Sholiq, Danang Ary Dewangga, A. P. Subriadi, F. A. Muqtadiroh
{"title":"Quality Measurement of Software Based on Characteristics of Functionality, Reliability, and Maintainability","authors":"Sholiq, Danang Ary Dewangga, A. P. Subriadi, F. A. Muqtadiroh","doi":"10.1109/ISRITI.2018.8864449","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864449","url":null,"abstract":"The purpose of this study is to determine the level of quality of software “application of software cost estimation ” which is a product of previous research that will be opened to the public. Testing uses the ISO 9126–1 standard that applies internationally. The ISO standard is chosen because it has complete quality characteristics. The characteristics tested in this study are functionality, reliability, and maintainability. These three characteristics are the factors that most influence the quality of the application. The results of this study are quality measurement values based on ISO 9126–1 and recommendations for improving application quality. After measuring the application/software quality, we know that the characteristics of functionality and reliability are very good, while the maintainability characteristics are still in the bad category. Required to add some features such as to record the activity log, to diagnose the application, and to test features which are installed in the application. Finally, the procedures, methods, and metrics used in this study can be adopted for other software quality testing. Adjustments, as needed, are needed with the condition of the software object being tested.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123132094","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. Fahmi, E. Sugiarto, Agus Winarno, S. Sumpeno, M. Purnomo
{"title":"Waqf Lands Assets Classification Based On Productive Value For Business Development Using Naïve Bayes","authors":"A. Fahmi, E. Sugiarto, Agus Winarno, S. Sumpeno, M. Purnomo","doi":"10.1109/ISRITI.2018.8864489","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864489","url":null,"abstract":"‘Waqf’ is an act of giving some of the assets owned for worship purpose in Islam and social charity. Land is one of many assets used as ‘waqf’ objects which can be used as a valuable asset for worship and economy. There are many cases that make ‘waqf’ lands allotment not suitable for business development. A ‘waqf’ land allotment classifier to discriminate assets which were productive and not productive for business development was proposed in this study. The classifier was built using Naïve Bayes algorithm. Seven important attributes of waqf asset data were analyzed, and then the attributes were used to discriminate productive and not productive assets. The dataset contained 57 ‘waqf’ lands divided into 80% for training data and 20% for testing data. The experiment results showed that the proposed method can achieve accuracy at 93% for training data and 91% for testing data.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123803832","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":"Robustness of Steganography Image Method Using Dynamic Management Position of Least Significant Bit (LSB)","authors":"R. Isnanto, Risma Septiana, A. F. Hastawan","doi":"10.1109/ISRITI.2018.8864439","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864439","url":null,"abstract":"Steganography is used to hide information in the process of data communication. The data that can be hidden are either the texts or images. Hiding image in an image means that the pixel values of the secret image will be embedded in an image called cover image. The challenge is that the cover image should not be damaged even if the embedding process changes the pixel values. Steganography methods have various ways to embed a secret message hidden. This research will use one of the methods called the Least Significant Bit (LSB) and the method will be combined with a dynamic management position of placement of the message. The aim of combining method is to make the robustness method that can be implemented using various size and type of hidden images as the secret message. The robustness method will ensure that the embedded process result called stego-image should be reversible correctly. Measurement of damaging image uses the parameters of similarity image quality that are Mean Square Error, Peak Signal to Noise Ratio and Root Mean Square Error. The result shows good quality of similarity image and the method can recover the secret image from the image cover.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115083787","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 Batik Image using Grey Level Co-occurrence Matrix Feature Extraction and Correlation Based Feature Selection","authors":"Nani Sulistianingsih, I. Soesanti, Rudy Hartanto","doi":"10.1109/ISRITI.2018.8864237","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864237","url":null,"abstract":"Batik is a cultural heritage that has become part of Indonesian society. Batik has a variety of patterns and motifs. Each region has varieties of motifs in terms of color, texture and production techniques. This study discusses the feature selection method for classification of batik image into Kawung, Lereng, Nitik and Tambal. Selection of the right features by eliminating redundant features can result in higher accuracy. Another important step is feature extraction. This research applies the Gray Level Co-occurrence Matrix feature extraction to extract features in the image of batik. The total features obtained by extracting batik images using GLCM are 20 features. From 20 features, CFS is able to reduce 70% of irrelevant features. The results showed that the classification of batik using Backpropagation resulted in an accuracy of 83% and the classification using the K-Nearest Neighbor method was 67%.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129815898","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}
Sholiq, A. P. Widodo, Teguh Sutanto, A. P. Subriadi
{"title":"Effort Distribution per Activities for Small Software Development Project Uses Prototype Model","authors":"Sholiq, A. P. Widodo, Teguh Sutanto, A. P. Subriadi","doi":"10.1109/ISRITI.2018.8864434","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864434","url":null,"abstract":"In this study, we investigated the effort distribution for small-scale software development projects developed using prototype models. An effort is a work done to complete a software project that effort is measured uses a person-month. An estimated effort can be obtained using algorithmic or non-algorithmic estimation techniques. Effort distribution that is expressed in percentage is used distributing effort estimated into effort per activities of software development project. In addition to the distribution of effort per activity, this research also obtains the distribution of effort per role/position of the software development team. Knowledge of effort distribution per activity or per role is used to distribute activities obtained from estimates to in effort per activity. By knowing the effort per activity, the cost per activity can be obtained by multiplying effort per activity with the pay rate per activity. Thus, the cost of project development is achieved by summing the costs per activity. Therefore, this study is important to support estimation techniques of the software development project.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128479322","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 Childhood Diseases with Fever Using Fuzzy K-Nearest Neighbor Method","authors":"R. Putra, S. Mulyati","doi":"10.1109/ISRITI.2018.8864475","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864475","url":null,"abstract":"Fever or pyrexia is a condition when the body temperature rises above the average. This may occur due to viral or bacterial infection of the body. In addition, fever is the main symptom of diseases such as dengue fever, typhoid fever, diarrhea, gastroenteritis, measles, pneumonia, pharyngitis, and bronchitis. These diseases have similar symptoms, causing difficulty to distinguish them. In fact, the symptoms of diseases are usually recorded in a medical record document.Medical records can be categorized in order to ease diagnosis. The technique to categorize based on certain characteristics to several classes is called classification. Classification can categorize textual data which are first converted into numerical data so that the classification process can generate results. Fuzzy K-Nearest Neighbor is one classification technique that measures the distance between training and testing data, which then put them into a fuzzy set. This study developed a classification system for childhood diseases with fever using Fuzzy K-Nearest Neighbor based on textual medical record documents.The test results of the classification system showed an accuracy of 83.3% in the dengue fever and pneumonia data with a comparison of training and testing data of 80: 20, K value of 10, and M value of 2. Thus, it can be concluded that Fuzzy K-Nearest Neighbor classification system can be used as a solution to the classification of childhood diseases with fever.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124624508","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}
Mustofa Alisahid Almahfud, Robert Setyawan, C. A. Sari, D. Setiadi, E. H. Rachmawanto
{"title":"An Effective MRI Brain Image Segmentation using Joint Clustering (K-Means and Fuzzy C-Means)","authors":"Mustofa Alisahid Almahfud, Robert Setyawan, C. A. Sari, D. Setiadi, E. H. Rachmawanto","doi":"10.1109/ISRITI.2018.8864326","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864326","url":null,"abstract":"This study proposes a segmentation method in human brain MRI images by using a combination of two K-Means and Fuzzy C-Means (FCM) grouping methods to detect brain tumors. K-Means can detect optima and local outliers well and quickly because it is more sensitive to color differences. But the results of the K-Means cluster can be different each time the program starts. To overcome this problem, the results of K-means are clustered again with FCM to classify the convex shape based on the edge so that the cluster results better and the calculation process becomes lighter. Morphology and noise removal processes are also proposed at the preprocessing stage to improve accuracy. In this way the detection results are more effective and accurate with a faster calculation process. Based on the experimental results on 62 brain MRI images obtained an accuracy of 91.94%. This result is far more accurate than the K-Means or FCM methods and also the reverse FCM-K-Means method.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124699817","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 Hybrid SC-FCM Clustering with Cluster Validity Index","authors":"Victor Utomo, Dhendra Marutho","doi":"10.1109/ISRITI.2018.8864459","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864459","url":null,"abstract":"Clustering classifies data into groups based on the similarity of each element of data. In order to validate the cluster, cluster validity index is introduced. Hybrid SC-FCM (Subtractive Clustering-Fuzzy C-Means) clustering method is a clustering technique to overcome the weakness of the FCM (Fuzzy C-Means) clustering. While the hybrid SC-FCM is a promising method, no validity measurement on the resulted cluster has been done. This research measures the cluster validity index of Hybrid SC-FCM method. The cluster validity indices used in the research are partition coefficient, partition entropy, and Xen Beni Index. The research shows mix results. Even though the Hybrid SC-FCM method fails to find the best number of clusters as suggested, it shows that hybrid SC-FCM able to exceed the traditional FCM method in providing initial centroids.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130345428","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":"Mathematical Modeling and Simulation of Missile Firing Impact Force on Warship","authors":"Heri Purnawan, T. Asfihani, D. Adzkiya, Subchan","doi":"10.1109/ISRITI.2018.8864451","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864451","url":null,"abstract":"In this paper, we propose a 3-DOF ship model with a constant surge velocity. The development of 3-DOF ship model is done by considering the impact force of missile firing as a system’s disturbance. We conduct two scenarios to study the behavior of the model. Scenario 1 is simulated on both nonlinear and linear system model with different rudder angle input. The simulation results show that both nonlinear and linear system model can describe the results of turning cycle, although there are some differences in advanced, tactical diameter and transfer. Scenario 2 is simulated with different missile disturbances and fixed rudder angle input. The simulation results of this scenario indicate that missile with a greater impact force can produce greater influence than missiles with small impact force, especially on position coordinate of the ship.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130404415","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":"Decisions Support System to determine Anxiety Levels based on Fuzzy Preference Relations","authors":"Kahfi Yordan, E. Wahyuni, Sri Kusumad","doi":"10.1109/ISRITI.2018.8864333","DOIUrl":"https://doi.org/10.1109/ISRITI.2018.8864333","url":null,"abstract":"Problems in a family daily lives consists many things, one of them is family harmonies, harmonies in a family created if there is a firm and balanced relationship in everyday life. If there are any problems then it can result in bad effects in family harmony such as anxieties in oneself. Longer anxiety can cause depressions if it’s not handled by the experts. It is crucial to give a proper treatment and getting to know what cause of the anxiety in the first place. A psychologist can use Fuzzy Preference Relations method to determine what cause of the anxiety in a person. The purpose of the method is to minimize each psychologists opinion of how to determine if the anxiety levels so it can conclude the optimal threshold to determine the relation factor. The client needs to answer The Taylor Manifest Anxiety Scale questionnaire first so that the psychologist can diagnose of the anxiety level and determine the cause. The results will be given for the client with the information of the cause and the level of anxieties by the system.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124255826","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}