CD Skripsi

Metode density-based spatial clustering applications with noise dan hierarchical clustering untuk Pengelompokan saham

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Stock investment is one of the financial instruments that plays an important role in encouraging economic growth. The rapid development of the capital market makes investors faced with the challenge of identifying patterns and groups of stocks that are suitable for their investment strategies. One approach that can be used to understand the characteristics of stocks is through clustering analysis. This study aims to cluster the stocks in KOMPAS100 index based on fundamental indicators and ESG values by comparing two methods. The methods used in this study are density-based clustering, namely Density Based Spatial Clustering Application with Noise (DBSCAN) and hierarchical methods, namely Agglomerative Hierarchical Clustering (AHC). Evaluation of cluster results was conducted using the silhouette coefficient and Davies-Bouldin Index (DBI) metrics.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2103110509

Penerbit

Pekanbaru : Universitas Riau FMIPA Statistika., 2025

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2103110509

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

STATISTIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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