The Application of Fuzzy Association Rule on Co-movement Analyze of Indonesian Stock Price

Andi Asrafiani Arafah; Imam Mukhlash

doi:10.1016/j.procs.2015.07.541

The Application of Fuzzy Association Rule on Co-movement Analyze of Indonesian Stock Price

Andi Asrafiani Arafah, Imam Mukhlash

Laboratory of Machine Learning and Big Data

Institut Teknologi Sepuluh Nopember

Research output: Contribution to journal › Conference article › peer-review

14 Citations (Scopus)

Abstract

One type of investments in securities is stock as a sign of ownership for individual or corporation within a company. For making investment strategy and portfolio, investors should pay more attention to the co-movement of the stock price. Several methods can be used to see moving of the stock price, one of them is data mining. In this paper, association rule mining algorithm is used to find the stock movement relationship of inter-company in Indonesia. Fuzzy approach is used as tools to categorize data based on the time and transactions sequence. Experimental results show that association rule method can solve the problems. By using some values of minimum support, some strong association rules among companies can be obtained.

Original language	English
Pages (from-to)	235-243
Number of pages	9
Journal	Procedia Computer Science
Volume	59
DOIs	https://doi.org/10.1016/j.procs.2015.07.541
Publication status	Published - 2015
Event	1st International Conference on Computer Science and Computational Intelligence, ICCSCI 2015 - Jakarta, Indonesia Duration: 24 Aug 2015 → 26 Aug 2015

Keywords

Association Rule
Co-Movement
Data Mining
Fuzzy
Stock Price

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10.1016/j.procs.2015.07.541

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title = "The Application of Fuzzy Association Rule on Co-movement Analyze of Indonesian Stock Price",

abstract = "One type of investments in securities is stock as a sign of ownership for individual or corporation within a company. For making investment strategy and portfolio, investors should pay more attention to the co-movement of the stock price. Several methods can be used to see moving of the stock price, one of them is data mining. In this paper, association rule mining algorithm is used to find the stock movement relationship of inter-company in Indonesia. Fuzzy approach is used as tools to categorize data based on the time and transactions sequence. Experimental results show that association rule method can solve the problems. By using some values of minimum support, some strong association rules among companies can be obtained.",

keywords = "Association Rule, Co-Movement, Data Mining, Fuzzy, Stock Price",

author = "Arafah, {Andi Asrafiani} and Imam Mukhlash",

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T1 - The Application of Fuzzy Association Rule on Co-movement Analyze of Indonesian Stock Price

AU - Arafah, Andi Asrafiani

AU - Mukhlash, Imam

PY - 2015

Y1 - 2015

N2 - One type of investments in securities is stock as a sign of ownership for individual or corporation within a company. For making investment strategy and portfolio, investors should pay more attention to the co-movement of the stock price. Several methods can be used to see moving of the stock price, one of them is data mining. In this paper, association rule mining algorithm is used to find the stock movement relationship of inter-company in Indonesia. Fuzzy approach is used as tools to categorize data based on the time and transactions sequence. Experimental results show that association rule method can solve the problems. By using some values of minimum support, some strong association rules among companies can be obtained.

AB - One type of investments in securities is stock as a sign of ownership for individual or corporation within a company. For making investment strategy and portfolio, investors should pay more attention to the co-movement of the stock price. Several methods can be used to see moving of the stock price, one of them is data mining. In this paper, association rule mining algorithm is used to find the stock movement relationship of inter-company in Indonesia. Fuzzy approach is used as tools to categorize data based on the time and transactions sequence. Experimental results show that association rule method can solve the problems. By using some values of minimum support, some strong association rules among companies can be obtained.

KW - Association Rule

KW - Co-Movement

KW - Data Mining

KW - Fuzzy

KW - Stock Price

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U2 - 10.1016/j.procs.2015.07.541

DO - 10.1016/j.procs.2015.07.541

M3 - Conference article

AN - SCOPUS:84948391082

SN - 1877-0509

VL - 59

SP - 235

EP - 243

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 1st International Conference on Computer Science and Computational Intelligence, ICCSCI 2015

Y2 - 24 August 2015 through 26 August 2015

ER -

The Application of Fuzzy Association Rule on Co-movement Analyze of Indonesian Stock Price

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Keywords

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