{"title":"String Transformations Preserving Analogies","authors":"Y. Lepage","doi":"10.1109/ICACSIS.2018.8618162","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618162","url":null,"abstract":"This paper examines the following problem: which transformations on strings preserve analogy? For instance, consider the analogy putra: putera:: putri: puteri.<sup>1</sup>1Indonesian: prince/son, princess/daughter in two possible spellings. If we systematically reduplicate the characters in the strings (ppuuttrraa: ppuutteerraa:: ppuuttrrii: ppuutteerrii), or systematically insert a space between each character in the strings (p⎵u⎵t⎵r⎵a: p⎵u⎵t⎵e⎵r⎵a:: p⎵u⎵t⎵r⎵i: p⎵u⎵t⎵e⎵r⎵i), the analogies between the transformed strings still hold. The analogies considered are formal analogies of commutation between strings of characters, the definition of which makes use of LCS distance. Experiments on more than 16 million formal linguistic examples confirm several theoretical results, invalidate some hypotheses, and allow to test interesting conjectures.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124227815","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":"Dynamic Thresholding Mechanisms for IR-Based Filtering in Efficient Source Code Plagiarism Detection","authors":"Oscar Karnalim, Lisan Sulistiani","doi":"10.1109/ICACSIS.2018.8618207","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618207","url":null,"abstract":"To solve time inefficiency issue, only potential pairs are compared in string-matching-based source code plagiarism detection; wherein potentiality is defined through a fast-yet-order-insensitive similarity measurement (adapted from Information Retrieval) and only pairs which similarity degrees are higher or equal to a particular threshold is selected. Defining such threshold is not a trivial task considering the threshold should lead to high efficiency improvement and low effectiveness reduction (if it is unavoidable). This paper proposes two three holding mechanisms-namely range-based and pair-count-based mechanism-that dynamically tune the threshold based on the distribution of resulted similarity degrees. According to our evaluation, both mechanisms are more practical to be used than manual threshold assignment since they are more proportional to efficiency improvement and effectiveness reduction.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115507617","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}
L. Nadeak, B. Purwandari, Riri Satria, Larastri Kumaralalita
{"title":"Success Factor Analysis of Jakarta Siaga 112 Emergency Service Management System","authors":"L. Nadeak, B. Purwandari, Riri Satria, Larastri Kumaralalita","doi":"10.1109/ICACSIS.2018.8618265","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618265","url":null,"abstract":"Jakarta Siaga 112 Emergency Service is an emergency call provided by the government of Special Capital Region of Jakarta to handle emergency calls from the citizens. Jakarta Siaga 112 Emergency Service Management System is run by the staffs of Jakarta government to organize the follow-ups of emergency calls. Referring to the importance of this system, a study was administered to evaluate factors affecting its success. The investigation was conducted based on the DeLone and McLean success model. Data were collected using questionnaires distributed to staffs of Jakarta Government Work Units and agencies, who work together on the system. The data were analyzed using Partial Least Squares-Structural Equation Model. The results demonstrate that System Quality, Information Quality, Service Quality, Use, User Satisfaction, and Net Benefits significantly influence the success of this system. However, two out of nine hypotheses are rejected. These are the relationship between System Quality towards Use, as well as Use towards User Satisfaction. Theoretical impact from the research and result is to enrich the diversity of research related to emergency services in the field of information technology.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130790684","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}
Clarissa Nuralifa Mangkunegara, Fatunah Azzahro, P. W. Handayani
{"title":"Analysis of Factors Affecting User's Intention in Using Mobile Health Application: A Case Study of Halodoc","authors":"Clarissa Nuralifa Mangkunegara, Fatunah Azzahro, P. W. Handayani","doi":"10.1109/ICACSIS.2018.8618174","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618174","url":null,"abstract":"This study aims to evaluate essential factors that affect user's behavioral intention in using Halodoc, a mobile health application. This study examines factors from several theories and perspective such as TAM, TPB and Health Belief Model. A total of 146 Halodoc's users completed the online survey. The data is processed by using SmartPLS (v. 3.2.7). The result shows that perceived usefulness, perceived behavioral control, trust, self-health awareness, system quality, and attitude influence users' behavioral intention in using Halodoc.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130801611","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":"Classification of Limestone Mining Site using Multi-Sensor Remote Sensing Data and OBIA Approach a Case Study: Biak Island, Papua","authors":"Daniel Sande Bona, A. M. Arymurthy, P. Mursanto","doi":"10.1109/ICACSIS.2018.8618198","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618198","url":null,"abstract":"Most of Soil Type in Biak Island, Papua is Coral Limestone. This limestone is used as building material. Limestone mining is one of the income sources for local people. This study tries to map limestone mining sites using multi-sensor remote sensing data fusion and Object-Based Image Analysis (OBIA) classification approach. 1.5 meters resolution SPOT-6 data acquired in 2015 and 2017 used as spectral and geometric parameters in OBIA classification process. Surface deformation points obtained from the PS-InSAR technique on Sentinel-IA SLC SAR data acquired from November 2017 to May 2018 is used as the structural variable for OBIA classification process to determine whether mining site is active or inactive. The overall accuracy of classification result is 84.7% for 2015 SPOT-6 data and 74.9% for 2017 SPOT-6 data.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121597738","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":"Human Identification Using Human Body Features Extraction","authors":"Martino C. Khuangga, D. H. Widyantoro","doi":"10.1109/ICACSIS.2018.8618211","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618211","url":null,"abstract":"A system that can mark personnel attendance becomes an increasingly important tool. It usually requires human action in order to detect the presences of a person such as putting finger on a scanner in a fingerprint detection system. There are some systems that do not need human action (such as the use of camera in a face recognition system) but it requires human face database. This paper introduces human identification system implementing human body feature extraction, which can track the presence of persons in a room. The system uses camera as input device to remove the special action needed. Features on human body was chosen because they tend to be easier to detect and serve as a strong identity to mark person who enter a room, yet we do not need to train body features first. There are two main processes in this system. First, the system detects person entering a room. Second, it also detects the same person leaving the room. This application was implemented using image processing techniques such as human detection using HOG descriptors, HSV color conversion, and template matching. Tracking failures from this application could happen because this system still could not handle some special cases.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121604641","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":"The Analysis of Critical Success Factor Ranking for Software Development and Implementation Project Using AHP","authors":"Ryann Octavianus, P. Mursanto","doi":"10.1109/ICACSIS.2018.8618147","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618147","url":null,"abstract":"The success criteria of a project are the timeliness of completion, the costs incurred not exceeding the budget, the client's needs are met, and the team management which is running well. Some of research found that more than half of the IT projects experience failure. Variables used to determine the most influential factor in software development and implementation success consist of criteria, factor category and factors. Particularly in Verint where the case study took place, there is currently no research on the ranking of factors that affect the success of IT projects. This paper presents quantitative method to perform data analysis using Analytic Hierarchy Process (AHP). The result shows that skilled staff from management attitude category is the most influential factor in software development and implementation project in Verint.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121640277","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":"Music Era Classifcation using Hierarchical-level Fusion","authors":"M. Pratama, M. Adriani","doi":"10.1109/ICACSIS.2018.8618242","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618242","url":null,"abstract":"Music era is one of Music Information Retrieval research that connecting several songs with similar characteristics from similar year or decade but not limited to particular genre and mood. Previous researcher tried to recognize musical era with classification model using single audio feature like spectrogram and chromagram, but the performance was poor. Feature and model selection affect classification era performance. One of the challenge in selecting feature is whether the using of multimodal or combination of audio features can improve music era classification performance. In this research, Hierarchical-level fusion model is used to combine several audio features like spectrogram and chromagram to determine music era. We obtained both 83% and 73% overall accuracy for Indonesian Music Dataset (IMD) and Mimon Song Dataset (MSD) of era classification tasks using Hierarchical-level fusion model. This research result also strengthened with overall precision, recall, and F-score result 0.83, 0.82, 0.82 for IMD dataset and 0.73, 0.72, 0.72 for MSD dataset experiment.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122022194","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":"Information Extraction for Mobile Application User Review","authors":"Erry Suprayogi, I. Budi, Rahmad Mahendra","doi":"10.1109/ICACSIS.2018.8618164","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618164","url":null,"abstract":"The growth of mobile e-commerce and the popularity of smartphones makes the intensity of mobile app users increase exponentially. The users can provide reviews related to their experience while using the application, this review can contain valuable information such as complaints or suggestions that can be used for further in-depth analysis based on reviews given. However, the large number of reviews makes it difficult to find and understand the information contained in each review. To solve these problems, this study proposes a model that can extract information in the reviews by categorizing and analyzing sentiments in each review using the text mining approach and machine learning techniques, we use several algorithms for sentiment analysis, classification and modeling topics that are popularly used by previous researchers. The output of this model is a collection of the most trending reviews that have been identified and classified as polarity sentiments and review categories. We had conducted a series of experiments to find the best model, the average sentiment precision of reviews is 85% and the best algorithm for classifying the reviews obtained using SVM with an average FI score of 84.38% using the unigram feature while the NMF works better compared to LDA in modeling topic reviews.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123421607","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":"Measuring Information Security Awareness on Employee Using HAIS-Q: Case Study at XYZ Firm","authors":"Alvin Cindana, Y. Ruldeviyani","doi":"10.1109/ICACSIS.2018.8618219","DOIUrl":"https://doi.org/10.1109/ICACSIS.2018.8618219","url":null,"abstract":"Information security cannot be separated from its user behavior. Many organizations applied an information security policy, but cease at the human aspects of information security. XYZ firm has implemented information security policies and socialized it towards its employee through several ways. However, the internal control division of XYZ firm always finds violation towards information security policies every time they conduct office sweeping. This study was conducted to measure the employee’s information security awareness in XYZ firm using HAIS-Q framework that has seven focus area (password management, email usage, internet usage, social media, mobile device, information handling, and incident reporting) and weighed to three dimension of knowledge (knowledge, attitude, and behavior). The result of ISA measurement in the XYZ employee considered as good with total score 87.59. However, this study indicates that employee’s information security awareness on internet usage should be improved by the firm since it was classified as average with score 79.07.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128966052","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}