Pengaruh Cluster Emiten terhadap Return Saham JSX Berbasis Parameter Rasio Analisa Fundamental

https://doi.org/10.35912/jakman.v2i4.294
Published: Jul 9, 2021

Abstract:

Purpose: This research aimed to find the effect of cluster techniques in determining stock selection to maximize return and minimize risk in the stock market.

Research Methodology: The methodology consists of two of several algorithmic approaches of the clustering method to find hidden patterns in a group of datasets, i.e., Partitioning clusters (k-means) defined by the dataset object and its central area, and hierarchical clusters that group data through varying scales to be implemented into cluster trees or dendrogram. Dataset summary analysis of the fundamental ratio of stocks in the study was obtained from IDX stock data.

Results: This study's classification has been obtained that consists of three zones: green, blue and red zone. The significance obtained provides an alternative form of stock categorization, creating an investment decision support system based on Cluster Analysis, the search for correlations and patterns between ratios of the Financial Statements as complementary tools of Investment Risk Management.

Limitations: This research uses only two clustering algorithm methods to analyze the effect of clustering in maximizing return and minimizing risk and only used variables of financial reports for the company listed on the Indonesia Stock Exchange.

Contribution: The risk management portfolio is a crucial part of being analyzed for investors and management to improve financial performance. As a complement to decision support, the risk management systems have to be analyzed based on cluster analysis and subsequent data mining to know the potential stock valuation in the market.

Keywords:
1. Stock
2. Partitioning Clusters
3. Hierarchical Clusters
4. Financial Statements
5. Fundamental Analysis Ratio
Authors:
1 . Berlian Karlina
2 . Ario Menak Sanoyo
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How to Cite
Karlina, B., & Sanoyo, A. M. (2021). Pengaruh Cluster Emiten terhadap Return Saham JSX Berbasis Parameter Rasio Analisa Fundamental . Jurnal Akuntansi, Keuangan, Dan Manajemen, 2(4), 279–291. https://doi.org/10.35912/jakman.v2i4.294
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Issue & Section
Vol. 2 No. 4 (2021): September
Articles
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  1. Aleksandar Vasilev. (2020). How Quantitatively Important is Public Investment for Both Business Cycle Fluctuations and Output Growth in Bulgaria (1999–2018)?. Macroeconomics and Finance in Emerging Market Economies.
  2. Bini B. S, Tessy Mathew. (2016). Clustering and Regression Techniques for Stock Prediction. Procedia Technology 24, 1248 – 1255.
  3. Dragan Radojevic, Boris Delibaši?, Ksenija Mandic. (2015). An application of the Integrated IBA-TOPSIS Model in supplier selection. International Journal of Decision Support System Technology 7(1), 15-30.
  4. Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster Analysis (5 Ed.). Hoboken, NJ, United States: John Wiley & Sons.
  5. Hery. (2015). Analisis Laporan Keuangan. Edisi 1. Yogyakarta: Center For Academic Publishing Services.
  6. Hery. (2017). Auditing dan Asurans. Jakarta. Grasindo
  7. Irham Fahmi. (2018). Pengantar Manajemen Keuangan. Bandung. Alfabeta.
  8. Kasmir. (2016). Analisis Laporan Keuangan. Jakarta: Raja Grafindo Persada.
  9. Munawir, S. (2004). Analisa Laporan Keuangan. Edisi IV, Liberty, Yogjakarta
  10. M. Sholihun (2019). Pengaruh Likuiditas terhadap Nilai Perusahaan melalui Struktur Modal pada Perusahaan Manufaktur Indonesia. Jurnal Mu’allim, 1(2).
  11. E-ISSN: 2655-8912 P-ISSN: 2655-8939
  12. Santosa, B. (2007). Data Mining Terapan dengan Matlab. Salemba Empat. hal 8. 2. Indonesia Graha Ilmu.
  13. Santosa, B. (2007). Data Mining Teknik Pemanfaatan Data untuk Keperluan Bisnis. Indonesia Graha Ilmu.
  14. Sugiyono. (2018). Metode Penelitian Kuantitatif. Bandung. Alfabeta.
  15. Tambunan, A. P. (2008). Menilai Harga Wajar Saham (Stock Valuation). Jakarta Elex Media Komputindo.