Prediksi Harga Saham pada Portofolio Investor dengan Analisis Time Series Harga Saham menggunakan ANN


Authors

  • Hendra Wibiksana Sekolah Tinggi Teknologi Bandung, Bandung, Indonesia

DOI:

https://doi.org/10.47065/bulletincsr.v4i1.298

Keywords:

Shares; Backpropagation; Training; Testing; Predictions; Portfolio

Abstract

The Indonesian Stock Exchange (BEI) is a place for stock market trading in Indonesia. In general, this is represented by the Composite Stock Price Index (IHSG) value. IHSG itself is the combined value of all shares listed on the Stock Exchange. It doesn't matter whether the shares traded that day are up, down, flat (no change in value), not traded, or even suspended (prohibited from making transactions within a certain period of time). The stock data source used is the closing price of BNI, BCA and Mandiri shares for 15 years from 2008-2022 from the Indonesian Stock Exchange (via the Yahoo Finance site). Each stock data is trained and tested, to see how accurate it is using this method. The stock prices predicted by ANN are combined into a portfolio, this portfolio will show an increase or decrease. At the end of the process, the rate of change in stock prices from predicted losses to predicted profitable stock prices is calculated. The daily data accuracy of BNI, BCA and Mandiri is 97.6927%, 97.9754% and 97.6275% respectively. Weekly data accuracy is slightly smaller than daily accuracy. The accuracy of weekly data for BNI, BCA and Mandiri is 95.7673%, 97.1222% and 96.5592% respectively. Monthly data accuracy is slightly smaller than weekly accuracy. The accuracy of BNI, BCA and Mandiri monthly data is 90.4161%, 94.781% and 93.0619% respectively. If an investor focuses all his funds on buying just one share, he will get 3 times the portfolio profit from before. If the profit on BNI shares is 46.12%, then in terms of portfolio, the investor gets a profit of 46.12% x 3 = 138.36%. Compare this with the profit levels of the 3 banks, which if added up, the value becomes as follows: 46.12+54.42+56.01 = 156.55%. So there is an additional profit from the portfolio of 156.55% - 138.36% = 18.19%.

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References

U. Pada et al., “Membangun Kesadaran Kemandirian Dengan Inovasi Dan Kreatifitas,” J. Abdi Masy. Multidisiplin, vol. 1, no. 1, pp. 62–65, 2022.

M. A. C. Perdana, N. W. Sulistyowati, A. Ninasari, Jainudin, and S. Mokodenseho, “Analisis Pengaruh Pembiayaan, Skala Usaha, dan Ketersediaan Sumber Daya Manusia terhadap Profitabilitas UMKM,” Sanskara Ekon. dan Kewirausahaan, vol. 1, no. 03, pp. 135–148, 2023, doi: 10.58812/sek.v1i03.120.

M. D. Hadi Pratama, K. Al Kautsar, R. Hidayat, V. Melistiana, and Tiarapuspa, “Analisis Bisnis Strategi Nasi Padang 99,” J. Ekon. Trisakti, vol. 3, no. 1, pp. 601–610, 2023, doi: 10.25105/jet.v3i1.15519.

N. Nasfi, R. Rahmad, and S. Sabri, “Pengaruh Kualitas Pelayanan Terhadap Kepuasan Nasabah Perbankan Syariah,” Ekon. SYARIAH J. Econ. Stud., vol. 4, no. 1, p. 19, 2020, doi: 10.30983/es.v4i1.3146.

M. A. Prawira and R. Amin, “Sistem Pendukung Keputusan Pemilhan Karyawan Terbaik Pada PT. Citra Prima Batara Dengan Metode AHP,” J. Tek. Komput. AMIK BSI, vol. 8, no. 2, pp. 174–180, 2022, doi: 10.31294/jtk.v4i2.

A. Setiobudi, C. Sudyasjayanti, and A. A. Danarkusuma, “Pengaruh Pengalaman Pelanggan, Kualitas Layanan Dan Kepercayaan Pelanggan Terhadap Kesediaan Untuk Membayar,” JBMI (Jurnal Bisnis, Manajemen, dan Inform., vol. 17, no. 3, pp. 238–252, 2021, doi: 10.26487/jbmi.v17i3.12442.

A. Rohmah, F. Sembiring, and ..., “Implementasi Algoritma K-Means Clustering Analysis Untuk Menentukan Hambatan Pembelajaran Daring (Studi Kasus: Smk Yaspim …,” … Sist. Inf. dan …, pp. 290–298, 2021.

V. N. Sari, L. Y. Astri, and E. Rasywir, “Analisis Dan Penerapan Algoritma Naive Bayes Untuk Evaluasi,” J. Ilm. Mhs. Tek. Inform., vol. 2, no. 1, pp. 53–68, 2020.

P. P. Nicolas, H. Soetanto, W. Wahyudi, and A. Rossi, “Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik pada PT. XYZ dengan Metode Profile Matching dan Interpolasi,” J. Sist. dan Teknol. Inf., vol. 9, no. 2, p. 121, 2021, doi: 10.26418/justin.v9i2.44159.

Fachruddin, M. R. Pahlevi, M. Ismail, E. Rasywir, and Y. Pratama, “Analisis Usability Pada Implementasi Sistem Pengelolaan Keuangan Masjid Menggunakan USE Questionnaire,” J. Media Inform. Budidarma, vol. 4, pp. 1216–1224, 2020, doi: 10.30865/mib.v4i4.2518.

V. Abdurrohman and S. Nita, “Rancang Bangun Sistem Informasi Penjualan Smartphone Berbasis Web,” Semin. Nas. Teknol. Inf. dan Komun., pp. 43–48, 2020.

D. W. Sitohang and A. Rikki, “Implementasi Algoritma K- Means Clustering untuk Mengelompokkan Data Gizi Balita pada Kecamatan Garoga Tapanuli Utara,” KAKIFIKOM (Kumpulan Artik. Karya Ilm. Fak. Ilmu Komputer), vol. 02, pp. 80–92, 2019, doi: 10.54367/kakifikom.v1i2.642.

M. Seyedan and F. Mafakheri, “Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities,” J. Big Data, vol. 7, no. 1, 2020, doi: 10.1186/s40537-020-00329-2.

M. M. Abdelsamea, U. Zidan, Z. Senousy, M. M. Gaber, E. Rakha, and M. Ilyas, “A survey on artificial intelligence in histopathology image analysis,” Wiley Interdiscip. Rev. Data Min. Knowl. Discov., vol. 12, no. 6, pp. 1–44, 2022, doi: 10.1002/widm.1474.

Dr. V. Suma, “Data Mining based Prediction of Demand in Indian Market for Refurbished Electronics,” J. Soft Comput. Paradig., vol. 2, no. 3, pp. 153–159, 2020, doi: 10.36548/jscp.2020.3.002.

A. Voden?arevi?, J. Kreuzeder, A. Wöckel, and P. Fasching, “Prediction of QT Prolongation in Advanced Breast Cancer Patients Using Survival Modelling Algorithms,” in Proceedings ofthe 12th International Conference on Data Science, Technology and Applications (DATA 2023), 2023, no. Data, pp. 164–172, doi: 10.5220/0012130900003541.

R. D. Laksmana, E. Santoso, and B. Rahayudi, “Prediksi penjualan roti menggunakan metode exponential smoothing (Studi Kasus: Harum Bakery),” Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 5, pp. 4933–4941, 2019.

T. M. Tamtelahitu, “Komparasi Algoritma Clustering dengan Dataset Penyebaran Covid-19 di Indonesia Periode Maret-Mei 2020,” J. Teknol. Technoscientia, vol. 13, no. 1, pp. 27–34, 2020.

M. A. Aswathy and M. Jagannath, “Performance Analysis of Segmentation Algorithms for the Detection of Breast Cancer,” Procedia Comput. Sci., vol. 167, pp. 666–676, 2020, doi: 10.1016/j.procs.2020.03.333.


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Submitted: 2023-11-26
Published: 2023-12-31

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How to Cite

Wibiksana, H. (2023). Prediksi Harga Saham pada Portofolio Investor dengan Analisis Time Series Harga Saham menggunakan ANN. Bulletin of Computer Science Research, 4(1), 10-17. https://doi.org/10.47065/bulletincsr.v4i1.298

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