Tresna Maulana Fahrudin, I. Syarif, Ali Ridho Barakbah
{"title":"Discovering patterns of NED-breast cancer based on association rules using apriori and FP-growth","authors":"Tresna Maulana Fahrudin, I. Syarif, Ali Ridho Barakbah","doi":"10.1109/KCIC.2017.8228576","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228576","url":null,"abstract":"No Evidence of Disease (NED) is breast cancer patient condition status which it indicates that they can life, no find the cancer by tested, and without any symptoms of cancer in period of times, after they received primary treatment. NED is a critical status, because it involves the treatment type and patient cancer condition factors. This paper examines about breast cancer problem in data mining technical side, especially to discover the patterns of NED-breast cancer patient using cancer registry data from Oncology Hospital. Its patterns are discovered through the relationship of among features begin from 1dimensional, 2-dimensional, 3-dimensional, and n-dimensional. We applied association rules mining using Apriori and FP-Growth algorithm, which both have the advantage and drawback. Apriori algorithm involves all generation of candidate item sets and multiple database scans, but it makes highconsuming iteration. While FP-Growth algorithm extracts the frequent item sets directly from FP-Tree, it make the advantage of FP-Growth that is faster process needs only scan the database once. This paper experiment shown that the association result of Apriori and FP-Growth is almost similar, 10-highest confidence value represented 100% confidence of association rule on breast cancer dataset with support value up to 50%.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127078928","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}
Ali Ridho Barakbah, Amang Sudarsono, T. Harsono, M. Askari
{"title":"A mobile application for cluster-based visualization of spatio-temporal earthquake data distribution in Indonesia","authors":"Ali Ridho Barakbah, Amang Sudarsono, T. Harsono, M. Askari","doi":"10.1109/KCIC.2017.8228591","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228591","url":null,"abstract":"Earthquake is one of natural disasters that often occurs in Indonesia and may cause damages on environmental and infrastructural properties, such as road, bridge, houses. The high rate of earthquake in Indonesia is that Indonesia is located at the crash point of three major tectonic plates: Eurasian Plate, Australian Plate, and Pacific Plate. This situation challenges a need to prepare participatory development for public awareness regarding the effects of earthquake and how to prepare for a possible hazard risk of earthquake. It helps the government and individuals for consequently saving their live. One of the ways to increase this awareness is to utilize mobile device through earthquake applications. This paper proposes a new system for cluster-based visualization of spatio-temporal earthquake data distribution in Indonesia through a mobile application. The system applies an automatic clustering to detect automatically number of clusters for earthquake data distribution and then analyze characteristics of earthquake behavior for each region in Indonesia. The system provides 4 main features which are (1) Data acquisition and preprocessing earthquake data, (2) Automatic clustering for spatio-temporal data distribution, (3) Mobile data exchange between user and earthquake data server, and (4) Spatio-temporal data visualization. For experimental study, the system used earthquake dataset of ANSS (Advanced National Seismic System) for earthquake activities in Indonesia from 1960 to 2015. The experimental results showed the distribution of earthquake with spatio-temporal features.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132953982","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":"Mobile application for identifying personality of person using graphology","authors":"Kukuh Prasetyo, Nana Ramadijanti, A. Basuki","doi":"10.1109/KCIC.2017.8228589","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228589","url":null,"abstract":"Personality in person definitely has its strengths and weaknesses. Many benefits that we can take with knowing our personality or others. Identifying personality of person can be done using graphology. Graphology is science that is studying about handwriting. Handwriting is human idea that can describe or reflect the human personality. However, many people do not know about graphology. In addition, there is a technology that can be utilized and is very trend in public. That is mobile technology. This research has purpose to build mobile application that can be used for identifying personality of person using graphology. We will apply this application on android. This application will be doing identification of personality based on writing direction, slant of writing, writing width, writing margin, pointed or rounded letter, and space between lines in writing. The handwriting that is used has two lines. This application is capable to identify writing based on the space between line, the writing direction, the slant of the writing, the width of the writing, the margin of writing, and the pointed or rounded letter like identification of the expert from the 25 tested handwritings.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129487073","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}
Nur Ashar Aditiya, Muhammad Rizky Dharmawan, Zaqiatud Darojah, D. Sanggar
{"title":"Fault diagnosis system of rotating machines using Hidden Markov Model (HMM)","authors":"Nur Ashar Aditiya, Muhammad Rizky Dharmawan, Zaqiatud Darojah, D. Sanggar","doi":"10.1109/KCIC.2017.8228583","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228583","url":null,"abstract":"In the industry, maintenance costs can be reduced by early detection and diagnosis. It can also improve the overall equipment efficiency of the machine system. To diagnose the problem is required a diagnosis system with a particular method. The Hidden Markov Model (HMM) method is used because it can determine the parameters that are hidden from the observable parameters. Then, The specified parameters can be used for further analysis. This study, an error diagnostic system was applied on a rotating machinery using the Hidden Markov Model (HMM) analysis based on error recognition. The expected results are improving efficiency of equipment, diagnose faults on industrial machinery so that the maintenance costs can be reduced.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133170434","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}
Muhammad Rizal Prihartadi, A. Fariza, N. R. Mubtadai
{"title":"Desktop computer specification support system using simulated annealing","authors":"Muhammad Rizal Prihartadi, A. Fariza, N. R. Mubtadai","doi":"10.1109/KCIC.2017.8228586","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228586","url":null,"abstract":"Until now the desktop computer is still very popular because it is relatively easy to upgrade and cheap compared to the performance obtained. When building a desktop computer, the specification must be adjusted to how the computer will be used to get optimum performance. For each specification, the selection of the right components is the key to get the desired performance. There are many choices of components that can meet almost all the needs of personal computing. However, choosing the right components is not an easy task for some people especially for those with a limited budget. Based on these problems, we propose a system to help find the optimum desktop computer specification from various components available. To build the specification, we pair a bunch of computer components with certain rules and determine the performance value. We used simulated annealing algorithm to find the optimum specification from many specifications that arise. To make this algorithm able to solve this problem, there is some point that needs to be modified. First, the system searches the greatest energy. Second, the solution modification process needs to fit certain compatibility rules. From the user perspective, the system only receives input in the form of computer usage category and budget. Based on the test that has been done with the expert, the system with simulated annealing algorithm gives a good result with an accuracy of 75.1%.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128991806","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 implementation of data exchange using authenticated attribute-based encryption for environmental monitoring","authors":"Munsyi, Amang Sudarsono, M. A. Rasyid","doi":"10.1109/KCIC.2017.8228564","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228564","url":null,"abstract":"A reliable and efficient security system on the Internet of things era is one of the most required aspects. An information security in the environment monitoring system is very important, the information sent from the wireless sensor network to the Data Center must be completely secure and only users with the access right can read the contents of the information. To secure the contents of the data, then ciphertext policy attribute-based encryption (CP-ABE) is one of solution for the data security. The data sent from the Data Center will be encrypted using attributes attached to the previously registered user. The data can be decrypted if and only if the attributes of the users are appropriate to the existing policy rules on the ciphertext. The importance of maintaining the authenticity of data on a system, it is necessary to add a security system to protect from users who perform illegal acts. In this paper, we discuss the security mechanism with revocation user, we use the attributes in the CP-ABE who can be updated if the user is doing the illegal actions of the system. By adding an authentication feature using a timestamp digital signature Rivest, Shamir Adleman (RSA) 2048 in a message, it will be a guaranteed the data integrity of information data and no repetition of data transmitted by any particular party.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114045048","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":"Feature selection software development using Artificial Bee Colony on DNA microarray data","authors":"Wildan Andaru, I. Syarif, Ali Ridho Barakbah","doi":"10.1109/KCIC.2017.8228447","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228447","url":null,"abstract":"DNA Microarray data is a high-dimensional data that enables the researchers to analyze the expression of many genes in a single reaction quickly and in an efficient manner. Its characteristics such as small sample size, class imbalance, and data complexity causes it difficult to classified. Feature selection is a process that automatically selects features that are most relevant to the predictive modeling in dataset. This research aims at investigating, implementing, and analyzing a feature selection method using the Artificial Bee Colony (ABC) approach. The result is compared with other evolution algorithms, which is Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The result is that feature selection using ABC has a better result at classification using k-Nearest Neighbor (k-NN) and Decision Tree (DT), but has a slightly higher fracture of features compared to GA and PSO algorithms.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122358192","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}
Entin Martiana Kusumaningtyas, Ali Ridho Barakbah, A. Hermawan, S. Candra
{"title":"Auto cropping for application of heart abnormalities detection through Iris based on mobile devices","authors":"Entin Martiana Kusumaningtyas, Ali Ridho Barakbah, A. Hermawan, S. Candra","doi":"10.1109/KCIC.2017.8228572","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228572","url":null,"abstract":"As the WHO says, heart disease is a main cause of death and examining it by current methods in hospitals is not cheap. Iridology is one of the most popular alternative ways to detect the condition of organs. Iridology is a science field that makes a health non-expert or practitioner to study signs in the iris that are capable of showing abnormalities in the body, including basic genetics, toxin deposition, dam circulation, and other weaknesses. Research on computer iridology has been done before. One is about the computer's iridology system to detect heart conditions. Some previous works used manual cropping to get iris images and auto cropping on PC. This research presents auto cropping on iris images base on mobile devices. There are several stages such as capture eye base on target, pre-processing, cropping, segmentation, feature extraction and classification using Thresholding algorithms. The system we proposed was tested at Mugi Barokah Clinic Surabaya. This research resulted in an experimental using 20 data indicating that the auto cropping results is 45% success for cropping process and all the success cropping brings accuracy for classification.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116797336","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}
Dyah Ceni Adelina, R. Sigit, T. Harsono, M. Rochmad
{"title":"Identification of diabetes in pancreatic organs using iridology","authors":"Dyah Ceni Adelina, R. Sigit, T. Harsono, M. Rochmad","doi":"10.1109/KCIC.2017.8228573","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228573","url":null,"abstract":"Diabetes is a general disease often infected in humans. Many ways to detect diabetes, one of them is checking blood pressure, but this way is not effective, because it takes blood first and take a lot of time. Iridology is one way analysis health based on the iris. Therefore we need a tool used to identify pancreatic damage as an indication of diabetes through iridology. Load image is the first step to identify pancreatic organs based on the iris. The eye image that we used as the input system comes from the eye clinic database. The next step is adaptive median filtering used in the process preprocessing to reduce the noise on the image. After that the next step is segmentation process using hough circle transform method. The results of segmentation will be normalized and take the Region of interest. ROI will be done feature extraction by using GLCM (Gray Level Co-Occurrence Matrix). To know the condition of pancreas organ using backpropagation method.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133662483","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}
Rendra Budi Hutama, Ali Ridho Barakbah, Afrida Helen
{"title":"Indonesian news auto summarization in infrastructure development topic using 5W+1H consideration","authors":"Rendra Budi Hutama, Ali Ridho Barakbah, Afrida Helen","doi":"10.1109/KCIC.2017.8228596","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228596","url":null,"abstract":"With an average reading speed of 200–500 words per minute, at least human takes 2 to 3 minutes to read and understand one news in online media. The number of news updates on an online media in a few minutes can be a lot and it's time-consuming if a reader has to read the contents of all the news. Reading a summary that represents the main idea of the news can be a solution to save time. This study considers the 5W + 1H element in generating news summaries because this element is important in a news. The single news from online media pages is taken by scanning and grabbing process which is further will be sanitized, then segmentation and tokenizing to break the news into sentences and words. Each sentence classified into multi-label whether it contains 5W + 1H (What, Who, Where, When, Why and/or How) or nothing else by using training data that has been built. Sentences containing 5W + 1H will be selected as summary sentences. Testing of summary results shows the average precision 91%, recall 67% and f-measure 76%.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115823905","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}