Pemodelan Harga Saham Menggunakan Model Mixture Autoregressive

Rasyid, Dwilaksana Abdullah (2018) Pemodelan Harga Saham Menggunakan Model Mixture Autoregressive. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Telekomunikasi telah menjadi kebutuhan bagi masyarakat luas yang tidak dapat dihindari. Berkembangnya pengguna teknologi komunikasi di Indonesia mengakibat-kan perkembangan teknologi informasi mampu menggeser media komunikasi dari kebutuhan sekunder atau tersier menjadi kebutuhan primer. Meningkatnya kebutuhan komunikasi dimasyarakat membuat saham dibidang telekomunikasi termasuk saham dengan kapitalisasi terbesar. Hal tersebut membuat masyarakat untuk berinvestasi pada perusahaan telekomunikasi. Harga saham terkadang ditutup dengan harga sangat tinggi atau sangat rendah. Fluktuasi penutupan harga saham yang tinggi berakibat pada perilaku harga saham untuk periode selanjutnya dan muncul dugaan adanya multimodal. Seringkali dalam memodelkan suatu time series mengalami kesulitan disebabkan data multimodal. Penelitian ini bertujuan untuk memperkenalkan pemodelan time series dengan menggunakan model Autoregressive Integrated Moving Average (ARIMA) dan Mixture Autoregressive (MAR). Untuk mengaplikasikan penelitian ini penulis menggunakan data penutupan harga saham pada beberapa perusahaan yang sejenis yaitu perusahaan yang bergerak pada bidang telekomunikasi. Hasil yang diperoleh adalah model MAR pada ketiga perusahaan lebih baik jika dibandingkan dengan model ARIMA.================================================================================================================== Telecommunication has been being a need for wide community that can not be avoided. The development of communication technology users in Indonesia causes movement of development of information technology from a secondary or tertiary need to be a primary need. The increase of needs of communication in the community make telecom stocks being the largest capital stocks. So that makes community should invest in communication factory. The price of the stock closed somehow with high prices or low prices. Closed fluctuation of high price stocks cause behaviour of stock prices for next period and emerge a multiomdal. Frequently its hard to perform modelling a time series model because of multimodal. the purpose of this research is to introduce time series model using Autoregressive Integrated Moving Average (ARIMA) and Mixture Autoregressive (MAR). To apply this research, writer is using closed stock price in some similiar factories, that is communication factory. The result obtained is the MAR model in the three companies is better when compared with ARIMA model.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Autoregressive Integrated Moving Average, Mixture Autoregressive, Harga Saham, Telekomunikasi
Subjects: Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Q Science > QA Mathematics > QA279.5 Bayesian statistical decision theory.
Q Science > QA Mathematics > QA402.5 Genetic algorithms.
Divisions: Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Rasyid Dwilaksana Abdullah
Date Deposited: 09 Jul 2021 09:32
Last Modified: 09 Jul 2021 09:32
URI: https://repository.its.ac.id/id/eprint/57186

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