Annisa Monicha Sari, A. Hidayanto, B. Purwandari, M. Kosandi, W. R. Fitriani
{"title":"Measurement Scale of e-Complaint Service Quality","authors":"Annisa Monicha Sari, A. Hidayanto, B. Purwandari, M. Kosandi, W. R. Fitriani","doi":"10.1109/ICACSIS47736.2019.8979853","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979853","url":null,"abstract":"Emerging technology has changed human activities to be more efficient and effective. Citizens become more participatory in their involvement in the process of policymaking, decision making, or service design utilizing technology, communication, and information. In developing countries including Indonesia, electronic participation especially e-complaint has been recently implemented. There is a continuous desire from the citizen for better service quality along with the implementation. It is a challenge for the government to improve e-complaint service quality. The previous study claimed that we must first know how citizens apprehend and assess online to deliver better service quality. The objective of this study is conceptualizing, develop, refine the scale for measuring e-complaint service quality. The factor analysis with principal component analysis (PCA) used to stable the dimension of e-complaint service quality. We classified 23 item-scale under five main dimension of e-complaint service quality, they are technical efficiency, responsiveness, transparency, security, and citizen-support.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115475333","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}
Harits Muhammad, P. W. Handayani, M. Rifki Shihab, F. Azzahro
{"title":"The Development of Digital Marketing Strategy for Tourism Startup: A Case Study of Atourin","authors":"Harits Muhammad, P. W. Handayani, M. Rifki Shihab, F. Azzahro","doi":"10.1109/ICACSIS47736.2019.8979797","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979797","url":null,"abstract":"The development of startup companies is supported by the growth of internet users and also positive developments and large market customers have attracted investment interest both from within and outside the country. With the business process that is unique and highly dependent on the effectiveness of product positioning and promotion methods, a startup named Atourin requires the development of marketing strategies to improve competitiveness to develop its business model. This can help to meet the periodic targets as a reference for Atourin’s business development, which will be information that is accountable to investors. This research was conducted with a qualitative approach that was included in the case study by interviewing Atourin’s top level management and observing Atourin’s performance and conducting market and competitive analysis relevant to the Atourin’s business model to provide recommendations to companies in the form of marketing-based strategies information technology tailored to the context of Atourin. This study describes various strategies and tactics in utilizing information technology-based marketing to achieve the stated objectives, which produce eight strategies and fourteen tactics which generally describes strategies in attracting visitors who have an interest in tourism to visit the Atourin site and become Atourin’s active users. The results of this study can be used as a reference in the formation of information technology-based marketing strategies that are in line with Atourin’s business needs.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116307831","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}
Luthfi Aulia Sulaiman, Harry Budi Santoso, R. Isal
{"title":"Interaction Design Development on Indonesia)s Computer-Based National Exam Using User-Centered Design","authors":"Luthfi Aulia Sulaiman, Harry Budi Santoso, R. Isal","doi":"10.1109/ICACSIS47736.2019.8979827","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979827","url":null,"abstract":"With the development of technology, there are advances that help civilizations on their day-to-day activities, one of which is the implementation of e-Learning on the Final Exams. A standardized national computer-based final examination in Indonesia is called Ujian Nasional Berbasis Komputer (UNBK). Despite the fact that UNBK has been held nationwide since 2016, its interface and system have only gone through minor improvement throughout the years. To improve the usability and interface of UNBK, it is necessary to first evaluate the current interface from the users. The user evaluation was conducted using a mixed-method approach to compare and/or relate qualitative data and quantitative data. The user evaluation using an online questionnaire with the Post-Study System Usability Questionnaire (PSSUQ) shows that UNBK’s quality only exceeds in System Quality with a score of 75.71 out of 100. The online questionnaire data is supported with the qualitative data of contextual interviews, resulting in an affinity diagram to observe users’ needs, pain points, and missing opportunities. The improved interface design according to the users’ feedbacks was also tested using Usability Testing. The result of the UT shows that it has the binary task succession rate of 86.50%.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"489 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122174747","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}
{"title":"Analysis of Factors Affecting The Success of The Use of Academic Information Systems On Lecturer Users: A Case Study of Sriwijaya University","authors":"N. Ulfa, D. I. Sensuse, Y. Ruldeviyani","doi":"10.1109/ICACSIS47736.2019.8979861","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979861","url":null,"abstract":"Sriwijaya University (Unsri) as one of the state higher education institutions should be able to utilize information and communication technology in supporting various activities, one of which is in the learning process activities. One of the uses of information and communication technology at Sriwijaya University is by using an academic information system named Sistem Informasi Manajemen Akademik (SIMAK) of Sriwijaya University (Unsri). SIMAK is a mandatory system developed in 2008 to support academic activities in Unsri. Unsri has never evaluated the success factor of using SIMAK. Because it is a mandatory system, the success in carrying out academic activities depends on SIMAK application, so the researcher want to know what factors affecting the success of SIMAK usage on lecturer users. The research model used is a modification of DeLone and McLean information system success theory by adding several variables from individual aspects and organizational aspects. Data collection through a survey of 1232 lecturer respondents who were SIMAK users. The research method used is the mixed method. Structural Equation Modeling (SEM) is used to analyze data and SmartPLS as data processing tools. The results indicate the factors that affecting the successful use of SIMAK, namely information quality, service quality, system quality, self-efficacy, top management support, user satisfaction, and net benefits.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117343956","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}
{"title":"Modeling and Predicting Protein-Protein Interactions of Type 2 Diabetes Mellitus Using Feedforward Neural Networks","authors":"A. A. Zulfikar, W. Kusuma","doi":"10.1109/ICACSIS47736.2019.8979989","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979989","url":null,"abstract":"Data of protein-protein interactions (PPIs) are still limited. More data of PPIs are required so one can find significant proteins representing a disease more accurately. Computational approach which can predict PPIs is one of alternatives to reduce time and cost that generally required by experimental work. This research focused on predicting PPIs of Type 2 Diabetes mellitus using feedforward neural network (FNN). Impact of different activation functions, number of units per hidden layers and number of hidden layers themselves to estimation error were observed. Rectifier activation function, seven hidden layers and 36 units per hidden layers gave smallest MSE separately. The model with those configurations predicted a PPI with predicted combined score of 0.922. FNN model had better prediction accuracy than random forest and support vector regression models.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126267902","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}
{"title":"Hyperspectral Analysis for Detection of Sea Cucumber Habitat (Holothuria scabra) based on Support Vector Machine","authors":"R. Utami, A. H. Saputro","doi":"10.1109/ICACSIS47736.2019.8979955","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979955","url":null,"abstract":"Sea cucumbers are sea animals that have a high nutrient and high selling value in both the local market and international markets. In Indonesia, sea cucumbers are found in almost all Indonesian waters, but sea cucumbers in Indonesia have not been grouped by their habitat due to lack of technology that can categorize sea cucumber habitats quickly, precisely and does not damage sea cucumbers. The method is generally destructive and is carried out manually in laboratory tests. In this paper, a classification system from the origin of sea cucumber habitats is introduced using non-destructive Hyperspectral imaging by detecting electromagnetic waves with a spectral range of 400 to 1000 nm. The system algorithm consists of measurement of reflected image profiles, feature extraction, feature selection for spectral and spatial data, object profiles will be combined to select excellent features using the PCA (Principal Component Analysis) method. The data used will be classified into two habitat classes, namely, Pontianak and Belitung using the SVM (Support Vector Machine) method. Data samples will be evaluated with cross-validation to measure system performance. Based on experiments, the accuracy obtained from the classification and evaluation of the SVM method is 92%. The results of this work indicate that this system can be proposed as a classification system for the origin of habitats that do not damage sea cucumbers and are suitable for use in industrial sorting systems.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125567701","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}
{"title":"Image Deblurring Using Scale-recurrent Network for Mobile Devices","authors":"I. Pambudi, D. Chahyati","doi":"10.1109/ICACSIS47736.2019.8979906","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979906","url":null,"abstract":"Image deblurring is a problem in computer vision that aims to restore blur images into sharp images. The blurring might be caused by the camera shaking or an object moving when the image is captured, resulting in an image with a non-uniform blur in a dynamic scene. One recent approach to restoring images with non-uniform blur is by using end-to-end deep neural networks. Continuing the deblur research using a scale-recurrent network, we modify the neural network architecture to be lighter to run on mobile devices. The proposed method achieves PSNR of 29.55 and SSIM of 0.8873 in a 16.9 MB sized model. The inference process on a mobile device only requires 1 GB of memory with 8.2 seconds in latency for deblurring a single 1280x720 pixel image.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127011093","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}
A. Aditya Rahman, P. Gusman Dharma, R. Mohamad Fatchur, A. Nala Freedrikson, B. Pranata Ari, Y. Ruldeviyani
{"title":"Master Data Management Maturity Assessment: A Case Study of A Pasar Rebo Public Hospital","authors":"A. Aditya Rahman, P. Gusman Dharma, R. Mohamad Fatchur, A. Nala Freedrikson, B. Pranata Ari, Y. Ruldeviyani","doi":"10.1109/ICACSIS47736.2019.8979656","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979656","url":null,"abstract":"Patient’s master data is an important data for hospital’s operational. If the master data quality does not meet the expectation, it will affect the billing process and then will affect the income for the hospital. Master data management can help the hospital to integrate all their master data they have so for each data there will be only single source of truth and validity of data will be complied. By doing assessment of master data management maturity, hospital will be able to identify what aspect of master data management that they lack so the process can be improved as well as the quality of master data. Assessment of master data management maturity level is done using Master Data Management Maturity Model (MD3M) by Spruitz and Pietzka. The assessment showed 90 percent of activity related to master data management has been implemented. Some policies need to be implemented regarding to the master data management, such as documentation of the policies and the definition of master data, formal appointment of the data stewards, and the implementation of master data quality management.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121771017","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}