2020 Fifth International Conference on Informatics and Computing (ICIC)最新文献_第2页

Managing Service Level for Academic Information System Help Desk for XYZ University Based on ITIL V3 Framework 基于ITIL V3框架的XYZ大学学术信息系统帮助台服务水平管理

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288592

Y. T. Wiranti, H. J. Saputra, D. B. Tandirau, T. P. Fiqar, M. G. Langgawan P, E. Ramadhani, A. I. N. F. Abdullah

{"title":"Managing Service Level for Academic Information System Help Desk for XYZ University Based on ITIL V3 Framework","authors":"Y. T. Wiranti, H. J. Saputra, D. B. Tandirau, T. P. Fiqar, M. G. Langgawan P, E. Ramadhani, A. I. N. F. Abdullah","doi":"10.1109/ICIC50835.2020.9288592","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9288592","url":null,"abstract":"Ministry of Research, Technology, and Higher Education of the Republic of Indonesia stated that every university in Indonesia needs to implement information technology governance, one of which is information technology service governance. XYZ University as one of the universities in Indonesia needs to implement the governance of information technology services. The implementation of information technology service governance can be using the Information Technology Infrastructure Library Version 3 (ITIL V3) framework. One of the information system services that often have issues with help desk services is academic information systems. The issue of academic information system help desk service issues is resolved by using one of the processes in ITIL V3, namely service level management. In this observation, a service level management process was carried out to produce three documents, namely the Service Level Requirement (SLR), Service Level Agreement (SLA), and Operational Level Agreement (OLA). This research includes three main processes, namely collecting data and information, creating documents, and verification and validation. The method of collecting data and information is carried out using interview techniques, the process of making documents, validation, and verification is carried out by conducting group discussion forums with service providers and service users. In this case, service users are the academics of XYZ University, while service users are the Information and Communication Technology Department of XYZ University. This observation resulted in three main documents in service level management, namely SLR, SLA, and OLA, for academic information system help desk services.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125880526","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: 2

Ontology-Based Approach for Dynamic E-Learning Personalization 基于本体的动态电子学习个性化方法

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288570

Kusuma Ayu Laksitowening, Zainal Arifin Hasibuan, Harry Budi Santoso

引用次数: 0

Usability Evaluation and User Interface Design of University Staffing Information System 高校人事信息系统的可用性评价与用户界面设计

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9335917

Bryanza Novirahman, H. Santoso, R. Isal

{"title":"Usability Evaluation and User Interface Design of University Staffing Information System","authors":"Bryanza Novirahman, H. Santoso, R. Isal","doi":"10.1109/ICIC50835.2020.9335917","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9335917","url":null,"abstract":"Human Resources X Information System or “Sistem Informasi Kepegawaian X (SIPEG-X)” is a staffing information system that is used to monitor staff performance at a large public university in Indonesia. Since this information system was first developed, there has been no significant update on the system, especially if it is viewed in terms of user-interface (UI) or user experience (UX). This then led to the difficulty of assessing performance against the university staff because of a lack of satisfaction and comfort in using the information system. Therefore, usability evaluation and design refinement of these university staffing information systems was carried out using user-centered design methodology so that a new system in the form of a mobile application was developed to provide solutions to the interface of this staffing information system. Evaluation is conducted through surveys, usability testing, and contextual interviews to assess the usability aspects of the current implemented website application. The evaluation results show that the usability of these information systems needs to be improved and based on the principle of Shneiderman's Eight Golden Rules of Interaction Design, a prototype is proposed to improve the interface as well as the user experience.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129357623","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: 1

Human Activity Recognition using Reduced Kernel Extreme Learning Machine for Body Weight Management 基于减核极限学习机的体重管理人体活动识别

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288546

Arwin Halim, Erick Kwantan, Silfi Langie, Vinson Chandra, Hernawati Gohzali

{"title":"Human Activity Recognition using Reduced Kernel Extreme Learning Machine for Body Weight Management","authors":"Arwin Halim, Erick Kwantan, Silfi Langie, Vinson Chandra, Hernawati Gohzali","doi":"10.1109/ICIC50835.2020.9288546","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9288546","url":null,"abstract":"The problem with bodyweight management is the inability to calculate the number of calories burned and consumed. Many applications can help to calculate it and one of them is implementing Human Activity Recognition using wearable sensors and smartphones. In this paper, an activity recognition model is built using the Reduced Kernel Extreme Learning Machine (RKELM) algorithm using an accelerometer sensor embedded in a smartphone that is used for calculating calories burned. This model was improved from the Extreme Learning Machine with the addition of the Gaussian kernel. The dataset comes from the London py data event in 2016 which consists of five activity labels. The proposed model will be compared with five other models and evaluated using precision, recall, f1score, training time, and testing time. The results have been validated with 10-fold cross-validation. The experimental results show that the RKELM-based recognition model has a higher performance than the other models with acceptable training and testing time, with an f1 score of 97% and less than 0.06 seconds.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130078619","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

Developing a Quality Metric in Controlling the Project Task 开发控制项目任务的质量度量标准

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288547

Indriana Novitiara, D. Pratami, Achmad Fuad Bay

{"title":"Developing a Quality Metric in Controlling the Project Task","authors":"Indriana Novitiara, D. Pratami, Achmad Fuad Bay","doi":"10.1109/ICIC50835.2020.9288547","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9288547","url":null,"abstract":"In several telecommunication projects, during the monitoring and controlling phases, the quality control and validate scope processes only rely on the receipt test form and handover minutes. Whereas quality errors, in general, can only be seen in the final project phase. If the project deliverables do not meet the customer requirement, the rework must be done or the worst possibility is that the project must be stopped. A quality metric using the internal control method is a project document that can be used to prevent possible problems. There is a quality metric template from previous research proposed for telecommunication projects, but the factors used as variable critical success criteria have not included other important factors that support project success. Therefore, this study will discuss the development of an existing quality metric template and what processes will be affected by the use of this quality metric in a project. It was found that procedures and human factors are critical success factors that can support project success, and quality metrics have an impact on the quality control process and validate scope. It can be concluded that this study produces a quality metric template that has been developed and this quality metric can be used as a template for other projects such as construction projects or IT projects.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132450519","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

Area of Mangrove Forests Calculated by Color Image Segmentation using K-Means Clustering and Region Growing) 基于k均值聚类和区域生长的彩色图像分割计算红树林面积

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288530

R. Rizal Isnanto, Oky Dwi Nurhayati, Tyas Panorama Nan Cerah

{"title":"Area of Mangrove Forests Calculated by Color Image Segmentation using K-Means Clustering and Region Growing)","authors":"R. Rizal Isnanto, Oky Dwi Nurhayati, Tyas Panorama Nan Cerah","doi":"10.1109/ICIC50835.2020.9288530","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9288530","url":null,"abstract":"The calculation of the area of mangrove forests by conventional methods requires much time and energy. In this study, a tool for calculating the area of mangrove forests in Southeast Sulawesi Province, Indonesia, using satellite imagery is developed on the basis of two segmentation methods, k-means clustering and region growing. We then compare those two methods to obtain the optimal method to calculate the area of mangrove forests. Before this research, there were no researchers who calculated the area of mangrove forests in Southeast Sulawesi using both methods. We constructed a calculation algorithm using Matlab, which includes different stages of digital image processing. The area of mangrove forests is calculated on the basis of the number of pixels with an area density of 900 m2/pixel. The accuracy of the two segmentation methods is compared for identical areas obtained by the National Institute of Aviation and Space in Indonesia (LAPAN), i.e., the area obtained by LAPAN is used as a reference in calculating the accuracy. The accuracy of the region growing segmentation method is 33.33%, whereas that by the k-means clustering segmentation method under optimum conditions is 59.26% in the application of 12 clusters.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131933609","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: 1

Data Mining for Student Assessment in e-Leaming: A Survey 电子学习中学生评价的数据挖掘研究

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288533

Wenty Dwi Yuniarti, E. Winarko, Aina Musdholifah

引用次数: 1

Adoption of Upcoming Blockchain Revolution in Higher Education: Its Potential in Validating Certificates 在高等教育中采用即将到来的区块链革命:其在验证证书方面的潜力

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288605

Tuti Nurhaeni, Indri Handayani, Frizca Budiarty, Desy Apriani, P. A. Sunarya

引用次数: 6

Learning Optimization Using Genetic Algorithm in Post-Stroke EEG Signal Classification 基于遗传算法的脑卒中后脑电信号分类学习优化

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288559

Esmeralda Contessa Djamal, Mita Amara, Daswara Djajasasmita, Sandy Lesmana Liem Limanjaya

{"title":"Learning Optimization Using Genetic Algorithm in Post-Stroke EEG Signal Classification","authors":"Esmeralda Contessa Djamal, Mita Amara, Daswara Djajasasmita, Sandy Lesmana Liem Limanjaya","doi":"10.1109/ICIC50835.2020.9288559","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9288559","url":null,"abstract":"A stroke is an attack that often requires long-term rehabilitation. One result of this condition can be seen from abnormal electrical signals in the brain, recorded by an electroencephalogram (EEG). Therefore, EEG can be used for monitoring and evaluation of post-stroke rehabilitation. Neurologists usually observe EEG signals based on their density, amplitude, waveform, and comparison of the channel pairs, but this analysis is not easy. Besides, using machine learning, such as Backpropagation, is sometimes constrained by random initial weights. This state can lead to a long convergence. This paper proposes the selection of initial weights in Backpropagation training using Genetic Algorithms. The use of Genetic Algorithms can optimize the initial weight selection in Backpropagation. The EEG signal used has been extracted into Alpha, Theta, Delta, and Mu waves. The experimental results show that using the Genetic Algorithm can increase non-training data accuracy to 75%, compared to only 65% without the genetic algorithm. Genetic Algorithms can overcome overfitting and local maximums. The results also show that the use of Wavelet transform for feature extraction can increase the accuracy from 60% to 75%. The optimization of training parameters also determines the accuracy.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126377210","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

Examining GOJEK Drivers' Loyalty: The Influence of GOJEK's Partnership Mechanism and Service Quality GOJEK司机忠诚度检验:GOJEK伙伴机制与服务质量的影响

2020 Fifth International Conference on Informatics and Computing (ICIC) Pub Date : 2020-11-03 DOI: 10.1109/ICIC50835.2020.9288612

F. Azzahro, Muhammad Adil, Arya Fathurrahman, Athifah Fidelia Sectianri, Nabila Laili Halimah, A. Hidayanto, Adhi Yuniarto Laurentius Yohanes

{"title":"Examining GOJEK Drivers' Loyalty: The Influence of GOJEK's Partnership Mechanism and Service Quality","authors":"F. Azzahro, Muhammad Adil, Arya Fathurrahman, Athifah Fidelia Sectianri, Nabila Laili Halimah, A. Hidayanto, Adhi Yuniarto Laurentius Yohanes","doi":"10.1109/ICIC50835.2020.9288612","DOIUrl":"https://doi.org/10.1109/ICIC50835.2020.9288612","url":null,"abstract":"The emerging ride-hailing services providing services to 60.7 million customers daily has, in aggregate, become a US$5,261 million industry in Indonesia. Such a flourishing industry is being overpowered by two companies, GOJEK and GRAB. Most research is focused on how to maintain and gain more customers in ride-hailing companies while forgetting that drivers are as essential as customers in the industry. This paper aims to understand GOJEK drivers' loyalty toward the company, by examining the role of partnership and service quality provided by GOJEK for them. The study uses a quantitative approach to 150 respondents and then analyze the data using PLS-SEM. The study shows that partnership has a significant influence on trust, service quality, and driver satisfaction towards the company. Meanwhile, trust and satisfaction have a significant direct effect on loyalty. Thus, to improve drivers' loyalty, GOJEK needs to strengthen its partnership with drivers and provide better service quality for them.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114184560","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: 1