{"title":"Dynamic nearest neighbours for generating spatial weight matrix","authors":"Mutiara Mawarni, Imam Machdi","doi":"10.1109/ICACSIS.2016.7872771","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872771","url":null,"abstract":"Spatial weight matrix is an important aspect in spatial analysis. Selecting different spatial weight matrix for the same analysis method will eventually generate different results. The commonly used scenarios to create spatial weight matrix are contiguity based and distance based. However, these scenarios have their own problems. Contiguity based scenario like Queen and Rook has disadvantages of forming unconnected neighbours especially for sparse region like islands. Meanwhile, distance based scenario needs specific input parameters, which often requires exhausted trials or expert judgement to specify the parameters. For distance based k-Nearest Neighbours, the result will be asymmetric weight matrix that cannot be used for two-way interaction analysis. To overcome these problems, we propose a Dynamic Nearest Neighbours (DNN) algorithm. It uses different types of distance, which are coordinate distance and attributed distance. In the evaluation, DNN algorithm outperforms other techniques of Rook, Queen, and Α-Nearest Neighbours since it can be applied to both contiguous and sparse regions and produce two-way relations.","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":"129089913","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}
Hurriyatul Fitriyah, E. R. Widasari, R. Denny Sagita, A. Bagus
{"title":"Design of remote control for smart home using interaction design method","authors":"Hurriyatul Fitriyah, E. R. Widasari, R. Denny Sagita, A. Bagus","doi":"10.1109/ICACSIS.2016.7872774","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872774","url":null,"abstract":"Smart home devices are mostly controlled using mobile application and touch-screen device which are expensive and fragile. There are cheaper and more solid controller which is button-based remote control, however it has enormous buttons that are confusing. This paper proposes a development of button-based remote control which is equipped with simple LCD screen. The LCD screen is accessorised in the remote control to reduce number of buttons and give visual feedback to users. The remote control is utilized for simple on-off operation and dedicated for Indonesian users. Its design method apply Interaction Design Method as guidance to maximize its usability. The method consists of following steps: (1) What is wanted, (2) Analysis (3) Design (4) Prototype, (5) Implementation and Deployment. The prototype was build using Arduino Nano as microcontroller, small LCD screen and push button switches. The remote control was first tested in functionality for design verification and it shows good performance to comply every given tasks. Afterward, user-participation test was conducted with 30 respondents. Based on the observation of user performing 8 tasks of swithcing on and off four smart home devices (gate, lamp, sprinkle and electronic devices) using the developed remote-control for the first time, average excecution time for each task is 9.2 seconds. Furthermore, USE quistionnaire given to users after experiencing the remote-control showed that its usability in terms of usefullness, satisfaction, ease of use and ease of learning achieved mode of grade 4 in 1–5 Likert scale.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"73 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":"125938121","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":"Supporting and inhibiting factors of e-commerce adoption: Exploring the sellers' side in Indonesia","authors":"Muslim, P. Sandhyaduhita","doi":"10.1109/ICACSIS.2016.7872777","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872777","url":null,"abstract":"In 2015, the number of internet user in Indonesia, already reached 88.1 million. There are around 5 million SMEs in Indonesia, but only about 75 thousand are already using e-commerce which means that the adoption of e-commerce by SMEs is still relatively low. Hence, this research aims to investigate what are the supporting and inhibiting factors for sellers (SMEs) in adopting e-commerce. The initial list of factors from the literature review are validated by 11 experts which resulted 25 supporting and 17 inhibiting factors grouped by using a combination of TOE framework and UTAUT model, namely I-TOE framework. Then, we distributed questionnaires on the basis of Fuzzy-AHP to rank the factors. The results show the top supporting factors are “Perceived ease of use”, “Technology infrastructure available”, “Customer communication improved”, and “Encouragement from environment culture” while the top inhibiting factors are “Perceived no benefit gain”, “Supporting infrastructure unavailable”, “Lack of business compatibility”, and “Vendor less friendly to customer”.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"15 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":"125817621","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":"An adaptation of the Index of Learning Style (ILS) to Indonesian version: A contribution to Index of Learning Style (ILS), validity and reliability score","authors":"Ayu Sahnaz Ovariyanti, H. Santoso","doi":"10.1109/ICACSIS.2016.7872762","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872762","url":null,"abstract":"Every student has different learning styles. They have tendency in perceiving, interacting and processing information they have learned. Those tendencies can be identified by assessing stodente' learning styles using the Index of Learning Style (ILS). ILS is commonly used to identify engineering student's learning style in learning personalization system. However, this questionnaire is developed in English language. Moreover, this study aims to give contribution in translating the questionnaire to Indonesian version. Hence, students who have Indonesian language as their mother tongue could easily understood the questionnaire. This study also describes the validity and the reliability score of the ILS adaptation to Indonesian version. There are four statements in Indonesian version of ILS that need to be revised. The Cronbach's alpha for the translated ILS is .602 that is reliable enough.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"21 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":"121517261","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":"An adaptive background estimation for real-time object localization on a color-coded environment","authors":"Peter Chondro, S. Ruan","doi":"10.1109/ICACSIS.2016.7872756","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872756","url":null,"abstract":"Object localization is a powerful technique to analyze certain features on particular objects for either general or specific purpose(s). To localize object within image frames, the background subtraction scheme is generally implemented as an unequivocal technique that pre-processes die corresponding input frame. Nevertheless, despite the prior developments and applications of various techniques for estimating backgrounds, eminent challenges remain in achieving real-time applications and robust detection. In this paper, an adaptive background estimation technique models specific color-coded environment to localize objects through color-based pixel-wise subtraction is proposed. Experimental evaluations indicate the grandeur of the proposed method compared with prior methods.","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":"131412653","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":"Comparative analysis of string similarity and corpus-based similarity for automatic essay scoring system on e-learning gamification","authors":"Eko Sakti Pramukantoro, M. Fauzi","doi":"10.1109/ICACSIS.2016.7872785","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872785","url":null,"abstract":"Essay assessment within e-learning need to be conducted manually by human expert. This process takes time and costly. Hence, automatic essay scoring is needed. Since the scoring system will be integrated to the e-learning, we need a computationally lightweight method that still does not rule out the accuracy of the assessment. In this paper, we propose an automatic scoring system for essay examination using unsupervised approaches. We compare and analyze two similarity measure methods, cosine similarity and latent semantic analysis. The parameters that was used to measure the performance of the methods are the computational complexity — measured by the amount of CPU and memory usage, and page load time — and accuracy — measured by Pearson Correlation and Mean Absolute Error. The results showed that both algorithm consumed same amount of memory. For CPU usage, LSA consumption is 0.13% and cosine's is 0.06%. For page load time, cosine similarity is faster than LSA which is 0.2 second and 0.5 second consecutively. Based on the correlation measure with Pearson, LSA is more superior to the cosine similarity by 0.59 to 0.49. LSA also has less MAE than cosine similarity which is 5.69 compared to 5.33. From that result, LSA and Cosine Similarity has a very competitive result in accuracy. However, Cosine has a better server performance so that preferred to be implemented in e-learning automatic essay scoring system.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"39 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":"128263528","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 emotion recognition based on active appearance model and semi-supervised fuzzy C-means","authors":"D. Liliana, M. R. Widyanto, T. Basaruddin","doi":"10.1109/ICACSIS.2016.7872744","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872744","url":null,"abstract":"Human emotion recognition is an emerging research area in the field of social signal processing. Facial expression is an important means to detect human emotion. The problem is some facial expressions represent similar emotions. Thus, the recognition must consider the ambiguity in the way human expresses emotions through face. Existing methods do not take into account the level of expression's ambiguity. In our research, we specify face points and display the degree of fuzzy cluster on eight face emotions, namely anger, contempt, disgust, happy, surprise, sadness, fear, and neutral. The proposed methods are based on Active Appearance Model (AAM) and semi-supervised Fuzzy C-means (FCM). We tested the system on Cohn Kanade+ dataset of facial expression which provided eight classes of human emotion. Our methods gain an average accuracy rate of 80.71% and surpass the existing Fuzzy Inference System.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"34 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":"128892837","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":"Combining topological and topical features for community detection","authors":"Retnani Latifah, M. Adriani","doi":"10.1109/ICACSIS.2016.7872775","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872775","url":null,"abstract":"Community detection is an important approach to identify community's structure in a network and can also be considered as graph clustering. This paper conducted a research about community detection using combined topological and topical features in Twitter. The combined features were compared to topological only and topical only. The topological features that were used are following-follower relationship and retweet-favorite ratio while topical features are hashtags, mentions, links and tweets. This research proposed a new node weight using retweet-favorite ratio to build topological matrix and it has been proved to have higher purity value by 30–40% and higher rand index value by 10–20%. The purity value of combining topological and topical features is also improved by 30% compared to using following-follower relationship as topological features. The highest rand index and purity values are achieved by matrix of combinied topological and topical features with multilevel community detection as clustering algorithm with 0.89 and 0.77.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"8 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":"132597931","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":"Query refinement in recommender system based on product functional requirements","authors":"Z. Baizal, D. H. Widyantoro, N. Maulidevi","doi":"10.1109/ICACSIS.2016.7872760","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872760","url":null,"abstract":"One of the advantages of conversational recommender system (CRS) is its ability to guide user in expressing their needs through conversation mechanism. In many cases, customers are often unable to express their needs clearly at the beginning of the interaction. CRS guides customer (user) to clarify his needs through the mechanism of query refinement. Not all customers are familiar with the technical features of product, especially for hightech product that has many features (complex products). Therefore, asking the customer's needs based on functionalities of product that he/she really wants (product functional requirements) is a more natural way for eliciting customer preference. This paper proposes a model of query refinement that is able to guide users to express their needs based on the functional requirements of product. The model was developed by utilizing exploration of semantic relations on ontology. The evaluation result shows that our proposed model is able to narrow down the average result's size significantly within short interactions.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"8 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132388985","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":"Adaptive genetic algorithm for reliable training population in plant breeding genomic selection","authors":"S. C. Purbarani, Ito Wasito, Ilham Kusuma","doi":"10.1109/ICACSIS.2016.7872803","DOIUrl":"https://doi.org/10.1109/ICACSIS.2016.7872803","url":null,"abstract":"Many algorithms are developed to model Genomic Estimated Breeding Value (GEBV). Modeling GEBV evolves a huge size of genotype in both terms of the dimension (columns) and the instances (rows). Good combinations of features help in predicting which phenotype is being represented. Preparing a good training population sample is assumed to be a convenient solution to deal with such complex genotype data. In this research, an Adaptive Genetic Algorithm (AGA) is proposed. The adaptive characteristic of AGA by adjusting probabilities in crossover and mutation is expected to converge into the global optimum without getting trapped in local optima. The proposed method using AGA to optimize the feature selection and shrinkage mechanism is looked forward to provide a reliable model to be reused in other similar datasets.","PeriodicalId":267924,"journal":{"name":"2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"7 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132547112","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}