是设计的主要参数。技术分析和资金成本设计采用MATLAB软件，采用野马优化(WHO)算法。世卫组织的分析结果将与HOMER的应用进行比较。结果表明，WHO算法方法优于HOMER应用，资金成本为198,363.05美元，共计772台光伏机组，1台WT, 54台电池。
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Pub Date : 2023-02-16DOI: 10.1109/ICCoSITE57641.2023.10127698
N. Kurniawan, Jacques, Muammar Azhim Tohepaly, A. Gui, M. S. Shaharudin, Y. Ganesan
Online loan is viewed as an alternative to banking but easier and provide direct connection between public and loan offerer. However, online security threats and scam are undermining the quality of online loan. This study aims to determine how the public views their privacy while using online loan applications, perceived risk, perceived security, and qualities on intention to apply online loan. In order to examine the intention, a quantitative survey method was adopted and survey questionnaire was sent to the public who had experienced and apply for online loan applications. 153 responses were received and analysed using IBM SPSS version 28 for demographic analysis and SmartPLS 4 for model and structural measurements. Results show that perceived security, service quality and system quality were not critical to the respondents when choosing online loan applications while perceived risk, information sharing, and privacy concern were critical. This study shows that general public believed that security and quality are part of the package when organization offered a product or service. Interestingly, while privacy, risk, and information are important, public felt that it is the duty of organization to take care of their interests. Future research should look into behavioural aspects of public risk, information sharing, and privacy concern to understand in-depth.
网络贷款被视为银行业务的另一种选择，但更容易，并提供了公众和贷款提供者之间的直接联系。然而，网络安全威胁和诈骗正在削弱网络贷款的质量。本研究旨在确定公众在使用网络贷款申请时如何看待自己的隐私、感知风险、感知安全性以及申请网络贷款意愿的品质。为了检验意向，我们采用了定量调查的方法，向有过网贷申请经历的公众发放了调查问卷。收到153份回复，并使用IBM SPSS version 28进行人口统计分析，使用SmartPLS 4进行模型和结构测量。结果表明，在选择网络贷款申请时，感知到的安全性、服务质量和系统质量对受访者来说并不重要，而感知到的风险、信息共享和隐私问题才是关键。这项研究表明，一般公众认为，安全和质量的一部分，当组织提供的产品或服务。有趣的是，虽然隐私、风险和信息很重要，但公众认为组织有责任照顾他们的利益。未来的研究应着眼于公共风险、信息共享和隐私问题的行为方面，以深入了解。
{"title":"Information Security and the Quality of Online Loan Applications: A Societal Analysis","authors":"N. Kurniawan, Jacques, Muammar Azhim Tohepaly, A. Gui, M. S. Shaharudin, Y. Ganesan","doi":"10.1109/ICCoSITE57641.2023.10127698","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127698","url":null,"abstract":"Online loan is viewed as an alternative to banking but easier and provide direct connection between public and loan offerer. However, online security threats and scam are undermining the quality of online loan. This study aims to determine how the public views their privacy while using online loan applications, perceived risk, perceived security, and qualities on intention to apply online loan. In order to examine the intention, a quantitative survey method was adopted and survey questionnaire was sent to the public who had experienced and apply for online loan applications. 153 responses were received and analysed using IBM SPSS version 28 for demographic analysis and SmartPLS 4 for model and structural measurements. Results show that perceived security, service quality and system quality were not critical to the respondents when choosing online loan applications while perceived risk, information sharing, and privacy concern were critical. This study shows that general public believed that security and quality are part of the package when organization offered a product or service. Interestingly, while privacy, risk, and information are important, public felt that it is the duty of organization to take care of their interests. Future research should look into behavioural aspects of public risk, information sharing, and privacy concern to understand in-depth.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"1 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":"129732505","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}
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