Prediksi Yield Obligasi Indonesia Menggunakan Pendekatan Neutrosophic Soft Set

Aini, Qonita Qurratu (2023) Prediksi Yield Obligasi Indonesia Menggunakan Pendekatan Neutrosophic Soft Set. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Obligasi merupakan salah satu instrumen investasi yang dapat diperjualbelikan. Investasi obligasi menawarkan imbal hasil (yield). Yield merupakan ukuran pengembalian obligasi yang dijanjikan. Berbeda dengan suku bunga obligasi yang bersifat tetap, nilai yield obligasi biasanya berfluktuasi. Oleh karena itu, prediksi nilai yield yang akurat sangat penting bagi para investor. Fluktuasi nilai yield obligasi berupa keadaan naik, turun, atau tetap. Kondisi ini bersesuaian dengan konsep Neutrosophic soft set. Neutrosophic soft set banyak diterapkan pada berbagai bidang, termasuk pengambilan keputusan, analisis kelompok, diagnosis medis, manajemen proyek, kriteria evaluasi keamanan kota, dan aplikasi klinis. Pada penelitian ini, neutrosophic soft set diterapkan dalam penentuan yield obligasi Indonesia untuk deret waktu multi-atribut, sehingga dapat diprediksi yield obligasi dengan memperhatikan fluktuasi Yield Penutupan, Yield Pembukaan, dan amplitudo harian sebagai variabel prediktor. Hasil dari penelitian ini adalah pendekatan Neutrosophic Soft Set dapat diimplementasikan dalam melakukan prediksi yield obligasi dengan beberapa atribut. Dengan melakukan uji coba dengan beberapa variasi pada rentang data latih dan banyaknya nilai Yield Penutupan selanjutnya yang diprediksi (np), diperoleh bahwa untuk yield obligasi tenor 10 tahun cocok jika menggunakan data latih dengan rentang 10 tahun. Selain itu, didapatkan hasil bahwa prediksi dengan Neutrosophic Soft Set (NSS) cocok untuk jumlah data yang kecil. Hasil uji coba ini mendukung konsep n-order dalam pendekatan NSS, dimana pada penelitian ini digunakan 9th-order yang hanya menggunakan data hingga 9 data sebelumnya untuk prediksi t + 1. Akurasi terbaik didapatkan pada uji coba dengan rentang data latih 10 tahun untuk memprediksi 25 data berikutnya dengan nilai MAE 0.0606 dan RMSE 0.0735.
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Bonds are one of the investment instruments that can be traded. Investment bonds offer returns (yield). Yield is a measure of the promised returns on bonds. In contrast to bond interest rates, which are fixed, bond yield values usually fluctuate. Therefore, accurate prediction of the yield value is very important for investors. Fluctuations in bond yields can occur in the form of increasing, decreasing, or constant conditions. This condition corresponds to the concept of Neutrosophic soft set. Neutrosophic soft sets are widely applied in various fields, including decision-making, group analysis, medical diagnosis, project management, city safety evaluation criteria, and clinical applications. In this study, a neutrosophic soft set is applied to determine Indonesian bond yields for multi-attribute time series, so that bond yields can be predicted by consideringfluctuations in closing, opening, and daily amplitude as predictor variables. The result of this research is that the Neutrosophic Soft Set approach can be implemented to predict bond yields with several attributes. By conducting trials with several variations in the range of training data and subsequent np prediction data, it was found that yields on 10-year tenor bonds are suitable when using training data with a range of 10 years. In addition, the results show that predictions using Neutrosophic Soft Set (NSS) are suitable for small number of next data. The results of this trial support the concept of n-order in the NSS approach, where the 9th-order is used in this study, which only uses up to nine previous data to predict t + 1. The best accuracy was obtained in trials with a 10-year training data range to predict the next 25 data points, with an MAE value of 0.0606 and RMSE of 0.0735.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Neutrosophic Soft Set, Fuzzy logic, Yield, Multi-attribute, Closing, Daily amplitude, Neutrosophic Soft Set, Logika fuzzy, Yield, Multi-atribut, Penutupan, Amplitudo harian.
Subjects:	Q Science > QA Mathematics > QA159 Algebra Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA39.3 Fuzzy mathematics Q Science > QA Mathematics > QA9.64 Fuzzy logic Q Science > QA Mathematics > QA248_Fuzzy Sets
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Qonita Qurratu Aini
Date Deposited:	05 Aug 2023 01:21
Last Modified:	05 Aug 2023 01:21
URI:	http://repository.its.ac.id/id/eprint/103214

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