Inter-transaction association rule mining in the Indonesia stock exchange market
Stock exchanges have a major impact on Indonesia economy condition as well as on the global economy. Stock activities forecasting is still a challenging issue which is a high demand for stock actors. Therefore, there is still a need to develop an application that is capable to accurately predict dir...
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| creator | Widiputra, H. Pahlevi, B. |
| description | Stock exchanges have a major impact on Indonesia economy condition as well as on the global economy. Stock activities forecasting is still a challenging issue which is a high demand for stock actors. Therefore, there is still a need to develop an application that is capable to accurately predict directions of stock price movement. This research proposes a data mining technique to model relationship between company stocks with other company stocks listed in the Indonesia Stock Exchange in a form of association rules. It is expected that extracted rules can be of a help to predict future stock prices movements with significant level of accuracy. |
| doi_str_mv | 10.1109/URKE.2012.6319532 |
| format | Conference Proceeding |
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Stock activities forecasting is still a challenging issue which is a high demand for stock actors. Therefore, there is still a need to develop an application that is capable to accurately predict directions of stock price movement. This research proposes a data mining technique to model relationship between company stocks with other company stocks listed in the Indonesia Stock Exchange in a form of association rules. 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Stock activities forecasting is still a challenging issue which is a high demand for stock actors. Therefore, there is still a need to develop an application that is capable to accurately predict directions of stock price movement. This research proposes a data mining technique to model relationship between company stocks with other company stocks listed in the Indonesia Stock Exchange in a form of association rules. It is expected that extracted rules can be of a help to predict future stock prices movements with significant level of accuracy.</description><subject>Accuracy</subject><subject>Association Rule Mining</subject><subject>Association rules</subject><subject>Companies</subject><subject>Data mining</subject><subject>Industries</subject><subject>inter-transaction</subject><subject>Prediction algorithms</subject><subject>Stock markets</subject><subject>stock price movement</subject><isbn>9781467314596</isbn><isbn>1467314595</isbn><isbn>1467314609</isbn><isbn>9781467314602</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotUNFKxDAQjIignv0A8SU_0LpJmrZ5lOPU4oEi5_OxTbZ38c5Umgj69xbtPMzOwDALw9i1gEIIMLdvr0-rQoKQRaWE0UqesEtRVrWaCMwpy0zdzF6b6pxlMb7DhEZqWZkL9tKGRGOeRgwRbfJD4BjjYD3-6fHrSPzDBx923Aee9sTb4IZA0SOPabAHTt92j2E3xXA8ULpiZz0eI2XzXbDN_WqzfMzXzw_t8m6dewMpL8k0lZZu4g6oVh2CBetIuFIpo6USstaq7zSIhkTvsLMgNCJ0DiotpFqwm_9aT0Tbz9FP33-28wbqF36rUE4</recordid><startdate>201208</startdate><enddate>201208</enddate><creator>Widiputra, H.</creator><creator>Pahlevi, B.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201208</creationdate><title>Inter-transaction association rule mining in the Indonesia stock exchange market</title><author>Widiputra, H. ; Pahlevi, B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-4e98652d986b0e73ba0c0cde1d433952312753fb5018e1fdabc015aa0bd065123</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Accuracy</topic><topic>Association Rule Mining</topic><topic>Association rules</topic><topic>Companies</topic><topic>Data mining</topic><topic>Industries</topic><topic>inter-transaction</topic><topic>Prediction algorithms</topic><topic>Stock markets</topic><topic>stock price movement</topic><toplevel>online_resources</toplevel><creatorcontrib>Widiputra, H.</creatorcontrib><creatorcontrib>Pahlevi, B.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Widiputra, H.</au><au>Pahlevi, B.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Inter-transaction association rule mining in the Indonesia stock exchange market</atitle><btitle>2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering</btitle><stitle>URKE</stitle><date>2012-08</date><risdate>2012</risdate><spage>149</spage><epage>152</epage><pages>149-152</pages><isbn>9781467314596</isbn><isbn>1467314595</isbn><eisbn>1467314609</eisbn><eisbn>9781467314602</eisbn><abstract>Stock exchanges have a major impact on Indonesia economy condition as well as on the global economy. Stock activities forecasting is still a challenging issue which is a high demand for stock actors. Therefore, there is still a need to develop an application that is capable to accurately predict directions of stock price movement. This research proposes a data mining technique to model relationship between company stocks with other company stocks listed in the Indonesia Stock Exchange in a form of association rules. It is expected that extracted rules can be of a help to predict future stock prices movements with significant level of accuracy.</abstract><pub>IEEE</pub><doi>10.1109/URKE.2012.6319532</doi><tpages>4</tpages></addata></record> |
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| identifier | ISBN: 9781467314596 |
| ispartof | 2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering, 2012, p.149-152 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Accuracy Association Rule Mining Association rules Companies Data mining Industries inter-transaction Prediction algorithms Stock markets stock price movement |
| title | Inter-transaction association rule mining in the Indonesia stock exchange market |
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