| dc.contributor.advisor | Mangku, I Wayan | |
| dc.contributor.advisor | Ardana, Ngakan Komang Kutha | |
| dc.contributor.author | Yudhistira, Muhammad Fakhriansyah | |
| dc.date.accessioned | 2023-09-14T23:55:57Z | |
| dc.date.available | 2023-09-14T23:55:57Z | |
| dc.date.issued | 2023 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/124698 | |
| dc.description.abstract | Saham adalah salah satu instrumen investasi yang diminati investor. Akan tetapi, harga saham bergerak cepat dan fluktuatif. Pergerakan harga saham dipengaruhi oleh banyak faktor di antaranya adalah inflasi, suku bunga, dan kurs USD, yang merupakan faktor eksternal di luar perusahaan. Penelitian ini bertujuan membuat model pengaruh inflasi, suku bunga, dan kurs USD terhadap harga saham menggunakan data longitudinal. Model dibuat menggunakan regresi nonparametrik spline truncated. Data yang digunakan dalam penelitian ini terdiri dari dua emiten, yaitu PT. Astra Agro Lestari (AALI) dan PT. Perusahaan Perkebunan London Sumatra (LSIP). Data dipisahkan menjadi dua sampel, yaitu data in sample dimulai dari Januari 2017 – Desember 2020 yang digunakan untuk membuat model dan data out sample dimulai dari Januari 2021 – Desember 2021 untuk diprediksi. Metode MAPE digunakan sebagai alat pengukur kinerja prediksi. Hasil penelitian menunjukkan model terbaik untuk saham AALI memiliki tiga titik knot dan memiliki nilai MAPE sebesar 17,27%. Model terbaik untuk saham LSIP memiliki tiga titik knot dan memiliki nilai MAPE sebesar 13,42%. | id |
| dc.description.abstract | Stock is one of investment instruments that an investor has an interest in. However, stocks move fast and fluctuate. The movement of the stock price is influenced by many factors including inflation, interest rate and USD exchange rate which are external factors outside the company. This manuscript aims to create a model for influence of inflation, interest rate, and USD exchange rate on stock prices uses longitudinal data. The models were obtained by using nonparametric regression spline truncated. The data consisted of stocks from two companies, namely PT. Astra Agro Lestari (AALI) and PT. Perusahaan Perkebunan London Sumatra (LSIP). The data were split into two sub-samples which were “in sample” data from January 2017 – December 2020 that were used to generate the models and “out sample” data from January 2021 – December 2021 that were used in predictions. MAPE was used as measurement of predictive performance. The results show that the best model for AALI has three knot points and has a MAPE value of 17,27%. The best model for LSIP has three knots and has a MAPE value of 13,42%. | id |
| dc.language.iso | id | id |
| dc.publisher | IPB University | id |
| dc.title | Pemodelan Regresi Nonparametrik Spline Truncated pada Faktor-faktor Eksternal yang Memengaruhi Harga Saham | id |
| dc.title.alternative | Nonparametric Regression Spline Truncated Modelling on External Factors Affecting Stock Prices | id |
| dc.type | Undergraduate Thesis | id |
| dc.subject.keyword | data longitudinal | id |
| dc.subject.keyword | regresi nonparametrik spline truncated | id |
| dc.subject.keyword | saham | id |
| dc.subject.keyword | longitudinal data | id |
| dc.subject.keyword | nonparametric regression spline truncated | id |
| dc.subject.keyword | stock | id |
