Pub Date : 2021-11-03DOI: 10.1109/icic54025.2021.9632936
{"title":"ICIC 2021 Preface","authors":"","doi":"10.1109/icic54025.2021.9632936","DOIUrl":"https://doi.org/10.1109/icic54025.2021.9632936","url":null,"abstract":"","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116885298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9633005
R. E. Indrajit, Marsetio Marsetio, R. Gultom, P. Widodo, R. W. Putro, Pantja Djati, Siswo Hadi, B. Pramono, L. Simbolon
The European Union Agency for Cybersecurity study shows that there are 15 (fifteen) types of cyber-attacks that will emerge in the next five years. This trend is obtained through an in-depth study of the trend of recent phenomena. The purpose of this study is to try to detect which attacks need attention by the military and state defence sectors in Indonesia. To detect it, a risk analysis method is used in combination with prioritization based on weights. The data was obtained through the involvement of several key experts in the field of cyber defence and security. The results of the study show that eight of the fifteen defined threat trends need special attention by the government and cyber security defence practitioners in Indonesia.
{"title":"Risk Mapping against Cyber Attack Trend in the Perspective of National Defence and Military Sector in Indonesia","authors":"R. E. Indrajit, Marsetio Marsetio, R. Gultom, P. Widodo, R. W. Putro, Pantja Djati, Siswo Hadi, B. Pramono, L. Simbolon","doi":"10.1109/ICIC54025.2021.9633005","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9633005","url":null,"abstract":"The European Union Agency for Cybersecurity study shows that there are 15 (fifteen) types of cyber-attacks that will emerge in the next five years. This trend is obtained through an in-depth study of the trend of recent phenomena. The purpose of this study is to try to detect which attacks need attention by the military and state defence sectors in Indonesia. To detect it, a risk analysis method is used in combination with prioritization based on weights. The data was obtained through the involvement of several key experts in the field of cyber defence and security. The results of the study show that eight of the fifteen defined threat trends need special attention by the government and cyber security defence practitioners in Indonesia.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126849823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9633006
F. A. Setiawan, Puji Rahmadi
Marine algae, both micro and macro algae, are potential marine biological resources as industrial commodities. Indonesia is one of the five largest macroalgae producers in the world and plays a role as a supplier of biomass raw materials in the development of marine algae-based industries. However, Indonesia does not yet have a data center and information this wealth of resources. In fact, in developing appropriate technology and diversifying innovative products based on micro and macro marine algae, it is necessary to have information from the database of the wealth of these algae resources. Therefore, this study aims to build a database of Indonesian native strains of micro and macro algae (Mikro dan Makro Alga Laut Strain Asli Indonesia [MALSAI]) at the national level and present it in the form of an online information system. The methods used in this research are primary and secondary data collection, web-based information system development, collaborative data entry into the system, and continuous data updating. The availability of an algae database on a web-based and open-access information system at the national level through this activity is the first in Indonesia and even at the regional level. The results obtained are: (1) The collection morphology and distribution data of 100 algae species with specimens obtained from 9 events stored in 4 depositors and (2) the publication of the MALSAI database on the IndoAlgae website at https://www.indoalgae.org.
海藻，无论是微藻还是巨藻，都是极具潜力的海洋生物资源。印度尼西亚是世界五大大型藻类生产国之一，在发展海洋藻类产业方面发挥着生物质原料供应国的作用。然而，印尼还没有数据中心和信息这一丰富的资源。事实上，在开发基于微观和宏观海洋藻类的适当技术和多样化创新产品时，有必要从这些藻类资源的丰富数据库中获取信息。因此，本研究的目标是在国家层面建立印尼本土微、大型藻类菌株(Mikro dan Makro Alga Laut Strain Asli Indonesia [MALSAI])数据库，并以在线信息系统的形式呈现。本研究采用的方法是收集一手和二手数据，开发基于web的信息系统，协同数据录入系统，持续更新数据。通过这项活动，在国家一级建立了一个基于网络和开放获取信息系统的藻类数据库，这在印度尼西亚甚至在区域一级都是第一次。获得的结果是:(1)收集了4个存款人、9个事件、100种藻类的形态和分布数据;(2)MALSAI数据库在IndoAlgae网站https://www.indoalgae.org上发布。
{"title":"IndoAlgae: The Database of Indonesian Native Strains of Potential Marine Algae","authors":"F. A. Setiawan, Puji Rahmadi","doi":"10.1109/ICIC54025.2021.9633006","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9633006","url":null,"abstract":"Marine algae, both micro and macro algae, are potential marine biological resources as industrial commodities. Indonesia is one of the five largest macroalgae producers in the world and plays a role as a supplier of biomass raw materials in the development of marine algae-based industries. However, Indonesia does not yet have a data center and information this wealth of resources. In fact, in developing appropriate technology and diversifying innovative products based on micro and macro marine algae, it is necessary to have information from the database of the wealth of these algae resources. Therefore, this study aims to build a database of Indonesian native strains of micro and macro algae (Mikro dan Makro Alga Laut Strain Asli Indonesia [MALSAI]) at the national level and present it in the form of an online information system. The methods used in this research are primary and secondary data collection, web-based information system development, collaborative data entry into the system, and continuous data updating. The availability of an algae database on a web-based and open-access information system at the national level through this activity is the first in Indonesia and even at the regional level. The results obtained are: (1) The collection morphology and distribution data of 100 algae species with specimens obtained from 9 events stored in 4 depositors and (2) the publication of the MALSAI database on the IndoAlgae website at https://www.indoalgae.org.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129939935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632954
Y. Sari, M. Maulida, Endi Gunawan, J. Wahyudi
Amil Zakat National Agency (BAZNAS) is a national institution for the distribution of zakat. As one of the main foundations in Islam, zakat is, obviously, very important to be fulfilled. However, it is very often that the data of the recipient became unclear that it caused problems in terms of a fair distribution of zakat. This research tried to offer a solution by doing a classification of the recipient of zakat on the BAZNAS websites into two categories: indigent and poor, using K-Nearest Neighbor method. This research concluded that the accuracy of KNN method by using classification report, confusion matrix, and ROC-AUC respectively resulted in accuracy of 97%, 96.7%, and 97.7%
{"title":"Artificial Intelligence Approach For BAZNAS Website Using K-Nearest Neighbor (KNN)","authors":"Y. Sari, M. Maulida, Endi Gunawan, J. Wahyudi","doi":"10.1109/ICIC54025.2021.9632954","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632954","url":null,"abstract":"Amil Zakat National Agency (BAZNAS) is a national institution for the distribution of zakat. As one of the main foundations in Islam, zakat is, obviously, very important to be fulfilled. However, it is very often that the data of the recipient became unclear that it caused problems in terms of a fair distribution of zakat. This research tried to offer a solution by doing a classification of the recipient of zakat on the BAZNAS websites into two categories: indigent and poor, using K-Nearest Neighbor method. This research concluded that the accuracy of KNN method by using classification report, confusion matrix, and ROC-AUC respectively resulted in accuracy of 97%, 96.7%, and 97.7%","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124224136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632965
A. Laksito, Ainul Yaqin, Sumarni Adi, Mardhiya Hayaty
The student's study period's in a university was significant in implementing higher education goals and study programs to improve accreditation level. The student's study period's prediction can make higher education institutions' foundation in making future policies. Several factors in implementing students during their studies, including the cumulative achievement index (GPA), affect the study period. Furthermore, the institution often does not consider the conditions or the student's study period's predictive value at its campus. A neural network (NN) is a prediction or classification method that previous researchers have widely used because it is reliable in solving prediction problems. The main problem with improving the accuracy of the NN is the tuning parameter. The neural network model has algorithms for optimization, namely, Particle Swarm Optimization (PSO) and Genetic Algorithm(GA). Based on the experiments and analyses that have been done, the accuracy has been obtained in the GA (GA-ANN) Neural network model with an accuracy score of 71.4%. The score is gained from the parameter specification number of epoch 5, mutation rate = 0.9, layer size 20, tanh activation function, adam solver, and 1000 maximum iteration.
{"title":"Neural Network Optimization for Prediction of Student Study Period","authors":"A. Laksito, Ainul Yaqin, Sumarni Adi, Mardhiya Hayaty","doi":"10.1109/ICIC54025.2021.9632965","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632965","url":null,"abstract":"The student's study period's in a university was significant in implementing higher education goals and study programs to improve accreditation level. The student's study period's prediction can make higher education institutions' foundation in making future policies. Several factors in implementing students during their studies, including the cumulative achievement index (GPA), affect the study period. Furthermore, the institution often does not consider the conditions or the student's study period's predictive value at its campus. A neural network (NN) is a prediction or classification method that previous researchers have widely used because it is reliable in solving prediction problems. The main problem with improving the accuracy of the NN is the tuning parameter. The neural network model has algorithms for optimization, namely, Particle Swarm Optimization (PSO) and Genetic Algorithm(GA). Based on the experiments and analyses that have been done, the accuracy has been obtained in the GA (GA-ANN) Neural network model with an accuracy score of 71.4%. The score is gained from the parameter specification number of epoch 5, mutation rate = 0.9, layer size 20, tanh activation function, adam solver, and 1000 maximum iteration.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130458853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632950
H. Wibowo, Eri Prasetyo Wibowo, Robby Kurniawan Harahap
There is an imbalance between the ratio of the number of vehicles of 11% and the addition of new roads or road extensions of 0,01%, especially in Jakarta, Indonesia, which is often an issue that causes traffic problems, one of them is traffic jam. This paper discusses an implementation of a video surveillance system-based method to monitor traffic conditions such as detection, tracking and counting of vehicles in the form of information technology in the form of system simulation using a computer.The objective of this research is the implementation of a video surveillance based system that can detect, track and count the number of vehicles using an image processing method approach. The approach used in this research is Mixture of Gaussians (MOG2) for background subtraction with optimization of Region of Interests (ROI). There are four stages in this method, namely pre-processing, vehicle tracking, vehicle counting, and ROI optimization. The results were obtained in the form of accuracy which is divided into two conditions, namely in the morning and in the daytime. For accuracy, this system has a capability of 86% in the morning and 94,1% in the daytime with each video duration of 30 seconds. This system simulation can be used as a reference for traffic-related bureaus to help manipulate traffic.
{"title":"Implementation of Background Subtraction for Counting Vehicle Using Mixture of Gaussians with ROI Optimization","authors":"H. Wibowo, Eri Prasetyo Wibowo, Robby Kurniawan Harahap","doi":"10.1109/ICIC54025.2021.9632950","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632950","url":null,"abstract":"There is an imbalance between the ratio of the number of vehicles of 11% and the addition of new roads or road extensions of 0,01%, especially in Jakarta, Indonesia, which is often an issue that causes traffic problems, one of them is traffic jam. This paper discusses an implementation of a video surveillance system-based method to monitor traffic conditions such as detection, tracking and counting of vehicles in the form of information technology in the form of system simulation using a computer.The objective of this research is the implementation of a video surveillance based system that can detect, track and count the number of vehicles using an image processing method approach. The approach used in this research is Mixture of Gaussians (MOG2) for background subtraction with optimization of Region of Interests (ROI). There are four stages in this method, namely pre-processing, vehicle tracking, vehicle counting, and ROI optimization. The results were obtained in the form of accuracy which is divided into two conditions, namely in the morning and in the daytime. For accuracy, this system has a capability of 86% in the morning and 94,1% in the daytime with each video duration of 30 seconds. This system simulation can be used as a reference for traffic-related bureaus to help manipulate traffic.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134119254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632995
Fx. Hendra Prasetya, Bernardinus Harnadi, Albertus Dwiyoga Widiantoro, Agus Cahyo Nugroho
Covid-19 pandemic forcing teaching and learning to be done in a limited way. Because of that situation this study has purpose to investigate the impact of quality factors on continuance intention to use e-learning. The study employs expectation–confirmation model (ECM) to express the effect of Information Quality, System Quality, Service Quality on Confirmation and Satisfaction and adds Perceived Usefulness and Self efficacy to reveal their effect on Satisfaction. The proposed model was tested using 325 respondents. They are young people that live in digital native culture. The analysis of data was carried out in two stages, the first stage is checking for validity and reliability to perform correlation analysis of variables when the result is pass minimal value. The second stage, the causal effects of variables are examined using Structural Equation Modelling (SEM) using Partial Least Square (PLS). The findings of the study reveal quality factors as the determining factors for the confirmation of the satisfying and using e-learning continually. The confirmation also was determined by the perceived usefulness of the system and the self-efficacy in using the system. The findings disclose the quality of e-learning system is prominent factor on continuance intention to use the system.
{"title":"Extending ECM with Quality Factors to Investigate Continuance Intention to Use E-learning","authors":"Fx. Hendra Prasetya, Bernardinus Harnadi, Albertus Dwiyoga Widiantoro, Agus Cahyo Nugroho","doi":"10.1109/ICIC54025.2021.9632995","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632995","url":null,"abstract":"Covid-19 pandemic forcing teaching and learning to be done in a limited way. Because of that situation this study has purpose to investigate the impact of quality factors on continuance intention to use e-learning. The study employs expectation–confirmation model (ECM) to express the effect of Information Quality, System Quality, Service Quality on Confirmation and Satisfaction and adds Perceived Usefulness and Self efficacy to reveal their effect on Satisfaction. The proposed model was tested using 325 respondents. They are young people that live in digital native culture. The analysis of data was carried out in two stages, the first stage is checking for validity and reliability to perform correlation analysis of variables when the result is pass minimal value. The second stage, the causal effects of variables are examined using Structural Equation Modelling (SEM) using Partial Least Square (PLS). The findings of the study reveal quality factors as the determining factors for the confirmation of the satisfying and using e-learning continually. The confirmation also was determined by the perceived usefulness of the system and the self-efficacy in using the system. The findings disclose the quality of e-learning system is prominent factor on continuance intention to use the system.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"15 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132714832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632910
Banteng Widyantoro, Arini, H. Sukmana, Iik Muhamad Malik Matin, D. Khairani
Determining the shortest path with efficient results is important to achieve the minimum distance and time to arrive at the destination. The problem is that the shortest path algorithm can provide a solution. Among the shortest paths, dynamic programming (DP) is one of the algorithms that can provide the best solution for this problem. Several previous studies only used forward or backward models to provide solutions. Combining forward and backward models can be applied to problems that have search motion criteria. In this paper, we propose a combination of the forward-backward DP model and compare it with the forward and backward models to find parking spaces and measure time efficiency. The forward-backward combination model provides the most effective solution with efficient time consumption.
{"title":"The Effectiveness of Forward-Backward Combination Method in Dynamic Programming","authors":"Banteng Widyantoro, Arini, H. Sukmana, Iik Muhamad Malik Matin, D. Khairani","doi":"10.1109/ICIC54025.2021.9632910","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632910","url":null,"abstract":"Determining the shortest path with efficient results is important to achieve the minimum distance and time to arrive at the destination. The problem is that the shortest path algorithm can provide a solution. Among the shortest paths, dynamic programming (DP) is one of the algorithms that can provide the best solution for this problem. Several previous studies only used forward or backward models to provide solutions. Combining forward and backward models can be applied to problems that have search motion criteria. In this paper, we propose a combination of the forward-backward DP model and compare it with the forward and backward models to find parking spaces and measure time efficiency. The forward-backward combination model provides the most effective solution with efficient time consumption.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115664148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632982
Bryanza Novirahman, Y. G. Sucahyo, Arfive Gandhi
Teknologi Quran International is a startup company that runs on the education of Islam religion especially in Al-Qur’an recitation. Since this company was founded in 2015, there has been no significant profit from applications that can sponsor the operational cost of the company. This then led to the unfocused development of the Learn Quran Tajwid application because most of the employees now have other external projects outside the company. Therefore, the evaluation of the business model is provided to suggest the monetization model so that the company can gain more profit on its side. The challenged-based learning (CBL) methodology is conducted through qualitative data collection with contextual interviews in order to assess the learning theory which has been implemented and finding the perfect in-app purchasing as well as an organic marketing technique that wants to be implemented in the future. The application that is examined by 20 most convenient user samples and stakeholder’s recommended domain or subject expert, is available on both platforms, Android, and iOS. The evaluation results show that the monetization model of Learn Quran Tajwid needs to be improved completely since right now there are so many possibilities from the active users who have an opportunity to be taken advantage of by the company. This research can also give benefits to a startup company that wants to have a combination of more sustainable monetization models.
Teknologi Quran International是一家创业公司，主要经营伊斯兰教教育，特别是古兰经背诵。该公司自2015年成立以来，一直没有从能够赞助公司运营成本的应用中获得重大利润。这导致了Learn Quran Tajwid应用程序开发的不集中，因为大多数员工现在都有其他外部项目。因此，提供商业模式的评估，建议货币化模式，使公司能够获得更多的利润。基于挑战的学习(CBL)方法是通过定性数据收集和情境访谈来进行的，目的是评估已经实施的学习理论，并找到完美的应用内购买以及未来想要实施的有机营销技术。该应用程序由20个最方便的用户样本和利益相关者推荐的领域或主题专家进行检查，可在Android和iOS两个平台上使用。评估结果表明，Learn Quran Tajwid的盈利模式需要彻底改进，因为目前活跃用户的可能性很大，有机会被公司利用。这项研究也可以给那些想要结合更可持续的盈利模式的初创公司带来好处。
{"title":"Monetization Model Suggestion of Islamic Education Technology Application","authors":"Bryanza Novirahman, Y. G. Sucahyo, Arfive Gandhi","doi":"10.1109/ICIC54025.2021.9632982","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632982","url":null,"abstract":"Teknologi Quran International is a startup company that runs on the education of Islam religion especially in Al-Qur’an recitation. Since this company was founded in 2015, there has been no significant profit from applications that can sponsor the operational cost of the company. This then led to the unfocused development of the Learn Quran Tajwid application because most of the employees now have other external projects outside the company. Therefore, the evaluation of the business model is provided to suggest the monetization model so that the company can gain more profit on its side. The challenged-based learning (CBL) methodology is conducted through qualitative data collection with contextual interviews in order to assess the learning theory which has been implemented and finding the perfect in-app purchasing as well as an organic marketing technique that wants to be implemented in the future. The application that is examined by 20 most convenient user samples and stakeholder’s recommended domain or subject expert, is available on both platforms, Android, and iOS. The evaluation results show that the monetization model of Learn Quran Tajwid needs to be improved completely since right now there are so many possibilities from the active users who have an opportunity to be taken advantage of by the company. This research can also give benefits to a startup company that wants to have a combination of more sustainable monetization models.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"12 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124274862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-03DOI: 10.1109/ICIC54025.2021.9632906
D. Puspitasari, Al Fath Riza Kholdani, Adani Dharmawati, M. E. Rosadi, Windha Mega Pradnya Dhuhita
A stroke is a medical emergency that occurs when blood flow to the brain is blocked or decreased, depriving brain tissue of oxygen and nutrients. Stroke is the world's second leading cause of death, according to the World Health Organization (WHO). Stroke patients die within the first year of their illness. To reduce the risk of stroke, simple and effective tools are required. The goal of this study was to look into the classification of stroke potential and come up with a simple and reliable model. The Kaggle database provided the stroke prediction data set, which was based on input criteria such as gender, age, various illnesses, and smoking status. To determine the prediction of the construction model, decision trees and random forest classification methods were utilized. The independent variables determining the incidence of stroke were determined to be age (AUC 0.85), hypertension (AUC 0.62), blood sugar level (AUC 0.61), history of heart disease (0.56), married status (0.60), and body mass index (BMI) (AUC 0.56). Age, hypertension, blood sugar level, and BMI were all valid, with a random forest method accuracy of 98.90 percent and decision tree method accuracy of 95.90 percent.
{"title":"Stroke Disease Analysis and Classification Using Decision Tree and Random Forest Methods","authors":"D. Puspitasari, Al Fath Riza Kholdani, Adani Dharmawati, M. E. Rosadi, Windha Mega Pradnya Dhuhita","doi":"10.1109/ICIC54025.2021.9632906","DOIUrl":"https://doi.org/10.1109/ICIC54025.2021.9632906","url":null,"abstract":"A stroke is a medical emergency that occurs when blood flow to the brain is blocked or decreased, depriving brain tissue of oxygen and nutrients. Stroke is the world's second leading cause of death, according to the World Health Organization (WHO). Stroke patients die within the first year of their illness. To reduce the risk of stroke, simple and effective tools are required. The goal of this study was to look into the classification of stroke potential and come up with a simple and reliable model. The Kaggle database provided the stroke prediction data set, which was based on input criteria such as gender, age, various illnesses, and smoking status. To determine the prediction of the construction model, decision trees and random forest classification methods were utilized. The independent variables determining the incidence of stroke were determined to be age (AUC 0.85), hypertension (AUC 0.62), blood sugar level (AUC 0.61), history of heart disease (0.56), married status (0.60), and body mass index (BMI) (AUC 0.56). Age, hypertension, blood sugar level, and BMI were all valid, with a random forest method accuracy of 98.90 percent and decision tree method accuracy of 95.90 percent.","PeriodicalId":189541,"journal":{"name":"2021 Sixth International Conference on Informatics and Computing (ICIC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063540","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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