PREDIKSI PROBABILITAS TRANSISI RISIKO HARGA CRYPTOCURRENCY DENGAN MENERAPKAN ANALISIS RANTAI MARKOV

VIONICA, NADIA and Sukanda, Dian Cahyawati and Eliyati, Ning (2023) PREDIKSI PROBABILITAS TRANSISI RISIKO HARGA CRYPTOCURRENCY DENGAN MENERAPKAN ANALISIS RANTAI MARKOV. Undergraduate thesis, Sriwijaya University.

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Abstract

Cryptocurrency prices depend on supply and demand in the market, so that price fluctuations occur from time to time. This study aims to predict daily Cryptocurrency prices by applying Markov Chain analysis by finding the probability value of each country until the probability value reaches a steady state condition. The data analyzed in this study are Cryptocurrency price data (X_t ) for 2022 and data for January 2023 t=1,2,3,…396. The initial stage of applying Markov Chain analysis is to determine the state category based on the variables (X_t and X_(t-1) ) which are defined by 3 states, namely if the price increases it is categorized as state 1 (rising state), if the price remains combined as state 2 (fixed state), and falling prices are considered as state 3 (down states). The results of the probability of the price of Bitcoin in steady state conditions are that the price increases by 0.36. The price of Ethereum in steady state conditions is the amount the price increases by 0.39. The Binance coin price at a steady state price condition is the price increase by 0.42. The Tether price at a steady state price condition is the price increase by 0.44. Based on this, it can be concluded that the prices of Bitcoin and Ethereum have decreased in price with a probability during steady state conditions of 0.45 and 0.40, while Binance Coin and Tether have increased with probabilities during steady state conditions of 0.42 and 44.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Statistik
Subjects:	Q Science > QA Mathematics > QA1-43 General
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Nadia Vionica
Date Deposited:	04 Aug 2023 08:33
Last Modified:	04 Aug 2023 08:33
URI:	http://repository.unsri.ac.id/id/eprint/125673

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