Social distancing and isolation are one of the impacts of COVID-19 pandemic, which lead to the increase of internet users across the country especially in suburbs area. Consequently, news regarding COVID-19 reported by the media particularly online media would reach extensive masses. One of the concerns pertaining to this issue is the sentiments and emotions evoked by COVID-19 news, which those sentiments and emotions are crucial in shaping perceptions and attitudes of the public about COVID-19. Therefore, understanding the sentiments and emotions caused by COVID-19 news would help the public more aware in the process of seeking information through online media news. This research used more than 19.000 COVID-19 headlines from known and popular online media starting March 2020 (based on public health authority announcements) to March 2021. NRC Emotion Lexicon used to detect sentiments and emotions from the headlines. The result shown from the analysis stated that 40% of all the headlines evoked negative sentiments. The first seven months were dominated by negative sentiments. Although, at the end of the 2020 positive sentiment started increasing gradually. Sadness, Fear, Trust, and Anticipate were the most dominant emotions evoked by COVID-19 news. The high negative sentiment has no correlation with death-per-million because of COVID-19 in Indonesia.
{"title":"Indonesia COVID-19 Online Media News Sentiment Analysis with Lexicon-based Approach and Emotion Detection","authors":"Bayu Waspodo, Nuryasin, Amalia Khaerunnisa Nursya Bany, Rinda Hesti Kusumaningtyas, Eri Rustamaji","doi":"10.1109/CITSM56380.2022.9935884","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935884","url":null,"abstract":"Social distancing and isolation are one of the impacts of COVID-19 pandemic, which lead to the increase of internet users across the country especially in suburbs area. Consequently, news regarding COVID-19 reported by the media particularly online media would reach extensive masses. One of the concerns pertaining to this issue is the sentiments and emotions evoked by COVID-19 news, which those sentiments and emotions are crucial in shaping perceptions and attitudes of the public about COVID-19. Therefore, understanding the sentiments and emotions caused by COVID-19 news would help the public more aware in the process of seeking information through online media news. This research used more than 19.000 COVID-19 headlines from known and popular online media starting March 2020 (based on public health authority announcements) to March 2021. NRC Emotion Lexicon used to detect sentiments and emotions from the headlines. The result shown from the analysis stated that 40% of all the headlines evoked negative sentiments. The first seven months were dominated by negative sentiments. Although, at the end of the 2020 positive sentiment started increasing gradually. Sadness, Fear, Trust, and Anticipate were the most dominant emotions evoked by COVID-19 news. The high negative sentiment has no correlation with death-per-million because of COVID-19 in Indonesia.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"42 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":"124762303","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/CITSM56380.2022.9935983
S. Agung, Dhifa Mutia Wulan Sari, D. Khairani, Viva Arifin, Teddy Indira Budiwan, Saepul Aripiyanto
State Islamic Higher Education (PTKIN) is a formal Islamic educational institution tasked with administering higher education with a mission of religious moderation that spreads moderate understanding. This study aims to design an ustadz consultation application that facilitates ulama or female ulama (ustadz/ustadzah) currently in the PTKIN organization to preach and answer community problems directly and interactively. Currently, there are no facilities for ustadz/ustadzah in conveying religious knowledge (preaching). This research focuses on designing application designs for ustadz consultations as a form of integration between Islamic science and technology to the high-fidelity prototype stage. The article's purpose is theoretical and methodological justification, practical testing and evaluation of Mobile Religious-Consultation Application processes using design thinking procedure. The Test was conducted using the System Usability Scale (SUS) and Single Ease Question (SEQ) methods and was conducted on 70 respondents. Testing with SUS got a final score of 91% with an Acceptable A rating scale for the Ustadz application and a final score of 80.5% with an Acceptable B rating scale for end-user applications. Meanwhile, in the SEQ test, this study obtained a score of 85.83%, a score of 7 (Very Easy), 10%, a value of 6 (Easy), and 4.17%, a value of 5 (Quite Easy) for the ustadz application and a score of 83.7% a score of 7 (Very Easy), 13.2% score 6 (Easy), 2.1% score 5 (Quite Easy), 0.7% score 4 (Neutral), and 0.3% score 3 (Moderately Difficult) for end-user applications.
{"title":"Development of Mobile Religious-Consultation Application: Design Thinking Approach","authors":"S. Agung, Dhifa Mutia Wulan Sari, D. Khairani, Viva Arifin, Teddy Indira Budiwan, Saepul Aripiyanto","doi":"10.1109/CITSM56380.2022.9935983","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935983","url":null,"abstract":"State Islamic Higher Education (PTKIN) is a formal Islamic educational institution tasked with administering higher education with a mission of religious moderation that spreads moderate understanding. This study aims to design an ustadz consultation application that facilitates ulama or female ulama (ustadz/ustadzah) currently in the PTKIN organization to preach and answer community problems directly and interactively. Currently, there are no facilities for ustadz/ustadzah in conveying religious knowledge (preaching). This research focuses on designing application designs for ustadz consultations as a form of integration between Islamic science and technology to the high-fidelity prototype stage. The article's purpose is theoretical and methodological justification, practical testing and evaluation of Mobile Religious-Consultation Application processes using design thinking procedure. The Test was conducted using the System Usability Scale (SUS) and Single Ease Question (SEQ) methods and was conducted on 70 respondents. Testing with SUS got a final score of 91% with an Acceptable A rating scale for the Ustadz application and a final score of 80.5% with an Acceptable B rating scale for end-user applications. Meanwhile, in the SEQ test, this study obtained a score of 85.83%, a score of 7 (Very Easy), 10%, a value of 6 (Easy), and 4.17%, a value of 5 (Quite Easy) for the ustadz application and a score of 83.7% a score of 7 (Very Easy), 13.2% score 6 (Easy), 2.1% score 5 (Quite Easy), 0.7% score 4 (Neutral), and 0.3% score 3 (Moderately Difficult) for end-user applications.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"38 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":"122736158","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/CITSM56380.2022.9935868
Indriana, D. Alamsyah, N. Othman
This study examines factors that can increase continuance intention in online learning users. There are several factors studied including compatibility, personal innovativeness, and self-efficacy. The research method used is a quantitative survey, where the survey was conducted to 469 students using online learning in Bandung (Indonesia). Data from respondents was processed using SmartPLS with two tests, namely PLS Algorithm and Bootstrapping. The model was tested through inner and outer tests as well as analysis based on research hypothesis testing. The results of the study found that compatibility and self-efficacy had a positive relationship with continuance intention. Students can continue the learning method with online learning if it is supported by the compatibility of hardware and software. It also requires online learning skills from students. However, it is known that the personal innovativeness of students is not sufficient to support the level of student continuance intention. This research is useful for universities in evaluating student learning behavior in online learning.
{"title":"The Continuance Intention of E-Learning: The Role of Compatibility and Self-Efficacy Technology Adoption","authors":"Indriana, D. Alamsyah, N. Othman","doi":"10.1109/CITSM56380.2022.9935868","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935868","url":null,"abstract":"This study examines factors that can increase continuance intention in online learning users. There are several factors studied including compatibility, personal innovativeness, and self-efficacy. The research method used is a quantitative survey, where the survey was conducted to 469 students using online learning in Bandung (Indonesia). Data from respondents was processed using SmartPLS with two tests, namely PLS Algorithm and Bootstrapping. The model was tested through inner and outer tests as well as analysis based on research hypothesis testing. The results of the study found that compatibility and self-efficacy had a positive relationship with continuance intention. Students can continue the learning method with online learning if it is supported by the compatibility of hardware and software. It also requires online learning skills from students. However, it is known that the personal innovativeness of students is not sufficient to support the level of student continuance intention. This research is useful for universities in evaluating student learning behavior in online learning.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"44 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":"122529008","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}
As a highly diverse cyber-physical system, Wireless Sensor Network (WSN) is vulnerable to various failures, which can have catastrophic consequences for safety, economy, and system dependability. Due to the various deployments and limitations of sensor resources, proper detection and diagnosis of failures or faults in WSNs is a complex problem. In this study, a supervised machine learning-based approach is used. To address this issue, the authors employ Random Under Sampling (RUS) sampling method, which is used to overcome class imbalance, and Extra-Tree (ET) classification algorithm to examine sensor behavior through data to find and diagnose problems. The performance of the proposed scheme is compared with advanced machine learning algorithms such as Support Vector Machine (SVM) and Random Forest (RF). The efficiency of the suggested scheme is compared based on the measuring parameters of Accuracy, Recall, Precision, F1-Score, and AUC-ROC Score. This study's results showed that the Random Under Sampling (RUS) sampling method could negatively and positively impact the performance of machine learning models generated to predict WSN data faults. Such as the performance results of one of the classification algorithms used, Support Vector Machine (SVM), the performance of the resulting model on the Accuracy measurement parameter has a value range between 0.29 to 0.83, depending on the model parameters used. In comparison, the Extra- Tree algorithm generates the best model performance on the Accuracy measurement parameter of 96% on all models with the model parameters used.
{"title":"Fault Detection in Wireless Sensor Networks Data Using Random Under Sampling and Extra-Tree Algorithm","authors":"Luh Kesuma Wardhani, Rifqi Adjie Febriyanto, Nenny Anggraini","doi":"10.1109/CITSM56380.2022.9935888","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935888","url":null,"abstract":"As a highly diverse cyber-physical system, Wireless Sensor Network (WSN) is vulnerable to various failures, which can have catastrophic consequences for safety, economy, and system dependability. Due to the various deployments and limitations of sensor resources, proper detection and diagnosis of failures or faults in WSNs is a complex problem. In this study, a supervised machine learning-based approach is used. To address this issue, the authors employ Random Under Sampling (RUS) sampling method, which is used to overcome class imbalance, and Extra-Tree (ET) classification algorithm to examine sensor behavior through data to find and diagnose problems. The performance of the proposed scheme is compared with advanced machine learning algorithms such as Support Vector Machine (SVM) and Random Forest (RF). The efficiency of the suggested scheme is compared based on the measuring parameters of Accuracy, Recall, Precision, F1-Score, and AUC-ROC Score. This study's results showed that the Random Under Sampling (RUS) sampling method could negatively and positively impact the performance of machine learning models generated to predict WSN data faults. Such as the performance results of one of the classification algorithms used, Support Vector Machine (SVM), the performance of the resulting model on the Accuracy measurement parameter has a value range between 0.29 to 0.83, depending on the model parameters used. In comparison, the Extra- Tree algorithm generates the best model performance on the Accuracy measurement parameter of 96% on all models with the model parameters used.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"72 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114037002","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/CITSM56380.2022.9936005
N. Hidayah, Nuryasin, Oviani Viandari
Application Depok Single Window (DSW) is a combination of various application portal of public services in Depok. To improve the quality of mobile - based e-Government services provided by the Depok City Government to the community, periodic evaluations are needed. But in reality, the Depok City Communication and Information Office has not evaluated the e-Government application service on the DSW application based on the perceptions and expectations of its users, so the application is still experiencing several obstacles, such as problems with the DSW application. Experienced a decrease in users every month which caused at least 0.5% of users of the DSW application from the total population of Depok City. Seeing the problems that exist in the service quality of DSW applications, therefore research is needed. This study aims to determine the quality of service in the DSW application based on user perceptions and expectations, and to obtain suggestions for factors that are the main priority for improvement. The model used in this study is the E-Government Service Quality (e-GovQual) model by adding two variables, namely: User Satisfaction (USAT) and Intent to Reuse (USE). This research uses a quantitative approach, and the data analysis process is carried out with IBM Statistics SPSS version 24 for Importance Performance Analysis (IPA), then SmartPLS version 3.2.9 is also used for analysis of the outer and inner models with the PLS-SEM approach. As a result, all indicators used have a negative gap value with the largest value on the Intention to Use variable with an average r value of −0.64. The factors that become the main priority for improvement are the efficiency (EFI) and Citizen Support (CS4) variables, namely: managers are responsive to user problems, managers have adequate knowledge to answer public questions, managers have the ability to deliver services with trust and confidence and information about adequate service.
应用程序站单一窗口(DSW)是应用程序站各种公共服务门户的组合。为提高德埔市政府向市民提供的流动电子政府服务的质素，我们需要定期进行评估。但实际上，德浦市通讯及新闻处并没有根据用户的看法和期望，对电子政府应用服务进行评估，因此，该应用仍遇到一些障碍，例如数码基建应用的问题。每个月的用户数量都在减少，这导致使用污水处理系统的用户至少占德埔市总人口的0.5%。因此，需要对DSW应用的服务质量进行研究。本研究旨在根据用户的感受和期望，确定数码生活服务应用的服务质素，并就需要优先改善的因素提出建议。本研究使用的模型是电子政务服务质量(e-GovQual)模型，该模型增加了两个变量，即用户满意度(USAT)和重用意图(USE)。本研究采用定量方法，数据分析过程采用IBM Statistics SPSS version 24 for Importance Performance analysis (IPA)，然后使用SmartPLS version 3.2.9对外部模型和内部模型进行分析，采用PLS-SEM方法。因此，所使用的所有指标的差距值均为负，其中使用意向变量的差距值最大，平均r值为- 0.64。成为改进的主要优先事项的因素是效率(EFI)和公民支持(CS4)变量，即:管理者对用户问题作出反应，管理者有足够的知识来回答公众问题，管理者有能力以信任和信心提供服务，并提供有关适当服务的信息。
{"title":"E-Government Application Service Quality Analysis Using E-Govqual Method and Importance Performance Analysis (IPA)","authors":"N. Hidayah, Nuryasin, Oviani Viandari","doi":"10.1109/CITSM56380.2022.9936005","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9936005","url":null,"abstract":"Application Depok Single Window (DSW) is a combination of various application portal of public services in Depok. To improve the quality of mobile - based e-Government services provided by the Depok City Government to the community, periodic evaluations are needed. But in reality, the Depok City Communication and Information Office has not evaluated the e-Government application service on the DSW application based on the perceptions and expectations of its users, so the application is still experiencing several obstacles, such as problems with the DSW application. Experienced a decrease in users every month which caused at least 0.5% of users of the DSW application from the total population of Depok City. Seeing the problems that exist in the service quality of DSW applications, therefore research is needed. This study aims to determine the quality of service in the DSW application based on user perceptions and expectations, and to obtain suggestions for factors that are the main priority for improvement. The model used in this study is the E-Government Service Quality (e-GovQual) model by adding two variables, namely: User Satisfaction (USAT) and Intent to Reuse (USE). This research uses a quantitative approach, and the data analysis process is carried out with IBM Statistics SPSS version 24 for Importance Performance Analysis (IPA), then SmartPLS version 3.2.9 is also used for analysis of the outer and inner models with the PLS-SEM approach. As a result, all indicators used have a negative gap value with the largest value on the Intention to Use variable with an average r value of −0.64. The factors that become the main priority for improvement are the efficiency (EFI) and Citizen Support (CS4) variables, namely: managers are responsive to user problems, managers have adequate knowledge to answer public questions, managers have the ability to deliver services with trust and confidence and information about adequate service.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"81 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":"129620584","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/CITSM56380.2022.9935863
S. Masruroh, Devi Zenvita Andriana Utami, D. Khairani, M. Azhari, M. Helmi, Rizka Amalia Putri
In Indonesia, incidents of violence against women have developed into a problem that needs attention. The National Commission for Women has recorded an increase in cases of violence during 2019 which was 6 percent compared to the previous year. The number of increases is a concern for the government in designing a countermeasure and prevention action. In 2014, the National Commission on Women initiated the A bill Law on the Elimination of Sexual Violence to follow up on acts of sexual violence in Indonesia. The ratification of a Bill on the Elimination of Sexual Violence is important to suppress cases of sexual violence. The pros and cons that arise regarding that are found in various media, including social media, namely Twitter as a forum for the community in freedom of expression to make a bill until now it has not been ratified. Comments in the form of tweets become a representation of sentiment that can be seen by the public, both positive and negative. This can affect a policy that is made whether it is feasible to apply or not. So that sentiment from the public can be analyzed properly, this study will examine sentiment analysis on Twitter regarding a Bill on the Elimination of Sexual Violence in Indonesia by applying Natural Language Processing (NLP), using the Support Vector Machine (SVM), and Naïve Bayes Classifier (NBC) algorithms with three different scenarios. The purpose of this study was to determine the algorithm with the best performance in classifying categories. From this research, the highest accuracy result for the test data is in scenario 3 with 97% using SVM and 94.50% using NBC. With these results, the model created can classify positive and negative categories in a document properly.
{"title":"Sentiment Analysis on Twitter towards the Ratification of a Bill on the Elimination of Sexual Violence in Indonesia using Machine Learning","authors":"S. Masruroh, Devi Zenvita Andriana Utami, D. Khairani, M. Azhari, M. Helmi, Rizka Amalia Putri","doi":"10.1109/CITSM56380.2022.9935863","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935863","url":null,"abstract":"In Indonesia, incidents of violence against women have developed into a problem that needs attention. The National Commission for Women has recorded an increase in cases of violence during 2019 which was 6 percent compared to the previous year. The number of increases is a concern for the government in designing a countermeasure and prevention action. In 2014, the National Commission on Women initiated the A bill Law on the Elimination of Sexual Violence to follow up on acts of sexual violence in Indonesia. The ratification of a Bill on the Elimination of Sexual Violence is important to suppress cases of sexual violence. The pros and cons that arise regarding that are found in various media, including social media, namely Twitter as a forum for the community in freedom of expression to make a bill until now it has not been ratified. Comments in the form of tweets become a representation of sentiment that can be seen by the public, both positive and negative. This can affect a policy that is made whether it is feasible to apply or not. So that sentiment from the public can be analyzed properly, this study will examine sentiment analysis on Twitter regarding a Bill on the Elimination of Sexual Violence in Indonesia by applying Natural Language Processing (NLP), using the Support Vector Machine (SVM), and Naïve Bayes Classifier (NBC) algorithms with three different scenarios. The purpose of this study was to determine the algorithm with the best performance in classifying categories. From this research, the highest accuracy result for the test data is in scenario 3 with 97% using SVM and 94.50% using NBC. With these results, the model created can classify positive and negative categories in a document properly.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"32 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":"128701285","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}
Project management is the process of planning, im-plementing, monitoring and closing projects so that the project runs according to the target. One company that requires project management is PT. Triprima Karya which offers construction project consulting services. In the company there are problems, namely there are still delays in several projects which result in de-lays in project payments so that it can harm the company. The purpose of this research is to implement the critical path method and what if analysis to anticipate project delays at PT Triprima Karya. The methods used for delay analysis are Critical Path Method and What If Analysis. The results of the research are based on the critical path method, the critical path on the project is the Preliminary work (A), Preparatory work (B), Construction work (C), Mechanical and plumbing work (E), Electrical work (F), Power connection new electricity (H). And if activity A is delayed for 7 days, based on the results of what if analysis calculations, the activities that can be accelerated are Preparatory work (B) with an additional number of 5 workers and 8 hours, Construction work (C) with an additional 1 worker and 0, 9 hours, Mechanical and plumbing work (E) with an additional number of 1 worker and 1 hour, Electrical work (F) with an additional 1 worker and 1.1 hours New electrical power connection (H) with an additional number of 3 workers and 4 hours.
项目管理是计划、实施、监视和结束项目的过程，使项目按照目标运行。一个需要项目管理的公司是PT. Triprima Karya，它提供建筑项目咨询服务。公司存在一些问题，即有几个项目仍然存在延迟，导致项目付款延迟，从而对公司造成损害。本研究的目的是在Triprima Karya PT实施关键路径方法和如果分析来预测项目延迟。用于延迟分析的方法有关键路径法和假设分析法。研究结果基于关键路径法，项目的关键路径为前期工作(A)，前期准备工作(B)，施工工作(C)，机械和管道工作(E)，电气工作(F)，电源连接新电(H)。如果活动A延迟7天，根据分析计算的结果，可以加速的活动是准备工作(B)，增加5名工人和8小时。建筑工程(C)增聘1名工人及0.9小时;机械及水管工程(E)增聘1名工人及1小时;电力工程(F)增聘1名工人及1.1小时;新接电工程(H)增聘3名工人及4小时。
{"title":"Implementation of Critical Path Method and What If Analysis in Project Management Information System","authors":"Zulfiandri, Farah Dhia Yasmin, Rinda Hesti Kusumaningtyas","doi":"10.1109/CITSM56380.2022.9935912","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935912","url":null,"abstract":"Project management is the process of planning, im-plementing, monitoring and closing projects so that the project runs according to the target. One company that requires project management is PT. Triprima Karya which offers construction project consulting services. In the company there are problems, namely there are still delays in several projects which result in de-lays in project payments so that it can harm the company. The purpose of this research is to implement the critical path method and what if analysis to anticipate project delays at PT Triprima Karya. The methods used for delay analysis are Critical Path Method and What If Analysis. The results of the research are based on the critical path method, the critical path on the project is the Preliminary work (A), Preparatory work (B), Construction work (C), Mechanical and plumbing work (E), Electrical work (F), Power connection new electricity (H). And if activity A is delayed for 7 days, based on the results of what if analysis calculations, the activities that can be accelerated are Preparatory work (B) with an additional number of 5 workers and 8 hours, Construction work (C) with an additional 1 worker and 0, 9 hours, Mechanical and plumbing work (E) with an additional number of 1 worker and 1 hour, Electrical work (F) with an additional 1 worker and 1.1 hours New electrical power connection (H) with an additional number of 3 workers and 4 hours.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"3 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":"130052793","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/CITSM56380.2022.9935934
A. Retnowardhani, A. Setyawan
The rules for studying from home during the COVID-19 pandemic “forced” schools in Indonesia to conduct distance learning. The change from the face-to-face learning system to online learning has surprised schools, especially teachers. The school must quickly make a decision about the application that will be used as a distance learning tool. The decision to use the application is in the hands of the principal, but the success of using the application depends on the acceptance and use of each individual as a user. One of support application for distance learning is Streamyard. This study trying to determine the user behavioral on the use Streamyard application. The success of using the application, among others, is based on its user behavior. Using the modified UTAUT2 model, this study will analyse the factors that influence the user behavioral intention of the Streamyard application by 40 teachers at Canisius Junior High School Jakarta as case study. The research was conducted by distributing questionnaires with the four Linkert scales. Five variables to be tested are performance expectancy, effort expectancy, social influence, facilitating conditions, habit, behavioral intention, and use behavior, with the moderating variable age. The results of data processing using the SmartPLS3.0 application show that users' behavior is not influenced by their behavioral intention to continue using the Streamyard application. Social influence and habit significantly influence behavioral intention, while age positively moderates habit on behavioral intention.
{"title":"User Behavioral Intention to Use Stream Yard Application: The Role of Social Influence and Habit","authors":"A. Retnowardhani, A. Setyawan","doi":"10.1109/CITSM56380.2022.9935934","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935934","url":null,"abstract":"The rules for studying from home during the COVID-19 pandemic “forced” schools in Indonesia to conduct distance learning. The change from the face-to-face learning system to online learning has surprised schools, especially teachers. The school must quickly make a decision about the application that will be used as a distance learning tool. The decision to use the application is in the hands of the principal, but the success of using the application depends on the acceptance and use of each individual as a user. One of support application for distance learning is Streamyard. This study trying to determine the user behavioral on the use Streamyard application. The success of using the application, among others, is based on its user behavior. Using the modified UTAUT2 model, this study will analyse the factors that influence the user behavioral intention of the Streamyard application by 40 teachers at Canisius Junior High School Jakarta as case study. The research was conducted by distributing questionnaires with the four Linkert scales. Five variables to be tested are performance expectancy, effort expectancy, social influence, facilitating conditions, habit, behavioral intention, and use behavior, with the moderating variable age. The results of data processing using the SmartPLS3.0 application show that users' behavior is not influenced by their behavioral intention to continue using the Streamyard application. Social influence and habit significantly influence behavioral intention, while age positively moderates habit on behavioral intention.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"83 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":"134139637","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/CITSM56380.2022.9935840
Nopriadi Saputra, Eka Maya Sari Siswi Ciptaningsih
This paper aims to assess the influence of gamification on work engagement in the holistic framework. A cross-sectional study with involved 401 millennial office workers in Jakarta and Tangerang was conducted. PLS SEM with SmartPLS version 3.3 application was utilized for testing the research model statistically. The analysis result found that gamification has positive influence on holistic work strongly. Performance as one of dimensions of gamification has stronger impact on psychical, intellectual, emotional, and spiritual engagement rather than purpose and motivation of gamification. For engaging millennial worker at office, the organizations should develop performance management system in considering the principles of gamification
{"title":"Assessing The Effect of Gamification on Holistic Work Engagement of Millennial Workers","authors":"Nopriadi Saputra, Eka Maya Sari Siswi Ciptaningsih","doi":"10.1109/CITSM56380.2022.9935840","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935840","url":null,"abstract":"This paper aims to assess the influence of gamification on work engagement in the holistic framework. A cross-sectional study with involved 401 millennial office workers in Jakarta and Tangerang was conducted. PLS SEM with SmartPLS version 3.3 application was utilized for testing the research model statistically. The analysis result found that gamification has positive influence on holistic work strongly. Performance as one of dimensions of gamification has stronger impact on psychical, intellectual, emotional, and spiritual engagement rather than purpose and motivation of gamification. For engaging millennial worker at office, the organizations should develop performance management system in considering the principles of gamification","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"68 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":"133907796","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/CITSM56380.2022.9935930
Rizqi Prima Hariadhy, Alif Shofa Danutirta, M. Lubis
Digital technology has been implemented into various sectors in Indonesia, such as the education, health, tourism sectors, and one of the most important is in the financial sector. Along with the continued development of technology in the financial sector, it will surely have a good affect to economic development. Along with the development of technology in the financial sector, it will surely have a good affect to economic development. Google trends is one of the open-source tools that can represent what keywords are most often searched by the public. In this study, author conducted research related to the relationship between the development of digital technology in the financial sector and economic development using one of the indicators, namely the inflation rate. The analysis that has been conduct use several data science algorithms and inform algorithm that has the best performance, namely Lasso Regression with MAPE value of 0.16 or 16% which means it can be interpreted as Good Forecasting. And the worst algorithm is Linear Regression with a MAPE value of 0.57 or 57%, which means it can be interpreted as Inaccurate Forecasting.
{"title":"Implementation of Data Science Algorithm for Monthly Inflation Prediction Based on Financial Technology Awareness Levels","authors":"Rizqi Prima Hariadhy, Alif Shofa Danutirta, M. Lubis","doi":"10.1109/CITSM56380.2022.9935930","DOIUrl":"https://doi.org/10.1109/CITSM56380.2022.9935930","url":null,"abstract":"Digital technology has been implemented into various sectors in Indonesia, such as the education, health, tourism sectors, and one of the most important is in the financial sector. Along with the continued development of technology in the financial sector, it will surely have a good affect to economic development. Along with the development of technology in the financial sector, it will surely have a good affect to economic development. Google trends is one of the open-source tools that can represent what keywords are most often searched by the public. In this study, author conducted research related to the relationship between the development of digital technology in the financial sector and economic development using one of the indicators, namely the inflation rate. The analysis that has been conduct use several data science algorithms and inform algorithm that has the best performance, namely Lasso Regression with MAPE value of 0.16 or 16% which means it can be interpreted as Good Forecasting. And the worst algorithm is Linear Regression with a MAPE value of 0.57 or 57%, which means it can be interpreted as Inaccurate Forecasting.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"65 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":"131507297","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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