slot gacor slot gacor hari ini slot gacor 2025 demo slot pg slot gacor slot gacor
PERAMALAN PENDAPATAN BULANAN MENGGUNAKAN FUZZY TIME SERIES CHEN ORDE TINGGI | Yuliyanto | Jurnal Gaussian skip to main content

PERAMALAN PENDAPATAN BULANAN MENGGUNAKAN FUZZY TIME SERIES CHEN ORDE TINGGI

*Muhammad Rizky Yuliyanto  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Triastuti Wuryandari  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Iut Tri Utami  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2023 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract

Cooperatives need consideration in the making of business strategy decisions. Forecasting can assist cooperatives in deciding on their business strategy. This study used n-orde Fuzzy Time Series Chen. n-orde Fuzzy Time Series Chen captures data patterns formed by two or more historical data in each period called fuzzy logic relation (FLR). The pattern of FLR is used to be projected in forecasting future conditions. This study used 2-orde, 3-orde, and 4-orde with 1-orde as the comparison. This study used data on the monthly revenue of the Employee Cooperative of PT. Telekomunikasi Indonesia Semarang Region for the period of January 2019 to May 2022 to predict revenue for the period of June and July 2022. This study used symmetric Mean Absolute Percentage Error (sMAPE) in calculating the forecasting error rate. 1-orde, 2-orde, 3-orde, and 4-orde of Fuzzy Time Series Chen produced different forecasting results for the period of June and July 2022. 1-orde has sMAPE value of 23.15% (good enough forecasting), 2-orde and 3-orde have sMAPE value of 10.06% (good forecasting), and 4-orde has sMAPE value of 4.52% (very good forecasting). This study showed that the larger orde used in Fuzzy Time Series Chen, the lower forecasting error rate.

Note: This article has supplementary file(s).

Fulltext View|Download |  Research Instrument
CTA-Gaussian_Muhammad Rizky Y_24050117130044 19-Sep-2022 11-02-50
Subject
Type Research Instrument
  Download (473KB)    Indexing metadata
Keywords: Cooperative; Forecasting; Revenue; n-orde Fuzzy Time Series Chen; symmetric Mean Absolute Percentage Error (sMAPE).

Article Metrics:

  1. Brata, A. S. 2016. Penerapan Fuzzy Time Series Dalam Peramalan Data Seasonal. Skripsi. Universitas Islam Negeri Maulana Malik Ibrahim
  2. Chen, S. M. 1996. Forecasting Enrollments Based on Fuzzy Time Series. Journal of Fuzzy Sets and System, 81 (3): 311-319
  3. Chen, S. M. 2002. Forecasting enrollments based on high-order fuzzy time series. Cybernetics and Systems, 33(1), 1-16
  4. Heizer, J. dan Render, B. 2001. Prinsip-Prinsip Manajemen Operasi: Operations Management. Jakarta: Salemba Empat
  5. Makridakis, S., Hibon, M. 2000. The M3-Competition: results, conclusions and implications. International journal of forecasting, 16(4), 451-476
  6. Naba, A. 2009. Belajar Cepat Fuzzy Logic Menggunakan Matlab. Yogyakarta: ANDI
  7. Prasetya, H., Lukiastuti, F. 2009. Manajemen Operasi. Jakarta: PT. Buku Kita
  8. Putra, N. A. 2017. Prediksi Jumlah Penduduk Menggunakan Fuzzy Time Series Model Chen (Studi Kasus: Kota Tanjungpinang). Jurnal Skripsi. FT UMRAH
  9. Song, Q., dan Chissom, B. S. 1994. Forecasting Enrollments with Fuzzy Time Series-Part II. Journal of Fuzzy Sets and System, 62:1-8
  10. Sukirno. 2006. Ekonomi Pembangunan. Proses, Masalah dan Kebijakan. Kencana Prenada Media Group
  11. Ujianto, Y., dan Irawan, M. I. 2015. Perbandingan Performansi Metode Peramalan Fuzzy Time Series yang Dimodifikasi dan Jaringan Syaraf Tiruan Backpropagation (Studi Kasus: Penutupan Harga IHSG). Jurnal Sains dan Seni ITS. Vol. 4, No.2, Hal. 31-36

Last update:

No citation recorded.

Last update:

No citation recorded.