WAHONO, ASTI APRILLIA (2025) PENERAPAN MODEL ANALISIS UNIVARIATE TIME SERIES DALAM MEMPREDIKSI PERGERAKAN INDEKS HARGA SAHAM GABUNGAN (IHSG). S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This study focuses on forecasting the Composite Stock Price Index which functions as the main indicator to describe the overall performance of stocks listed on the Indonesia Stock Exchange. The purpose of this study is to evaluate and compare the accuracy of several Univariate Time Series models in predicting the movement of the Composite Stock Price Index in the period from January 2, 2023 to March 27, 2025. This study uses daily closing price data of the Composite Stock Price Index which is analyzed using EViews software version 12 through the stages of stationarity testing, identification and estimation of model parameters, classical assumption tests, and comparative analysis of prediction results. Based on the results obtained, the ARCH-GARCH model proved to be the most appropriate model for mapping the volatility pattern of the Composite Stock Price Index because it is able to represent changes in residual variance that are dynamic in financial data. This finding underlines that there is no single univariate model that is absolutely superior in all conditions, so model selection needs to be aligned with the objectives of short-term forecasting and medium-term volatility analysis. Keywords: IHSG, Univariate Time Series, ARIMA, ARCH-GARCH, Stock Prediction. Penelitian ini berfokus pada peramalan Indeks Harga Saham Gabungan yang berfungsi sebagai indikator utama untuk menggambarkan kinerja keseluruhan saham yang tercatat di Bursa Efek Indonesia. Tujuan penelitian ini adalah untuk mengevaluasi dan membandingkan akurasi beberapa model Univariate Time Series dalam meramalkan pergerakan Indeks Harga Saham Gabungan pada rentang waktu 2 Januari 2023 hingga 27 Maret 2025. Penelitian ini menggunakan data harga penutupan harian Indeks Harga Saham Gabungan yang dianalisis dengan software EViews versi 12 melalui tahapan pengujian stasioneritas, identifikasi dan estimasi parameter model, uji asumsi klasik, serta analisis perbandingan hasil prediksi. Berdasarkan hasil yang diperoleh, model ARCH-GARCH terbukti menjadi model yang paling sesuai untuk memetakan pola volatilitas Indeks Harga Saham Gabungan karena mampu merepresentasikan perubahan variansi residual yang bersifat dinamis pada data keuangan. Temuan ini menggarisbawahi bahwa tidak ada satu model univariate yang secara mutlak lebih unggul di semua kondisi, sehingga pemilihan model perlu diselaraskan dengan tujuan peramalan jangka pendek maupun analisis volatilitas jangka menengah. Kata Kunci: IHSG, Univariate Time Series, ARIMA, ARCH-GARCH, Prediksi Saham.
| Item Type: | Thesis (S1) |
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| Call Number CD: | FE/MJ. 25 196 |
| NIM/NIDN Creators: | 43121010082 |
| Uncontrolled Keywords: | IHSG, Univariate Time Series, ARIMA, ARCH-GARCH, Prediksi Saham. |
| Subjects: | 300 Social Science/Ilmu-ilmu Sosial > 330 Economics/Ilmu Ekonomi 300 Social Science/Ilmu-ilmu Sosial > 330 Economics/Ilmu Ekonomi > 332 Financial Economics, Finance/Ekonomi Keuangan dan Finansial, Ekonomi Biaya dan Pembiayaan > 332.6 Investment/Investasi |
| Divisions: | Fakultas Ekonomi dan Bisnis > Manajemen |
| Depositing User: | khalimah |
| Date Deposited: | 02 Aug 2025 04:15 |
| Last Modified: | 02 Aug 2025 04:15 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/96477 |
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