{"title":"Error numerical analysis for result of rainfall prediction between Tsukamoto FIS and hybrid Tsukamoto FIS with GA","authors":"I. Wahyuni, Fitri Utaminingrum","doi":"10.1109/ICACSIS.2016.7872721","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872721","url":null,"abstract":"Rainfall is one important aspect of everyday life, but now rainfall increasingly unpredictable. Therefore it needs to make an accurate method to predict rainfall with small error. Tsukamoto FIS and genetic algorithm is one of algorithms that can be used for prediction problems. Research using Tsukamoto FIS and hybrid Tsukamoto FIS with GA for forecasting rainfall had been done already. The prediction results generated from both methods have a diverse error value. Need an error analysis to determine which method is most optimal to predict rainfall with minimum error. Therefore, this study focuses on error numerical analysis on the result of rainfall prediction using Tsukamoto FIS and hybrid Tsukamoto FIS with GA. From the analysis, Tsukamoto FIS produce relatively small error, but this method is weak when predicting rainfall = 0 or no rain. While hybrid Tsukamoto FIS with GA produce small error for predicting rainfall = 0 or no rain. It concluded that a hybrid method Tsukamoto FIS with GA generate an error value more smaller than Tsukamoto FIS.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132985917","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":"Incremental product configuration in software product line engineering","authors":"Triando, Radu Muschevici, A. Azurat","doi":"10.1109/ICACSIS.2016.7872749","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872749","url":null,"abstract":"Producing software variations from the same software product line requires developers to adopt developing tools that support variability. The Abstract Behavioral Specification (ABS) is a modeling language that facilitates the generation of various software products from a single code base. One part of ABS is the Product Selection Language (PSL), which is used to specify software products as sets of features. Even though some products might share some features, using PSL, all features in a product need to be stated one by one. If the product is obtained from tens to hundreds of features, defining the product will be difficult and inefficient To remedy this situation, we extend the PSL such that products can be declared incrementally, by referring to other products. Such declarations contain product expressions that use set-theoretic operations (i.e., union, intersection, complement) over products and sets of features. We evaluate our extended PSL with a case study of a Charity Organization System developed at the RSE Research Lab in the Faculty of Computer Science at Universitas Indonesia.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124354028","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}
M. S. Pebriadi, Vektor Dewanto, W. Kusuma, F. Afendi, R. Heryanto
{"title":"Learning similarity functions for binary strings via genetic programming","authors":"M. S. Pebriadi, Vektor Dewanto, W. Kusuma, F. Afendi, R. Heryanto","doi":"10.1109/ICACSIS.2016.7872773","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872773","url":null,"abstract":"Data that encode the presence of some characteristics typically can be represented as binary strings. We need similarity functions for binary strings in order to classify or cluster them. Existing similarity functions, however, do not take advantage of training data, which are often available. We believe that similarity functions should be data-specific. To this end, we use genetic programming (GP) to learn similarity functions from training data. We propose a novel fitness function that considers five aspects of good similarity functions, i.e. recall, magnitude, zero-division, identity and symmetry. We also report mostly-used math operators from extensive literature review. Experiment results show that GP-based similarity functions outperform the well-known Tanimoto function in most datasets in terms of classification accuracy using SVMs. In addition, those GP-based similarity functions are simpler: using fewer numbers of operators and operands. This suggests that our proposed fitness function for GP is justifiable for learning similarity functions.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125764372","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":"Multimodal decomposable models by superpixel segmentation and point-in-time cheating detection","authors":"Yohannes, Vina Ayumi, M. I. Fanany","doi":"10.1109/ICACSIS.2016.7872729","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872729","url":null,"abstract":"This research aims to classify cheating activity during exam from video observation. The method uses Conditional Random Field (CRF) for classifying and detecting some classes of cheating activities. The method used to detect the location of the joints of the body is a Multimodal Decomposable Model (MODEC) with superpixel segmentation. The used joints are head, shoulders, elbows, and wrists. The superpixel method is Simple Linear Iterative Clustering (SLIC). Comparison between MODEC and MODEC + SLIC as feature detector for CRF showed that MODEC + SLIC capable of providing a better activity classification. From our experiments, the cheating activities in average can be detected up to 83.9%. Moving beyond only detecting the class of motion segments, we also devised point-in-time event detection system also using CRF. The time of occurrences of three consecutive cheating activities are determined from a sequence of video frames.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125985620","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}
B. Purwandari, I. Budi, D. I. Sensuse, Puji Rahayu
{"title":"Indonesian certification of competency profession: A proposed conceptual E-portfolio model","authors":"B. Purwandari, I. Budi, D. I. Sensuse, Puji Rahayu","doi":"10.1109/ICACSIS.2016.7872764","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872764","url":null,"abstract":"The purpose of this study was to describe the process of developing a conceptual model in the development of models of E-portfolios for Professional Competency Certification in Indonesia. Stages in the development of conceptual model begin with a review of literature that aims to analyze and evaluate the facts of the previous studies. There are six concepts that will be discussed: (a) Certification of Competence Professional, (b) Factor E-portfolio, (c) the model ICCP E-portfolio, (d) Actor Network Theory, and (e) Recommender System. In the process of Professional Competence Certification in Indonesia, the portfolio is used as a document to evaluate the competence of the workforce, which still uses paper-based portfolios. The paper based portfolio is static and limited in sharing information with others in the management process, evaluation and updating the material is also difficult. It is expected that the conceptual model will contribute to the development of e-portfolio system to be applied in the Professional Competency Certification in Indonesia.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"10 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114030769","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":"Health capability: The representation of IoT in health domain among Jakartans","authors":"Tommy Prayoga, Juneman Abraham","doi":"10.1109/icacsis.2016.7872789","DOIUrl":"https://doi.org/10.1109/icacsis.2016.7872789","url":null,"abstract":"The advancement of new technologies provides not only better understanding of health but also ways to encourage it. For example, IoT in health domain comes a long way than just helping individuals regulate their body. It has enabled many social functions that connect users to serve more health related purposes. However, in Indonesia, as such an idea is still novel, there is a need to examine how is it being represented in health context to increase health capabilities. We asked 241 college students across Greater Jakarta (17–25 years old; Mean of age = 20.47 years old; Standard deviation of age = 1.469 years; 83 males, 158 females) 10 questions to measure their Social Representation towards IoT in the health domain. This is a descriptive research, and the instrument for data collecting is a questionnaire. The data obtained were analyzed using Voyant tool to generate words cirrus for every answer. The result showed that although participants generally perceive that IoT in health domain is potentially beneficial and can be used to increase health capabilities, there are a few practical agency freedom limitations, such as individual dispositions and economic status.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115804970","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}