Ilmiatul , Karomah (2025) APPLICATION OF HIGH ORDER CHEN FUZZY TIME SERIES METHOD USING PARTICLE SWARM OPTIMIZATION FOR FORECASTING THE STOCK INDEX OF INDONESIAN ISLAMIC BANKS. FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM, UNIVERISTAS LAMPUNG.
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Abstrak (Berisi Bastraknya saja, Judul dan Nama Tidak Boleh di Masukan)
This study aims to forecast the stock index of Bank Syariah Indonesia (BSI) using the High Order Chen Fuzzy Time Series (HOCFTS) method integrated with Par- ticle Swarm Optimization (PSO). Forecasting financial data such as stock indices requires models capable of handling data uncertainty and non-linearity. The Chen Fuzzy Time Series method offers a flexible approach by utilizing fuzzy logic, and its higher-order variant improves accuracy by incorporating multiple past observa- tions. However, determining optimal interval partitioning remains a challenge. To address this, PSO is employed to optimize interval lengths and enhance forecast- ing performance. Monthly stock index data of BSI from June 2018 to September 2024 were analyzed. Forecasting was conducted using the HOCFTS model from order 1 to 8, and the accuracy of each model was evaluated using Mean Abso- lute Percentage Error (MAPE). The results show that the fourth-order model with PSO optimization yields the lowest MAPE, indicating superior forecasting accu- racy compared to other orders. This research contributes to the development of hy- brid forecasting models in Islamic financial markets, providing more accurate tools for investors and financial analysts to make informed decisions. Keywords: Fuzzy Time Series, Chen Model, High Order, Particle Swarm Opti- mization, Stock Index Forecasting, Bank Syariah Indonesia.
| Jenis Karya Akhir: | Skripsi |
|---|---|
| Subyek: | 500 ilmu pengetahuan alam dan matematika 500 ilmu pengetahuan alam dan matematika > 510 Matematika |
| Program Studi: | FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM (FMIPA) > Prodi S1 Matematika |
| Pengguna Deposit: | UPT . Desi Zulfi Melasari |
| Date Deposited: | 10 Nov 2025 08:14 |
| Terakhir diubah: | 10 Nov 2025 08:14 |
| URI: | http://digilib.unila.ac.id/id/eprint/92933 |
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