Vol. 7 No. 1 (2026) Articles
Open Access

Forecasting Harga Saham PT. ABCD Menggunakan Algoritma Fuzzy Time Series

Muchamad Izzul Khaq
Universitas Yudharta Pasuruan
Arif Faizin
Universitas Yudharta Pasuruan
Ahmad Zulham Fahamsyah Havy
Universitas Yudharta Pasuruan
Published: January 10, 2026 Pages: 1-9
Original Full-Text Article
Download published version for reading and archiving
Abstract

High stock price fluctuations pose a significant challenge for investors and analysts in determining investment strategies. Price dynamics influenced by economic, political, and psychological market factors require forecasting methods that can accommodate uncertainty and non-linear historical data patterns. This study applies Cheng's Fuzzy Time Series algorithm to predict the stock price of PT. ABCD by going through the stages of universe set formation, interval determination, fuzzification, fuzzy logic relationship formation, and defuzzification to obtain prediction results. The method implementation was carried out using two approaches: manual calculation using Microsoft Excel and automatic calculation using the Orange application. The results show that Cheng's method is able to produce predictions very close to the actual value, with an accuracy level measured using the Mean Absolute Percentage Error (MAPE) indicator of 0.058787% on both platforms. The consistency of the results between Excel and Orange proves the reliability of Cheng's method, so it can be used as a reference in supporting investment decision-making in the Indonesian capital market.

Article Metrics & Downloads Graph
Monthly Download Trends:
Author Biographies
Muchamad Izzul Khaq Universitas Yudharta Pasuruan

Program Studi Teknik Informatika, Universitas Yudharta Pasuruan, Kabupaten Pasuruan, Provinsi Jawa Timur, Indonesia

Arif Faizin Universitas Yudharta Pasuruan

Program Studi Teknik Informatika, Universitas Yudharta Pasuruan, Kabupaten Pasuruan, Provinsi Jawa Timur, Indonesia

Ahmad Zulham Fahamsyah Havy Universitas Yudharta Pasuruan

Program Studi Teknik Informatika, Universitas Yudharta Pasuruan, Kabupaten Pasuruan, Provinsi Jawa Timur, Indonesia

How to Cite
Khaq, M. I., Faizin, A., & Havy, A. Z. F. (2026). Forecasting Harga Saham PT. ABCD Menggunakan Algoritma Fuzzy Time Series. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 7(1), 1-9. https://doi.org/10.63447/jimik.v7i1.1639
License

Creative Commons Attribution 4.0 International License (CC BY 4.0)

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License .

  • Share: You are free to copy, distribute, and transmit the work in any medium or format.
  • Adapt: You are free to remix, transform, and build upon the work for any purpose, even commercially.
  • Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Copyright & Retention: Authors retain copyright without restrictions and grant this journal the right of first publication under an open-access model. The journal retains non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

References
Total: 15 References
  1. Arvie, D. (2022). Peramalan import migas dan non-migas menggunakan metode fuzzy time series model cheng. Jatisi (Jurnal Teknik Informatika dan Sistem Informasi), 9(4), 3519–3528. https://doi.org/10.35957/jatisi.v9i4.2885
  2. Bidin, J., Sharif, N., Abas, S., Akil, K., & Abdullah, N. (2022). Cheng fuzzy time series model to forecast the price of crude oil in Malaysia. Journal of Computing Research and Innovation, 7(2), 196–210. https://doi.org/10.24191/jcrinn.v7i2.304
  3. Fathoni, M. Y., & Wijayanto, S. (2021). Forecasting Penjualan Gas LPG di Toko Sembako Menggunakan Metode Fuzzy Time Series. JUPITER (Jurnal Penelitian Ilmu Dan Teknologi Komputer), 13(2), 87-96.
  4. Fauzi, F., Agustina, D., & Nur, I. (2021). Evaluasi metode fuzzy time series cheng dan ruey chyn tsaur. Variance: Journal of Statistics and Its Applications, 3(2), 61–72. https://doi.org/10.30598/variancevol3iss2page61-71
  5. Fauziah, L., Devianto, D., & Maiyastri, M. (2019). Peramalan beban listrik jangka menengah di wilayah Teluk Kuantan dengan metode fuzzy time series cheng. Jurnal Matematika UNAND, 8(2), 84–92. https://doi.org/10.25077/jmu.8.2.84-92.2019
  1. Ismail, R., Surorejo, S., & Septiana, P. (2022). Systematic Literature Review: Penerapan Metode Fuzzy Logic Dalam Sistem Pakar. Indonesian Journal of Informatics and Research, 3(2), 47-53.
  2. Juwairiah, J., Haidar, W., & Rustamaji, H. (2022). Prediction of IDR-USD exchange rate using the cheng fuzzy time series method with particle swarm optimization. International Journal of Artificial Intelligence & Robotics (IJAIR), 4(2), 59–69. https://doi.org/10.25139/ijair.v4i2.5259
  3. Kadry, I., Massalesse, J., & Nur, M. (2022). Forecasting inflation in Indonesia using the modified fuzzy time series cheng. Jurnal Matematika, Statistika dan Komputasi, 19(1), 210–222. https://doi.org/10.20956/j.v19i1.21868
  4. Kurniawan, T. A. D., Setiawan, A., & Tita, F. (2025). Perbandingan kinerja metode support vector regression dan metode regresi linier berganda dalam memprediksi BMI pada dataset ASTHMA. Jurnal Sains dan Edukasi Sains, 8(2), 133–142. https://doi.org/10.24246/juses.v8i2p133-142
  5. Putra, K. Y. (2025). Sistem prediksi harga saham menggunakan fuzzy time series model Lee. JITU: Journal Informatic Technology and Communication, 9(1), 92–103. https://doi.org/10.36596/jitu.v9i1.1769
  6. Rochella, M., Lewa, F. S., & Witono, A. H. (2024, September). Penerapan CRISP-DM untuk Prediksi Harga Saham Starbucks Corporation Menggunakan Time Series Analysis. In Prosiding Seminar Nasional Universitas Ma Chung (Informatika & Sistem Informasi; Bahasa dan Seni; Farmasi) (Vol. 4, pp. 214-226).
  7. Sofhya, H. (2022). Comparison of fuzzy time series chen and cheng to forecast Indonesia rice productivity. Eduma: Mathematics Education Learning and Teaching, 11(1), 119–130. https://doi.org/10.24235/eduma.v11i1.10936
  8. Sofia, A. (2023). Forecasting Indonesian Islamic Bank (BSI) share prices using the fuzzy time series cheng method. Parameter: Journal of Statistics, 3(2), 68–75. https://doi.org/10.22487/27765660.2023.v3.i2.16920
  9. Subanti, S., & Rahmaningrum, A. (2024). Forecasting on closing stock price data using fuzzy time series. Indonesian Journal of Applied Statistics, 7(1), 41–52. https://doi.org/10.13057/ijas.v7i1.54309
  10. Tamam, M. B., Kuzairi, K., Yulianto, T., Faisol, F., Yudistira, I., & Amalia, R. (2024). Perbandingan metode fuzzy time series chen dan metode exponential smoothing dalam memprediksi curah hujan di Kabupaten Pamekasan. Networking Engineering Research Operation, 9(2), 127–136. https://doi.org/10.21107/nero.v9i2.27986.
Similar Articles

Articles sharing related keywords and machine learning classifications:

Peningkatan Akurasi Nilai Harga Saham Menggunakan Metode Long Short-Term Memory (LSTM) pada PT Unilever Tbk
PENERAPAN METODE NEURAL NETWORK DENGAN STRUKTUR BACKPROPAGATION UNTUK MEMPREDIKSI KEBUTUHAN STOK PADA TOKO UMKM PERLENGKAPAN BAYI BABYQU
Analisis Peramalan Jumlah Penjualan Susu pada PT. Superindo Utama Jaya Menggunakan Metode Weighted Moving Average
Sistem Pakar Diagnosis Kanker Prostat Berbasis Web Menggunakan Logika Fuzzy Tsukamoto
ANALYSIS OF STUDENT ACADEMIC ACHIEVEMENT LEVELS USING FUZZY LOGIC