CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE
The main information of this research is the transformation of the correlation coefficient value for stock price into the distance. It is done to create a representation in metric space that can be used in cluster analysis on the correlation network, which is a dynamic network. The dynamic network i...
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Universitas Pattimura
2025-04-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15328 |
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| author | Mokhammad Ridwan Yudhanegara Edwin Setiawan Nugraha Sisilia Sylviani Karunia Eka Lestari Ebenezer Bonyah |
| author_facet | Mokhammad Ridwan Yudhanegara Edwin Setiawan Nugraha Sisilia Sylviani Karunia Eka Lestari Ebenezer Bonyah |
| author_sort | Mokhammad Ridwan Yudhanegara |
| collection | DOAJ |
| description | The main information of this research is the transformation of the correlation coefficient value for stock price into the distance. It is done to create a representation in metric space that can be used in cluster analysis on the correlation network, which is a dynamic network. The dynamic network is generated from the weighted edges in the form of distances in each period. Finding the cluster members of the network can be analyzed using a simple technique called a minimum spanning tree. The central cluster member is the vertex betweenness. Vertex betweenness represents banking companies with a high degree of proximity and correlation. It means that the banks that are members of the central cluster are banks with high investment value. Clustering based on betweenness centrality in the case study of stock price correlation becomes useful when transforming the value of the correlation coefficient to distance. The effort to build a network with the edge weight being the distance makes the minimum spanning tree a simple, valuable method for cluster analysis on bank stock prices. In particular, the benefit to investors, i.e., it can reveal which assets are closely correlated, indicating that they may respond to market events in a similar way and make decisions in stock purchases |
| format | Article |
| id | doaj-art-b97ffd80388d498b95d2a2cf90b10029 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-b97ffd80388d498b95d2a2cf90b100292025-08-20T03:41:56ZengUniversitas PattimuraBarekeng1978-72272615-30172025-04-011921109111810.30598/barekengvol19iss2pp1109-111815328CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACEMokhammad Ridwan Yudhanegara0Edwin Setiawan Nugraha1Sisilia Sylviani2Karunia Eka Lestari3Ebenezer Bonyah4Department of Mathematics Education, Faculty of Teacher Training and Education, Universitas Singaperbangsa Karawang, IndonesiaDepartment of Actuarial Science, Faculty of Business, President University, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, IndonesiaDepartment of Mathematics Education, Faculty of Teacher Training and Education, Universitas Singaperbangsa Karawang, IndonesiaDepartment of Mathematics Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, GhanaThe main information of this research is the transformation of the correlation coefficient value for stock price into the distance. It is done to create a representation in metric space that can be used in cluster analysis on the correlation network, which is a dynamic network. The dynamic network is generated from the weighted edges in the form of distances in each period. Finding the cluster members of the network can be analyzed using a simple technique called a minimum spanning tree. The central cluster member is the vertex betweenness. Vertex betweenness represents banking companies with a high degree of proximity and correlation. It means that the banks that are members of the central cluster are banks with high investment value. Clustering based on betweenness centrality in the case study of stock price correlation becomes useful when transforming the value of the correlation coefficient to distance. The effort to build a network with the edge weight being the distance makes the minimum spanning tree a simple, valuable method for cluster analysis on bank stock prices. In particular, the benefit to investors, i.e., it can reveal which assets are closely correlated, indicating that they may respond to market events in a similar way and make decisions in stock purchaseshttps://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15328dynamic networkeuclidean distancestock pricevertex betweenness |
| spellingShingle | Mokhammad Ridwan Yudhanegara Edwin Setiawan Nugraha Sisilia Sylviani Karunia Eka Lestari Ebenezer Bonyah CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE Barekeng dynamic network euclidean distance stock price vertex betweenness |
| title | CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE |
| title_full | CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE |
| title_fullStr | CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE |
| title_full_unstemmed | CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE |
| title_short | CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE |
| title_sort | clustering based on betweenness centrality in period transformation of correlation coefficient value into distance in matric space |
| topic | dynamic network euclidean distance stock price vertex betweenness |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15328 |
| work_keys_str_mv | AT mokhammadridwanyudhanegara clusteringbasedonbetweennesscentralityinperiodtransformationofcorrelationcoefficientvalueintodistanceinmatricspace AT edwinsetiawannugraha clusteringbasedonbetweennesscentralityinperiodtransformationofcorrelationcoefficientvalueintodistanceinmatricspace AT sisiliasylviani clusteringbasedonbetweennesscentralityinperiodtransformationofcorrelationcoefficientvalueintodistanceinmatricspace AT karuniaekalestari clusteringbasedonbetweennesscentralityinperiodtransformationofcorrelationcoefficientvalueintodistanceinmatricspace AT ebenezerbonyah clusteringbasedonbetweennesscentralityinperiodtransformationofcorrelationcoefficientvalueintodistanceinmatricspace |