Terrorism has an impact on people's quality of life by stifling their physical and mental freedom. People are researching harder to investigate new defense systems to defend humanity. To protect people's lives in society and to raise the overall standard of living, counterterrorism strategies have been employed. Recently, artificially intelligent tools for counterterrorism have been developed using machine learning methodologies (AI). In this research, deep learning approaches are researched to comprehend the behavior of terrorist operations because this field of machine learning has recently seen a rise in its popularity. The first experiment, consisting of 10,000 tweets, was collected using five different terrorist terms, and the second experiment, 6,000 tweets from different features, was collected using Rapid Miner and a spreadsheet to collect real-time data. The models are implemented in deep learning model and two machine learning algorithms, i.e. Naïve bayes and kNN using Rapid Miner. The performance of the deep learning model is compared with two machine learning algorithms, and it is shown that the performance of deep learning is 79 to 89 percent in terms of accuracy, precision, recall, and Fl-Score, while traditional machine learning algorithms have only been able to achieve an accuracy of up to 68 percent. This leads to the conclusion that deep learning is an adequate model to utilize for forecasting terrorist activity. As shown by our studies, the dataset for terrorist activities is enormous. A deep learning model is a good choice to handle large datasets and comprehend the underlying patterns in the dataset.
{"title":"Using Deep Learning Model to Predict Terms Use by Terrorist to Pre-Plan an Attack on A Real-Time Twitter Tweets from Rapid Miner","authors":"Viva Arifin, Fatoumatta Binta Jallow, A. Lubis, Rizal Broer Bahaweres, Atep Abdu Rofiq","doi":"10.1109/CITSM56380.2022.9935880","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935880","url":null,"abstract":"Terrorism has an impact on people's quality of life by stifling their physical and mental freedom. People are researching harder to investigate new defense systems to defend humanity. To protect people's lives in society and to raise the overall standard of living, counterterrorism strategies have been employed. Recently, artificially intelligent tools for counterterrorism have been developed using machine learning methodologies (AI). In this research, deep learning approaches are researched to comprehend the behavior of terrorist operations because this field of machine learning has recently seen a rise in its popularity. The first experiment, consisting of 10,000 tweets, was collected using five different terrorist terms, and the second experiment, 6,000 tweets from different features, was collected using Rapid Miner and a spreadsheet to collect real-time data. The models are implemented in deep learning model and two machine learning algorithms, i.e. Naïve bayes and kNN using Rapid Miner. The performance of the deep learning model is compared with two machine learning algorithms, and it is shown that the performance of deep learning is 79 to 89 percent in terms of accuracy, precision, recall, and Fl-Score, while traditional machine learning algorithms have only been able to achieve an accuracy of up to 68 percent. This leads to the conclusion that deep learning is an adequate model to utilize for forecasting terrorist activity. As shown by our studies, the dataset for terrorist activities is enormous. A deep learning model is a good choice to handle large datasets and comprehend the underlying patterns in the dataset.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131000516","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9936012
Ichsan Budiman, D. R. Ramdania, Y. A. Gerhana, Alif Rakasha Pratama Putra, Nisairrizqy Nabilah Faizah, M. Harika
Birds play an essential role in the functioning of the world's ecosystems by directly impacting human health, economy, and food production and benefiting millions of other species. The diversity of bird habitats shows that there are many types of bird species. This study aims to provide a new treasure for the ontology field by applying a machine learning algorithm to classify bird species based on K-Nearest Neighbor (KNN). A total of 400 species of bird images with a total of 58388 images of data were tested in this study. The test scenario was carried out in 3 stages: 400, 200, and 100 species. The results of testing the accuracy of the K-Nearest Neighbor model applied to the bird image dataset are 26.846%, with a value of $mathrm{K}=1$. The comparison of training data with test data is 95:5 percent (%). This result shows that the KNN algorithm can classify bird species.
{"title":"Classification of Bird Species using K-Nearest Neighbor Algorithm","authors":"Ichsan Budiman, D. R. Ramdania, Y. A. Gerhana, Alif Rakasha Pratama Putra, Nisairrizqy Nabilah Faizah, M. Harika","doi":"10.1109/CITSM56380.2022.9936012","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9936012","url":null,"abstract":"Birds play an essential role in the functioning of the world's ecosystems by directly impacting human health, economy, and food production and benefiting millions of other species. The diversity of bird habitats shows that there are many types of bird species. This study aims to provide a new treasure for the ontology field by applying a machine learning algorithm to classify bird species based on K-Nearest Neighbor (KNN). A total of 400 species of bird images with a total of 58388 images of data were tested in this study. The test scenario was carried out in 3 stages: 400, 200, and 100 species. The results of testing the accuracy of the K-Nearest Neighbor model applied to the bird image dataset are 26.846%, with a value of $mathrm{K}=1$. The comparison of training data with test data is 95:5 percent (%). This result shows that the KNN algorithm can classify bird species.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130639251","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935886
U. Maman, Abuddin Nata, Rusdiono Mukri, Nindyantoro, Faisal Hendra, Zirmansyah
By the development of agribusiness e-commerce, the physical contact between seller and buyer is decreasing or even disappearing. The question in this context is whether the tangibility dimension is still needed or - at least -- what are the attributes of tangibility dimension are required in e-commerce of agribusiness. Thus, this research aims to explore the required attributes, the attributes need to remediate, and the attributes which have been completely performed for the tangibility aspect in agribusiness e-commerce. Based on literature review and in-depth interview, this research finds six attributes of tangibility aspect required in agribusiness e-commerce- By the survey to the 100 customers of online marketing in Indonesia - which sample size is determined by Lemeshow formula and taken by accidental sampling - and data analysis adopts the Importance Performance Analysis, this research proves product freshness needs to remediate; while the packaging facilities and product hygiene are the achievement of company services needs to maintain as a good work. The extension education is valuable to maintain the performed attributes and to remediate unperformed tangibility attribute in e-commerce services.
{"title":"The Need of Physical Improvement of Online Marketing: The Case of Agribusiness e-Commerce in Indonesia","authors":"U. Maman, Abuddin Nata, Rusdiono Mukri, Nindyantoro, Faisal Hendra, Zirmansyah","doi":"10.1109/CITSM56380.2022.9935886","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935886","url":null,"abstract":"By the development of agribusiness e-commerce, the physical contact between seller and buyer is decreasing or even disappearing. The question in this context is whether the tangibility dimension is still needed or - at least -- what are the attributes of tangibility dimension are required in e-commerce of agribusiness. Thus, this research aims to explore the required attributes, the attributes need to remediate, and the attributes which have been completely performed for the tangibility aspect in agribusiness e-commerce. Based on literature review and in-depth interview, this research finds six attributes of tangibility aspect required in agribusiness e-commerce- By the survey to the 100 customers of online marketing in Indonesia - which sample size is determined by Lemeshow formula and taken by accidental sampling - and data analysis adopts the Importance Performance Analysis, this research proves product freshness needs to remediate; while the packaging facilities and product hygiene are the achievement of company services needs to maintain as a good work. The extension education is valuable to maintain the performed attributes and to remediate unperformed tangibility attribute in e-commerce services.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116837941","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935830
Sumanto, B. Wijonarko, Muhammad Qommarudin, Aji Sudibyo, Pudji Widodo, Afit Muhammad Lukman
Face detection has been one of the most explored problems in computer vision for several years. Using the WIDER FACES data set, this study investigates how the Viola-Jones method can be used to identify faces in 179 photos and how it performs compared to other face detection algorithms. In a previous study for face detection using Viola-jones, the highest accuracy results were obtained at 90.9% for facial images and 75.5% for non-face images. In this study, the Viola-Jones approach had a 100 percent success rate. This approach will be used in the MATLAB algorithm for face identification to get better results than currently available. Experiments using two classes had promising results.
{"title":"Viola-Jones Algorithm for Face Detection using Wider Face Dataset","authors":"Sumanto, B. Wijonarko, Muhammad Qommarudin, Aji Sudibyo, Pudji Widodo, Afit Muhammad Lukman","doi":"10.1109/CITSM56380.2022.9935830","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935830","url":null,"abstract":"Face detection has been one of the most explored problems in computer vision for several years. Using the WIDER FACES data set, this study investigates how the Viola-Jones method can be used to identify faces in 179 photos and how it performs compared to other face detection algorithms. In a previous study for face detection using Viola-jones, the highest accuracy results were obtained at 90.9% for facial images and 75.5% for non-face images. In this study, the Viola-Jones approach had a 100 percent success rate. This approach will be used in the MATLAB algorithm for face identification to get better results than currently available. Experiments using two classes had promising results.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122677467","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935926
Taufiq Maulana Firdaus, Fahdi Saidi Lubis, M. Lubis
Financial technology (Fintech) is an amalgamation of financial management using a technology system. Fintech has become a public concern because this service provides many service features to make it easier from the financial side, such as being used in cooperative financial institutions, banking and insurance. This paper will analyze the opportunities and challenges of Fintech sharia in Indonesia. By exploring the existing literature, this article will try to answer that question. This research is carried out using a literature review approach and comparative qualitative method which will determined the results of the SWOT analysis of sharia financial technology in indonesia. It is needed to mitigate risk of funding in a peer to peer method in overcoming the security of funds and data from investors, firstly companies can perform transparency on the clarity of investor funds. This is done as one of the facilities provided to investors in the Fintech application. In the future, it is hoped that in facing competition, sharia-based fintech companies must be able to provide targeted services through the socialization of sharia fintech to the public, both online and offline. Investors are expected to be more careful before investing in choosing Fintech Peer to Peer (P2P) Lending services by checking the list of Fintech lending and lending companies registered and found by the Financial Services Authority (OJK).
{"title":"Financial Technology Risk Analysis for Peer to Peer Lending Process: A Case Study of Sharia Aggregator Financial Technology","authors":"Taufiq Maulana Firdaus, Fahdi Saidi Lubis, M. Lubis","doi":"10.1109/CITSM56380.2022.9935926","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935926","url":null,"abstract":"Financial technology (Fintech) is an amalgamation of financial management using a technology system. Fintech has become a public concern because this service provides many service features to make it easier from the financial side, such as being used in cooperative financial institutions, banking and insurance. This paper will analyze the opportunities and challenges of Fintech sharia in Indonesia. By exploring the existing literature, this article will try to answer that question. This research is carried out using a literature review approach and comparative qualitative method which will determined the results of the SWOT analysis of sharia financial technology in indonesia. It is needed to mitigate risk of funding in a peer to peer method in overcoming the security of funds and data from investors, firstly companies can perform transparency on the clarity of investor funds. This is done as one of the facilities provided to investors in the Fintech application. In the future, it is hoped that in facing competition, sharia-based fintech companies must be able to provide targeted services through the socialization of sharia fintech to the public, both online and offline. Investors are expected to be more careful before investing in choosing Fintech Peer to Peer (P2P) Lending services by checking the list of Fintech lending and lending companies registered and found by the Financial Services Authority (OJK).","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129576822","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935856
Muhammad Insan Al-amin, Fahmi Sidiq, D. R. Ramdania, N. Fajar, Y. A. Gerhana, M. Harika
Spices are ingredients that are commonly used as food flavoring in various types of food in the world. There are many types of spices that exist. Not everyone can distinguish the types of these spices. A Spice classifier is needed to address this problem. This study performs the classification of spice images using the Support Vector Machine (SVM) algorithm, which is a method of mapping data into certain categories. There are 5 spices identified, namely ginger, cinnamon, candlenut, turmeric and pepper. In this study, the SVM model for image identification produced an average accuracy of 38.7%. This model has the greatest accuracy in identifying cinnamon by 65.3% and the smallest accuracy in identifying ginger by 24.5%.
{"title":"Spices Image Classification Using Support Vector Machine","authors":"Muhammad Insan Al-amin, Fahmi Sidiq, D. R. Ramdania, N. Fajar, Y. A. Gerhana, M. Harika","doi":"10.1109/CITSM56380.2022.9935856","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935856","url":null,"abstract":"Spices are ingredients that are commonly used as food flavoring in various types of food in the world. There are many types of spices that exist. Not everyone can distinguish the types of these spices. A Spice classifier is needed to address this problem. This study performs the classification of spice images using the Support Vector Machine (SVM) algorithm, which is a method of mapping data into certain categories. There are 5 spices identified, namely ginger, cinnamon, candlenut, turmeric and pepper. In this study, the SVM model for image identification produced an average accuracy of 38.7%. This model has the greatest accuracy in identifying cinnamon by 65.3% and the smallest accuracy in identifying ginger by 24.5%.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125362368","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935963
Nurhayati, Kastari, Feri Fahrianto
Instant Messaging applications have become a common thing used by people, with the increasing popularity of smartphones with the support of various application functions. One of the most popular applications is an instant messaging application with a text message feature. However, the communication media is not always safe from attack sniffers. Symantec Enterprise Security analysis, threats to eavesdropping or wiretapping ranks first in the assault case against instant messaging. For that, how to maintain the security of message data on the communication media of smartphone users from sniffer attacks? One of the solutions uses end-to-end encryption. The encryption algorithms used in E2EE implementations may vary. In this study, the Advanced Encryption Standard (AES) cryptographic algorithm is used in this study. The study results are in the form of designing and building an instant messaging application on the Android mobile platform that can encrypt and decrypt text messages to improve security services on instant messaging applications.
{"title":"End-To-End Encryption on the Instant Messaging Application Based Android using AES Cryptography Algorithm to a Text Message","authors":"Nurhayati, Kastari, Feri Fahrianto","doi":"10.1109/CITSM56380.2022.9935963","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935963","url":null,"abstract":"Instant Messaging applications have become a common thing used by people, with the increasing popularity of smartphones with the support of various application functions. One of the most popular applications is an instant messaging application with a text message feature. However, the communication media is not always safe from attack sniffers. Symantec Enterprise Security analysis, threats to eavesdropping or wiretapping ranks first in the assault case against instant messaging. For that, how to maintain the security of message data on the communication media of smartphone users from sniffer attacks? One of the solutions uses end-to-end encryption. The encryption algorithms used in E2EE implementations may vary. In this study, the Advanced Encryption Standard (AES) cryptographic algorithm is used in this study. The study results are in the form of designing and building an instant messaging application on the Android mobile platform that can encrypt and decrypt text messages to improve security services on instant messaging applications.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"225 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124474361","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935837
Nurbojatmiko, Aris Lathifah, Faaza Bil Amri, A. Rosidah
Indonesia is a country with fairly high market development in Financial Technology (FinTech) Services in the Asia Pacific region. The innovative benefit of FinTech is sharia crowdfunding. Data and information security are important for a company or organization. The problem faced by the use of websites in various fields, especially on the sharia crowdfunding website, is the security of information concerning data from an organization. This study aims to analyze the security vulnerabilities of the sharia crowdfunding website with the Open Web Application Security Project (OWASP) approach using the Zed Attack Proxy (ZAP) tool. OWASP is an open-source framework for improving the security of application software on websites. The results of this study determine the level of vulnerability in the Sharia Crowdfunding Website. This test is carried out to find vulnerabilities and risks on a crowdfunding website and provide recommendations for improving security on the website. The top 10 Security Vulnerabilities based on OWASP consist of 4 high levels, 5 medium levels, 14 low levels, and 9 information levels including Broken Access Control, Injection, Insecure Design, Security Misconfiguration, Vulnerable and Outdated Components, and Software and Data Integrity Failures.
{"title":"Security Vulnerability Analysis of the Sharia Crowdfunding Website Using OWASP-ZAP","authors":"Nurbojatmiko, Aris Lathifah, Faaza Bil Amri, A. Rosidah","doi":"10.1109/CITSM56380.2022.9935837","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935837","url":null,"abstract":"Indonesia is a country with fairly high market development in Financial Technology (FinTech) Services in the Asia Pacific region. The innovative benefit of FinTech is sharia crowdfunding. Data and information security are important for a company or organization. The problem faced by the use of websites in various fields, especially on the sharia crowdfunding website, is the security of information concerning data from an organization. This study aims to analyze the security vulnerabilities of the sharia crowdfunding website with the Open Web Application Security Project (OWASP) approach using the Zed Attack Proxy (ZAP) tool. OWASP is an open-source framework for improving the security of application software on websites. The results of this study determine the level of vulnerability in the Sharia Crowdfunding Website. This test is carried out to find vulnerabilities and risks on a crowdfunding website and provide recommendations for improving security on the website. The top 10 Security Vulnerabilities based on OWASP consist of 4 high levels, 5 medium levels, 14 low levels, and 9 information levels including Broken Access Control, Injection, Insecure Design, Security Misconfiguration, Vulnerable and Outdated Components, and Software and Data Integrity Failures.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"60 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116358259","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9936014
Silvia Damayanti, Yusuf Durachman, Eva Khudzaeva
Pay later is one of the fastest growing payment methods in E-Commerce Applications. Although the use of pay later is increasing, pay later is not the main payment tool that people choose. The purpose of this study is to determine the factors that influence the interest in using Pay later, especially in the Shopee application, and the most dominant factors by comparing two-factor extraction methods, namely Principal Component Analysis and Maximum Likelihood Estimation. Respondents in this study were 125 Shopee application users who had used Shopee Pay later which was carried out by purposive sampling method. The method used in this research is the quantitative method. The results of this study indicate that the principal component analysis method is a feasible method to use because it has a low value on the RMSE and has a strong loading factor value (close to 1) so it can explain the formation of factors. The Principal Component Analysis method produces 3 factors that are formed from 11 variables. The most dominant factor in the influence of interest in using Shopee Pay later with the Principal Component Analysis method is the effect of benefits because the variable of benefit influence has the highest loading factor in decision making.
{"title":"Factors Analysis of Interest in Using Pay Later in E-commerce Applications Using Principal Component Analysis and Maximum Likelihood Estimation Methods","authors":"Silvia Damayanti, Yusuf Durachman, Eva Khudzaeva","doi":"10.1109/CITSM56380.2022.9936014","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9936014","url":null,"abstract":"Pay later is one of the fastest growing payment methods in E-Commerce Applications. Although the use of pay later is increasing, pay later is not the main payment tool that people choose. The purpose of this study is to determine the factors that influence the interest in using Pay later, especially in the Shopee application, and the most dominant factors by comparing two-factor extraction methods, namely Principal Component Analysis and Maximum Likelihood Estimation. Respondents in this study were 125 Shopee application users who had used Shopee Pay later which was carried out by purposive sampling method. The method used in this research is the quantitative method. The results of this study indicate that the principal component analysis method is a feasible method to use because it has a low value on the RMSE and has a strong loading factor value (close to 1) so it can explain the formation of factors. The Principal Component Analysis method produces 3 factors that are formed from 11 variables. The most dominant factor in the influence of interest in using Shopee Pay later with the Principal Component Analysis method is the effect of benefits because the variable of benefit influence has the highest loading factor in decision making.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126264413","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 : 2022-09-20DOI: 10.1109/CITSM56380.2022.9935878
A. Pramono, Tiara Ika Widia Primadani, Ida Bagus Ananta Wijaya, M. Huda, Muchammad Farchan, S. Budiman
The placement of artefacts on display at the museum can be placed on the floor, walls, showcases, or in portable displays. Problems that arise in museums related to artefacts are damage due to lighting factors, Indoor Air Quality (IAQ) factors, and acts of looting that irresponsible people often carry out. This research aims to create a portable museum display by implementing a fingerprint-based security system to protect the artefacts. This research used a single case study in manufacturing furniture as a portable display and implemented NodeMCU ESP8266 as a security system. In this research, the author uses a fingerprint reader as a trigger in the system. This study uses the right thumbnail to open the door of the portable display. On the other hand, when the operator is forced to open the door, the operator uses the left thumbnail. The display door will open, and no alarm will sound, but it will send an SOS SMS to the registered number informing that the door is forced to open. The microprocessor will also buzz the alarm and send an SMS if objects fall or are picked up by irresponsible people by breaking glass.
{"title":"Fingerprint-based Security System in Smart Portable Display at Brawijaya Museum","authors":"A. Pramono, Tiara Ika Widia Primadani, Ida Bagus Ananta Wijaya, M. Huda, Muchammad Farchan, S. Budiman","doi":"10.1109/CITSM56380.2022.9935878","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935878","url":null,"abstract":"The placement of artefacts on display at the museum can be placed on the floor, walls, showcases, or in portable displays. Problems that arise in museums related to artefacts are damage due to lighting factors, Indoor Air Quality (IAQ) factors, and acts of looting that irresponsible people often carry out. This research aims to create a portable museum display by implementing a fingerprint-based security system to protect the artefacts. This research used a single case study in manufacturing furniture as a portable display and implemented NodeMCU ESP8266 as a security system. In this research, the author uses a fingerprint reader as a trigger in the system. This study uses the right thumbnail to open the door of the portable display. On the other hand, when the operator is forced to open the door, the operator uses the left thumbnail. The display door will open, and no alarm will sound, but it will send an SOS SMS to the registered number informing that the door is forced to open. The microprocessor will also buzz the alarm and send an SMS if objects fall or are picked up by irresponsible people by breaking glass.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126396713","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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