2021 Sixth International Conference on Informatics and Computing (ICIC)最新文献

ICIC 2021 Preface

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/icic54025.2021.9632936

引用次数: 0

Risk Mapping against Cyber Attack Trend in the Perspective of National Defence and Military Sector in Indonesia 印尼国防和军事部门视角下的网络攻击趋势风险映射

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 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

引用次数: 0

IndoAlgae: The Database of Indonesian Native Strains of Potential Marine Algae IndoAlgae:印度尼西亚本土潜在海藻菌株数据库

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9633006

F. A. Setiawan, Puji Rahmadi

{"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}

引用次数: 0

Artificial Intelligence Approach For BAZNAS Website Using K-Nearest Neighbor (KNN) 基于k近邻(KNN)的BAZNAS网站人工智能方法

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632954

Y. Sari, M. Maulida, Endi Gunawan, J. Wahyudi

引用次数: 5

Neural Network Optimization for Prediction of Student Study Period 神经网络优化预测学生学习时间

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632965

A. Laksito, Ainul Yaqin, Sumarni Adi, Mardhiya Hayaty

{"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}

引用次数: 0

Implementation of Background Subtraction for Counting Vehicle Using Mixture of Gaussians with ROI Optimization 利用混合高斯和ROI优化实现车辆计数的背景减法

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632950

H. Wibowo, Eri Prasetyo Wibowo, Robby Kurniawan Harahap

{"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}

引用次数: 0

Extending ECM with Quality Factors to Investigate Continuance Intention to Use E-learning 基于质量因素的ECM扩展研究学生持续使用电子学习的意向

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632995

Fx. Hendra Prasetya, Bernardinus Harnadi, Albertus Dwiyoga Widiantoro, Agus Cahyo Nugroho

{"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}

引用次数: 7

The Effectiveness of Forward-Backward Combination Method in Dynamic Programming 正反向组合方法在动态规划中的有效性

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632910

Banteng Widyantoro, Arini, H. Sukmana, Iik Muhamad Malik Matin, D. Khairani

引用次数: 3

Monetization Model Suggestion of Islamic Education Technology Application 伊斯兰教育技术应用货币化模式建议

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632982

Bryanza Novirahman, Y. G. Sucahyo, Arfive Gandhi

{"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}

引用次数: 0

Stroke Disease Analysis and Classification Using Decision Tree and Random Forest Methods 基于决策树和随机森林方法的中风疾病分析与分类

2021 Sixth International Conference on Informatics and Computing (ICIC) Pub Date : 2021-11-03 DOI: 10.1109/ICIC54025.2021.9632906

D. Puspitasari, Al Fath Riza Kholdani, Adani Dharmawati, M. E. Rosadi, Windha Mega Pradnya Dhuhita

{"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}

引用次数: 3