Stock Grouping Based on Price Earnings Ratio and Price Book Value Using K-Medoids Algorithm

Oemar Abdillah, Muhammad Stock Grouping Based on Price Earnings Ratio and Price Book Value Using K-Medoids Algorithm. Journal of Information Systems and Informatics.

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Abstract

Investing involves allocating funds to achieve optimal returns by evaluating opportunities and managing risks in asset acquisition. Recently, many news reports have highlighted issues in the Indonesian capital market, such as stock investors using online loan funds for trading, which often leads to debt. This research aims to apply the K-Medoids algorithm for stock clustering, enabling investors to select fundamentally sound stocks based on the Price Earnings Ratio (PER) and Price-Book Value (PBV). The K-Medoids method results show that Cluster 1 includes 93 stocks with moderate PER and PBV values. Cluster 2 comprises 91 stocks with the lowest PER and PBV values. Cluster 3 contains 113 stocks with the highest PER and PBV values. Developing a web-based system that classifies stocks based on Price Earnings Ratio (PER) and Price Book Value (PBV) can help investors analyze and make investment decisions more effectively. Keywords: Investment, K-Medoids, Clustering, Stock

Jenis Item:	Artikel
Subjects:	500 Natural sciences and mathematics > 510 Mathematics
Divisions:	Fakultas Sains dan Teknologi > Sistem Informasi
Pengguna yang mendeposit:	Mrs Siti Masitah
Date Deposited:	16 Jan 2025 04:08
Last Modified:	16 Jan 2025 04:08
URI:	http://repository.uinsu.ac.id/id/eprint/23293

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