Deteksi Penyimpangan Pada Transaksi Saham Berdasarkan Pola Waktu Dengan Menggunakan Metode Peer Group Analysis

Ulya, Bilqiest Rokhimatul (2023) Deteksi Penyimpangan Pada Transaksi Saham Berdasarkan Pola Waktu Dengan Menggunakan Metode Peer Group Analysis. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Teknologi informasi pada saat ini menunjukkan perkembangan yang sangat pesat, khususnya teknologi digital yang membuat masyarakat berproses menuju dunia digital, salah satunya dengan trend investasi digital yaitu saham. Dengan fenomena populernya saham di kalangan masyarakat, banyak dijumpai oknum yang sengaja melakukan tindakan kecurangan dan termasuk suatu bentuk tindak pidana. Tindakan tersebut perlu dan penting untuk dideteksi sehingga memberikan kewaspadaan kepada para investor agar lebih teliti dalam membeli sebuah saham. Pada penelitian ini telah dilakukan deteksi adanya penyimpangan pada saham menggunakan peer group analysis dengan dataset pergerakan saham di bursa efek Indonesia. Dalam metode Peer Group Analysis telah dilakukan pengelompokkan objek berdasarkan kesamaan pola waktu ke dalam sebuah kelompok, kemudian dianalisis untuk mendeteksi perilaku abnormal suatu target lalu membandingkannya dengan kelompoknya. Hasil dari uji coba yang telah dilakukan, data saham yang memiliki pergerakan menyimpang dari anggota sesama clusternya diindikasikan sebagai penyimpangan transaksi saham.

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Information technology is currently showing very rapid development, especially digital technology which makes people move towards the digital world, one of which is the digital investment trend, namely stocks. With the phenomenon of the popularity of shares among the public, there are many individuals who deliberately take actions that benefit themselves and cause losses to other parties. These actions are necessary and important to detect so as to give vigilance to investors to be more careful in buying a stock. In this study, detection of stock fraud will be carried out using peer group analysis with a dataset of stock movements on the Indonesian stock exchange. In the Peer Group Analysis method, objects will be grouped based on the similarity of time patterns into a group, then analyzed to detect abnormal behavior of a target and then compared with other objects in the group and to measure the deviation of its behavior from its peers. Stock data that has deviated movements from its peers will be indicated as stock transaction deviations.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	investasi, saham, deteksi penyimpangan, perilaku abnormal, peer group analysis. investment, stocks, detection of irregularities, abnormal behavior, peer group analysis.
Subjects:	Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science) Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Bilqiest Rokhimatul Ulya
Date Deposited:	16 Feb 2023 03:00
Last Modified:	16 Feb 2023 03:00
URI:	http://repository.its.ac.id/id/eprint/97373

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