2015 International Conference on Data and Software Engineering (ICoDSE)最新文献_第2页

Unit test code generator for lua programming language lua编程语言的单元测试代码生成器

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7437005

Junno Tantra Pratama Wibowo, B. Hendradjaya, Yani Widyani

{"title":"Unit test code generator for lua programming language","authors":"Junno Tantra Pratama Wibowo, B. Hendradjaya, Yani Widyani","doi":"10.1109/ICODSE.2015.7437005","DOIUrl":"https://doi.org/10.1109/ICODSE.2015.7437005","url":null,"abstract":"Software testing is an important step in the software development lifecycle. One of the main process that take lots of time is developing the test code. We propose an automatic unit test code generation to speed up the process and helps avoiding repetition. We develop the unit test code generator using Lua programming language. Lua is a fast, lightweight, embeddable scripting language. It has been used in many industrial applications with focuses on embedded systems and games. Unlike other popular scripting language like JavaScript, Python, and Ruby, Lua does not have any unit test generator developed to help its software testing process. The final product, Lua unit test generator (LUTG), integrated to one of the most popular Lua IDE, ZeroBrane Studio, as a plugin to seamlessly connect the coding and testing process. The code generator can generate unit test code, save test cases data on Lua and XML file format, and generate the test data automatically using search-based technique, genetic algorithm, to achieve full branch coverage test criteria. Using this generator to test several Lua source code files shows that the developed unit test generator can help the unit testing process. It was expected that the unit test generator can improve productivity, quality, consistency, and abstraction of unit testing process.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133245718","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}

引用次数: 5

Personality classification based on Twitter text using Naive Bayes, KNN and SVM 基于朴素贝叶斯、KNN和支持向量机的Twitter文本个性分类

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/icodse.2015.7436992

Bayu Yudha Pratama, R. Sarno

引用次数: 192

Prototype of moving object visualization engine 移动对象可视化引擎的原型

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436994

Yani Widyani, Elia Dolaciho Bangun, Hira Laksmiwati, Rickard Elsen

引用次数: 2

Document clustering using sequential pattern (SP): Maximal frequent sequences (MFS) as SP representation 使用顺序模式(SP)的文档聚类:最大频繁序列(MFS)作为SP表示

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436979

D. Rahmawati, G. A. Putri Saptawati, Yani Widyani

{"title":"Document clustering using sequential pattern (SP): Maximal frequent sequences (MFS) as SP representation","authors":"D. Rahmawati, G. A. Putri Saptawati, Yani Widyani","doi":"10.1109/ICODSE.2015.7436979","DOIUrl":"https://doi.org/10.1109/ICODSE.2015.7436979","url":null,"abstract":"This research proposes an idea to apply Feature Based Clustering (FBC) in document clustering. A huge number of existing documents will be easier to be used if they are clustered into several topics. FBC uses K-Means algorithm to cluster sequential data of features. Features of text document can be presented as sequence of word. In order to be processed as sequential data, features must be extracted from collection of unstructured text documents. Therefore, we need preprocessing tasks to deliver appropriate form of document features. There are two types of sequential pattern using simple form: Frequent Word Sequence (FWS) and Maximal Frequent Sequence (MFS). Both types are appropriate for text data. The difference is in applying the maximum principle in MFS. Therefore, MFS amount from a text document would be less than the amount of its FWS. In this research, we choose maximal frequent sequences (MFS) as feature representation. We proposes framework to conduct FBC using MFS as features. The framework is tested to cluster dataset that is subset of the Twenty News Group Text Data. The result shows that the accuracy of clustering result is affected by the parameter's value, dataset, and the number of target cluster.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128750526","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}

引用次数: 3

A metamodel for disaster risk models 灾害风险模型的元模型

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436964

W. H. Nur, F. N. Azizah, Saiful Akbar

{"title":"A metamodel for disaster risk models","authors":"W. H. Nur, F. N. Azizah, Saiful Akbar","doi":"10.1109/ICODSE.2015.7436964","DOIUrl":"https://doi.org/10.1109/ICODSE.2015.7436964","url":null,"abstract":"As the world faces an increasing number of both natural and social disasters, attempts to support disaster risk reduction are also increasing. Although there is a general rule to calculate the disaster risk on an area based on the components of hazard, vulnerability, and capacity, disaster risk studies result in a number of disaster risk models which present different characteristics in terms of the number of components involved, indicators, and the calculations. This poses a difficulty for disaster analysts to choose the most appropriate model to calculate the disaster risk of an area. Moreover, they often need to adapt the existing models or even to create new models in order to provide the most suitable way of calculating the disaster risks. Therefore, a mechanism that enables the use of different kinds of disaster risk model and the creation of new models is required. This paper presents a metamodel of disaster risk based on a study on a number of disaster risk models used in Indonesia: the BNPB (Badan Nasional Penanggulangan Bencana) disaster risk model, the volcanic disaster risk model using SMART (Simple Multi Attribute Rating Technique) method, and the tidal flooding disaster risk model using fuzzy method. The metamodel is presented in an entity-relationship model. It is basically a spatial data model since the components and indicators for the calculation of disaster risks are always associated to the space on earth. The metamodel is implemented on top of ArcGIS software. Using Phyton Add-in, the software is adapted by adding new functionalities to calculate the disaster risk of an area and to create new disaster risk models.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131167735","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}

引用次数: 1

Preliminary diagnosis of pulmonary tuberculosis using ensemble method 集合法对肺结核的初步诊断

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436993

Rusdah, E. Winarko, Retantyo Wardoyo

{"title":"Preliminary diagnosis of pulmonary tuberculosis using ensemble method","authors":"Rusdah, E. Winarko, Retantyo Wardoyo","doi":"10.1109/ICODSE.2015.7436993","DOIUrl":"https://doi.org/10.1109/ICODSE.2015.7436993","url":null,"abstract":"Tuberculosis (TB) is the oldest human diseases with the highest mortality rates among infectious disease. Indonesia is the fifth highest TB burden country in the world. Diagnosis of TB is difficult, especially in the case of pediatric patients, extrapulmonary TB and smear-negative pulmonary TB. In addition, some of the tuberculosis symptoms have in common not only with lung cancer but also with other diseases. This situation will lead to a delay in the correct diagnosis and exposure to the inappropriate medication. Finally, individuals that receive inadequate treatment are more vulnerable to develop multidrug-resistant tuberculosis. This study aims to model the preliminary diagnosis of pulmonary tuberculosis. Preliminary diagnosis is established only by using patient demographic data, anamnesis, and physical examination. Some experiments were conducted using classification techniques. Some single classifiers such as C4.5, Naive Bayes, Backpropagation and SVM will be compared with ensemble method in order to improve the performance of the model. The data were taken from medical record of tuberculosis patients from Jakarta Respiratory Center. The result showed that ensemble method provided the best accuracy compared to the single classifier.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125848314","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}

引用次数: 9

Multiple MapReduce and derivative projected database: New approach for supporting PrefixSpan scalability 多MapReduce和衍生投影数据库:支持PrefixSpan可扩展性的新方法

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436988

P. N. Sabrina, G. A. Putri Saptawati

引用次数: 5

A domain-specific language for automatic generation of checkers 用于自动生成检查器的特定于领域的语言

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436963

Ryan Ignatius Hadiwijaya, M. M. Inggriani Liem

引用次数: 3

Risk-level assessment system on Bengawan Solo River basin flood prone areas using analytic hierarchy process and natural breaks: Study case: East Java 基于层次分析法和自然断裂的Bengawan Solo河流域洪水易发区风险等级评价体系——以东爪哇为例

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436997

Haris Rahadianto, A. Fariza, Jauari Akhmad Nur Hasim

{"title":"Risk-level assessment system on Bengawan Solo River basin flood prone areas using analytic hierarchy process and natural breaks: Study case: East Java","authors":"Haris Rahadianto, A. Fariza, Jauari Akhmad Nur Hasim","doi":"10.1109/ICODSE.2015.7436997","DOIUrl":"https://doi.org/10.1109/ICODSE.2015.7436997","url":null,"abstract":"Indonesia has the geographical conditions which are particularly vulnerable to disasters, especially floods and climate change. Throughout Indonesia, it is recorded that there are 5,590 main rivers and 600 rivers have the potential to cause flooding among others. One of it is Bengawan Solo River, which is the longest river in Java. The floods that hit the area have resulted in disruption of public health, disrupted economic activity, and damaged urban infrastructure. The phenomenon of floods and their negative impacts in the area of the Bengawan Solo river banks, indicating a condition of the area and the public about the lack of understanding of the characteristics of the hazards, behaviours that lead to degradation of natural resources, and lack of early warning that causes unpreparedness and inability in the face of danger. The purpose of this project is to be able to create an information system that can provide an assessment of the risk management in the Bengawan Solo's flood prone areas that passed in the province of East Java, by building a web-based information system that includes information on threats, vulnerabilities, and capacities, summarized in the disaster risks analysis that integrated with Geographic Information System to provide mapping areas that have high levels of risk in accordance. Based on the factors that are already said above and calculated by Analytical Hierarchy Process, the result of this project is a map with marked regions divided into three levels of risk like High, Medium, and Low using Natural Breaks to divide it. It also, by providing the risk-level for the regions, help the system to assess how much impact and damage that will be hit the risky area and give the recommendation to government and people how to increase the preparedness so it can reduce the damage from flood.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121726712","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}

引用次数: 19

Public facilities recommendation system based on structured and unstructured data extraction from multi-channel data sources 基于多通道数据源的结构化和非结构化数据提取的公共设施推荐系统

2015 International Conference on Data and Software Engineering (ICoDSE) Pub Date : 2015-11-01 DOI: 10.1109/ICODSE.2015.7436995

Alifa Nurani Putri, Saiful Akbar, Wikan Danar Sunindyo

{"title":"Public facilities recommendation system based on structured and unstructured data extraction from multi-channel data sources","authors":"Alifa Nurani Putri, Saiful Akbar, Wikan Danar Sunindyo","doi":"10.1109/ICODSE.2015.7436995","DOIUrl":"https://doi.org/10.1109/ICODSE.2015.7436995","url":null,"abstract":"Nowadays social media data has grown very rapidly by producing a huge amount and variety of data everyday. Those data can be analyzed and processed to deliver useful information especially for public needs. However, most of the data available in social media are unstructured. This paper proposes a recommendation system for public facilities by utilizing both structured and unstructured data gathered from multi-channel data sources. The system uses single-criteria rating, multi-criteria-rating, and text data as the inputs. The challenge is how to handle data variety such that any kind of data from any channel can be integrated. The second challenge is how to extract location-related data from the raw data. There are four data channels used in the system. Three of them are social media channels, i.e. Twitter, Instagram, and Foursquare, while the other is internal data channel built as a part of the system itself. The system deals with three categories of public facility, i.e. park, hospital, and mosque. The whole system consists of two sub systems, i.e. the extractor system including the rating input module and the recommendation system. The recommendation system is implemented as end-user mobile application such that the users are able to use it anytime and anywhere. The system successfully integrate data from different social media channels and in different format to provide users with useful information concerning public facilities in the form of recommendation (rating) and popularity of the facilities. The experiment has shown that above 90% of the data collected from the social media contains location-related information that is useful for further processing. The system has been tested using usability test, and it obtained an average users score 3.9 on a scale of 1 to 5.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125941934","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}

引用次数: 4