Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979818
A. Alwadain
Despite the growing interest in Enterprise Architecture (EA) over the last decade, many organizations still view EA as an abstract instrument that demands substantial investment, with hard to prove benefits. In fact, some organizations doubt the success of their EA initiatives due to the difficulties in justifying their EA-related expenditure. EA-benefits research often presents implicit perspectives of EA-benefits realization processes and there is no single thorough view of how EA might deliver value to organizations. Thus, this study endeavors to develop an EA-benefits realization process model using an established theoretical foundation. It uses the process theory of “how IT creates business value” to apprehend the focal elements of the formula for turning EA investment into organizational value. The contribution of this study is the development of a conceptual EA-benefits realization process model. The model conveys that EA investment results in an increased organizational performance through the realization of three interconnected processes. It connects and unpacks the EA-benefits realization process going from an early EA investment toward a preferred organizational performance using three processes: the conversion process, the use process, and the competitive process.
{"title":"How Enterprise Architecture Creates Business Value: A Theoretical Model","authors":"A. Alwadain","doi":"10.1109/ICACSIS47736.2019.8979818","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979818","url":null,"abstract":"Despite the growing interest in Enterprise Architecture (EA) over the last decade, many organizations still view EA as an abstract instrument that demands substantial investment, with hard to prove benefits. In fact, some organizations doubt the success of their EA initiatives due to the difficulties in justifying their EA-related expenditure. EA-benefits research often presents implicit perspectives of EA-benefits realization processes and there is no single thorough view of how EA might deliver value to organizations. Thus, this study endeavors to develop an EA-benefits realization process model using an established theoretical foundation. It uses the process theory of “how IT creates business value” to apprehend the focal elements of the formula for turning EA investment into organizational value. The contribution of this study is the development of a conceptual EA-benefits realization process model. The model conveys that EA investment results in an increased organizational performance through the realization of three interconnected processes. It connects and unpacks the EA-benefits realization process going from an early EA investment toward a preferred organizational performance using three processes: the conversion process, the use process, and the competitive process.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132862371","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979769
Vidya Qoriah Putri, M. R. Shihab, A. Hidayanto
Sriwijaya University aims to utilize e-learning within lecture activities. However, there is grave lack of interest amongst lecturers in using e-learning. To achieve higher e-learning usage, it is imperative to understand the factors that inhibit interest among university lecturers in using e-learning. Such factors were analyzed using the SQB theory and the UTAUT models. The data were gathered using questionnaires and were analyzed statistically using PLS-SEM. The results showed that the lack of computer self-efficacy and lack of organizational support encourage inertia, while lack of individuals’ experience with computers and lack of resources were not significantly towards inertia. Inertia was shown to negatively affect behavioral beliefs, thus indirectly reducing the intention to adopt e-learning. Performance expectancy and effort expectancy proved to have a positive effect on user intentions to use e-learning.
{"title":"Does Inertia Effect E-Learning System Acceptance Among University Lecturers? Insights from Sriwijaya University","authors":"Vidya Qoriah Putri, M. R. Shihab, A. Hidayanto","doi":"10.1109/ICACSIS47736.2019.8979769","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979769","url":null,"abstract":"Sriwijaya University aims to utilize e-learning within lecture activities. However, there is grave lack of interest amongst lecturers in using e-learning. To achieve higher e-learning usage, it is imperative to understand the factors that inhibit interest among university lecturers in using e-learning. Such factors were analyzed using the SQB theory and the UTAUT models. The data were gathered using questionnaires and were analyzed statistically using PLS-SEM. The results showed that the lack of computer self-efficacy and lack of organizational support encourage inertia, while lack of individuals’ experience with computers and lack of resources were not significantly towards inertia. Inertia was shown to negatively affect behavioral beliefs, thus indirectly reducing the intention to adopt e-learning. Performance expectancy and effort expectancy proved to have a positive effect on user intentions to use e-learning.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132874467","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979872
Farhan Anwar, S. Fadhilah, H. Santoso
This study aims to evaluate of Forest: Stay Focus, a self-control application that use gamification as their main concept of the application, according to factors affecting intention to use the application (playability). Factors affecting intention to use the application used in this study are playability factors which contain game usability (GU), gameplay (GP), and game multiplayer (MP). After participants use Forest for about a week, the evaluation is conducted with contextual interview and focus group discussion (FGD). Data were analyzed using affinity diagram, Bartle ’s test of gaming style, and also codification. The result shows that Forest version 4.7.1 has 16 playability issue. This study also give 8 design ecommendation based on the problem found in evaluation process.
{"title":"Playability Evaluation on Self-Control Application with Gamification Concept: Case Study Forest","authors":"Farhan Anwar, S. Fadhilah, H. Santoso","doi":"10.1109/ICACSIS47736.2019.8979872","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979872","url":null,"abstract":"This study aims to evaluate of Forest: Stay Focus, a self-control application that use gamification as their main concept of the application, according to factors affecting intention to use the application (playability). Factors affecting intention to use the application used in this study are playability factors which contain game usability (GU), gameplay (GP), and game multiplayer (MP). After participants use Forest for about a week, the evaluation is conducted with contextual interview and focus group discussion (FGD). Data were analyzed using affinity diagram, Bartle ’s test of gaming style, and also codification. The result shows that Forest version 4.7.1 has 16 playability issue. This study also give 8 design ecommendation based on the problem found in evaluation process.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133835598","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979998
Femilia Putri Mayranti, A. H. Saputro, W. Handayani
Phenolic compounds are one of the secondary metabolites in vegetation. In general, total phenolic content can be measured using a biological approach that requires some preparation time and destructive. In this study, total phenolic content was predicted using Visible Near-Infrared (VNIR) Imaging approach. VNIR analysis in the spectral range of 400-1000 nm was used to predict the total phenolic content of velvet apple leaf non-destructively. Spectral features from samples are calculated based on the average reflectances area of leaves with a spatial dimension of 20×20 pixels in 224 spectral features. The optimal feature selection was performed using the Decision Tree (DT) method. Decision Tree Regression (DTR) algorithm was applied to predict measured values based on spectral features. Sample data evaluated with cross-validation to calculated system perform. The best performance of prediction system which has 30 optimal wavelength band with the determination coefficient (R2) of 0.92 and root mean square of the relative error (RMSE) of 3.48 in predicting the total phenolic content in a Velvet apple leaf.
酚类化合物是植物次生代谢产物之一。一般来说，总酚含量可以用生物学方法测量，需要一些准备时间和破坏性。本研究采用可见光近红外(VNIR)成像方法预测总酚含量。采用400 ~ 1000 nm紫外近红外光谱法对丝绒苹果叶片总酚含量进行了无损预测。基于224个光谱特征中空间维度为20×20像素的叶片的平均反射率面积，计算样品的光谱特征。使用决策树(DT)方法进行最优特征选择。采用决策树回归(Decision Tree Regression, DTR)算法，基于光谱特征对测量值进行预测。通过交叉验证评估样本数据以计算系统性能。结果表明，30个最优波段的预测系统对丝绒苹果叶片总酚含量的预测效果最佳，其决定系数(R2)为0.92，相对误差(RMSE)的均方根为3.48。
{"title":"Wavelength Selection of Persimmon Leafusing Decision Tree Method in Visible Near-Infrared Imaging","authors":"Femilia Putri Mayranti, A. H. Saputro, W. Handayani","doi":"10.1109/ICACSIS47736.2019.8979998","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979998","url":null,"abstract":"Phenolic compounds are one of the secondary metabolites in vegetation. In general, total phenolic content can be measured using a biological approach that requires some preparation time and destructive. In this study, total phenolic content was predicted using Visible Near-Infrared (VNIR) Imaging approach. VNIR analysis in the spectral range of 400-1000 nm was used to predict the total phenolic content of velvet apple leaf non-destructively. Spectral features from samples are calculated based on the average reflectances area of leaves with a spatial dimension of 20×20 pixels in 224 spectral features. The optimal feature selection was performed using the Decision Tree (DT) method. Decision Tree Regression (DTR) algorithm was applied to predict measured values based on spectral features. Sample data evaluated with cross-validation to calculated system perform. The best performance of prediction system which has 30 optimal wavelength band with the determination coefficient (R2) of 0.92 and root mean square of the relative error (RMSE) of 3.48 in predicting the total phenolic content in a Velvet apple leaf.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"120 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133136506","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979851
Ardiansyah, R. Ferdiana, A. E. Permanasari
Software development effort prediction was an important stages in project planning. Poor prediction would lead to project failure, losing tenders and reduced profits. Several studies have improved Use Case Points as the effort prediction model using regression analysis. However, evaluation performance on the prediction models were biased and produce an asymmetric error distribution. Moreover, the dataset used were primarily from industrial, and less from universities. This study aims to investigate the performance of the regression model in terms of software development effort prediction based on Use Case Points using standardized accuracy (SA) and effect size (Δ) as the evaluation measurement. From the experiment results, regression model yielded 92%-0.64, 96%-1.86, and 69%-0.53 in term of SA and (Δ) over dataset DS1, DS3, and DS4, respectively. Experiment results shows that regression model yielded the best accuracy compared with the Karner model over three dataset. In the future, our results maybe used in development of effort prediction framework for calculating software project costs.
{"title":"Use Case Points based software effort prediction using regression analysis","authors":"Ardiansyah, R. Ferdiana, A. E. Permanasari","doi":"10.1109/ICACSIS47736.2019.8979851","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979851","url":null,"abstract":"Software development effort prediction was an important stages in project planning. Poor prediction would lead to project failure, losing tenders and reduced profits. Several studies have improved Use Case Points as the effort prediction model using regression analysis. However, evaluation performance on the prediction models were biased and produce an asymmetric error distribution. Moreover, the dataset used were primarily from industrial, and less from universities. This study aims to investigate the performance of the regression model in terms of software development effort prediction based on Use Case Points using standardized accuracy (SA) and effect size (Δ) as the evaluation measurement. From the experiment results, regression model yielded 92%-0.64, 96%-1.86, and 69%-0.53 in term of SA and (Δ) over dataset DS1, DS3, and DS4, respectively. Experiment results shows that regression model yielded the best accuracy compared with the Karner model over three dataset. In the future, our results maybe used in development of effort prediction framework for calculating software project costs.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125014490","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}
Pub Date : 2019-10-01DOI: 10.1109/icacsis47736.2019.8979863
{"title":"ICACSIS 2019 Welcome Message from General Chair","authors":"","doi":"10.1109/icacsis47736.2019.8979863","DOIUrl":"https://doi.org/10.1109/icacsis47736.2019.8979863","url":null,"abstract":"","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129113384","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979892
M. R. Diansyah, W. Kusuma, Annisa
Significant protein is an important protein needed by the body for growth. Protein disorders can cause organ diseases or dysfunction. In carrying out their functions, proteins interact with each others to form protein-protein interaction (PPI) networks. To find the most important protein in a network, centrality measures can be used with various criteria according to the parameter specified. This study uses skyline query, an algorithm for finding non-dominated data, to get optimal results for problems with various criteria. Some centrality measures are used as attributes to represent the PPI network features. The aim of this study is to find significant proteins of Parkinson, one of the fastest growing diseases in the world. The results find 14 proteins, according to the literature, 12 of them are related Parkinson Disease. These proteins are PARK2, SNCA, ATP13A2, TP53, MAPT, FYN, HSF1, DRD2, VEGFA, AKT1, MPO, and SLC18A2.
{"title":"Analysis of Protein-Protein Interaction Using Skyline Query on Parkinson Disease","authors":"M. R. Diansyah, W. Kusuma, Annisa","doi":"10.1109/ICACSIS47736.2019.8979892","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979892","url":null,"abstract":"Significant protein is an important protein needed by the body for growth. Protein disorders can cause organ diseases or dysfunction. In carrying out their functions, proteins interact with each others to form protein-protein interaction (PPI) networks. To find the most important protein in a network, centrality measures can be used with various criteria according to the parameter specified. This study uses skyline query, an algorithm for finding non-dominated data, to get optimal results for problems with various criteria. Some centrality measures are used as attributes to represent the PPI network features. The aim of this study is to find significant proteins of Parkinson, one of the fastest growing diseases in the world. The results find 14 proteins, according to the literature, 12 of them are related Parkinson Disease. These proteins are PARK2, SNCA, ATP13A2, TP53, MAPT, FYN, HSF1, DRD2, VEGFA, AKT1, MPO, and SLC18A2.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128463128","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979981
Yulianto Budi Prabowo, D. I. Sensuse, Sofian Lusa
College as an educational institution has an obligation to organize education, research, and community service. Previous studies have mentioned that college problems related to lack of knowledge sharing, access to scientific resources, and collaboration indicate the need of knowledge management (KM). This study aims to determine the level of readiness of STIS Polytechnic of Statistics (Polstat STIS) in implementing KM as well as providing recommendations to improve its readiness. The KM readiness framework is validated by experts and weighted with Analytic Hierarchy Process (AHP). Questionnaires are distributed to lecturers and staffs. The results show that individual and technology aspects are at the ready level, while organization, culture, and physical environment aspects are at the preliminary level. Overall the score of Polstat STIS KM readiness is 71% or at the preliminary level. This means that Polstat STIS has begun to have readiness in implementing KM.
{"title":"Analysis of Knowledge Management Readiness Level: A Case Study in STIS Polytechnic of Statistics","authors":"Yulianto Budi Prabowo, D. I. Sensuse, Sofian Lusa","doi":"10.1109/ICACSIS47736.2019.8979981","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979981","url":null,"abstract":"College as an educational institution has an obligation to organize education, research, and community service. Previous studies have mentioned that college problems related to lack of knowledge sharing, access to scientific resources, and collaboration indicate the need of knowledge management (KM). This study aims to determine the level of readiness of STIS Polytechnic of Statistics (Polstat STIS) in implementing KM as well as providing recommendations to improve its readiness. The KM readiness framework is validated by experts and weighted with Analytic Hierarchy Process (AHP). Questionnaires are distributed to lecturers and staffs. The results show that individual and technology aspects are at the ready level, while organization, culture, and physical environment aspects are at the preliminary level. Overall the score of Polstat STIS KM readiness is 71% or at the preliminary level. This means that Polstat STIS has begun to have readiness in implementing KM.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"9 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120841776","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979779
Citra Glory, Kasiyah, H. Santoso
MOOCs are quite well-known internationally. The development of the MOOC has even taken place rapidly in various countries. However, MOOCs in Indonesia do not seem to be popular or growing. This study aims to evaluate one of MOOC platforms, edX, in the Indonesian context involving 279 participants mostly from Jabodetabek (Jakarta, Bogor, Depok, Tangerang, and Bekasi). The evaluation is only done on free courses, and is based on instructional design and interaction design principles: Gagne’s Nine Levels of Learning and Chickering, Gamson's Seven Principles of Good Practice in Undergraduate Education, and Shneiderman's Eight Golden Rules of the Interface Design. The results of this study indicate that assessing performance (Gagne’s Nine Levels of Learning) and emphasizing time on task (Chickering and Gamson’s Seven Principles of Good Practice in Undergraduate Education) have not been fully implemented by edX. Alternative design recommendations are proposed to improve the edX website based on the principles that have not been met.
{"title":"Evaluation and Recommendations for edX MOOC Platform based on Instructional Design and Interaction Design Principles","authors":"Citra Glory, Kasiyah, H. Santoso","doi":"10.1109/ICACSIS47736.2019.8979779","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979779","url":null,"abstract":"MOOCs are quite well-known internationally. The development of the MOOC has even taken place rapidly in various countries. However, MOOCs in Indonesia do not seem to be popular or growing. This study aims to evaluate one of MOOC platforms, edX, in the Indonesian context involving 279 participants mostly from Jabodetabek (Jakarta, Bogor, Depok, Tangerang, and Bekasi). The evaluation is only done on free courses, and is based on instructional design and interaction design principles: Gagne’s Nine Levels of Learning and Chickering, Gamson's Seven Principles of Good Practice in Undergraduate Education, and Shneiderman's Eight Golden Rules of the Interface Design. The results of this study indicate that assessing performance (Gagne’s Nine Levels of Learning) and emphasizing time on task (Chickering and Gamson’s Seven Principles of Good Practice in Undergraduate Education) have not been fully implemented by edX. Alternative design recommendations are proposed to improve the edX website based on the principles that have not been met.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114743551","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}
Pub Date : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979928
Savira Latifah Hanum, Yanti Rusmawati, Muhammad Arzaki
We construct an ontology design of political parties’ ideological characteristics. The ontology is basically constructed from the concept lattice that has been built regarding the ideo-logical characteristics of the parties. Moreover, we also perform knowledge acquisition from pertinent studies concerning political parties’ identities. We also conduct correctness checking for the resulting ontology to check whether it is correct in accordance with the previously built concept lattice. The analysis results show that the ontology is correct with respect to the canonical basis of implication rules resulted from the associated formal context and concept lattice.
{"title":"Construction of the Ontology Design for Political Parties’ Ideological Characteristics","authors":"Savira Latifah Hanum, Yanti Rusmawati, Muhammad Arzaki","doi":"10.1109/ICACSIS47736.2019.8979928","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979928","url":null,"abstract":"We construct an ontology design of political parties’ ideological characteristics. The ontology is basically constructed from the concept lattice that has been built regarding the ideo-logical characteristics of the parties. Moreover, we also perform knowledge acquisition from pertinent studies concerning political parties’ identities. We also conduct correctness checking for the resulting ontology to check whether it is correct in accordance with the previously built concept lattice. The analysis results show that the ontology is correct with respect to the canonical basis of implication rules resulted from the associated formal context and concept lattice.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131748007","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}
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