Open access Jurnal
Forecasting Inflation In Indonesia Using The Modified Fuzzy Time Series Cheng
Jurnal Matematika, Statistika dan Komputasi · Vol. 19 No. 1 (2022) · pp. 210–222
- ISSN
- 2614-8811, 1858-1382
- Published
- 2022-09-07
- Publisher
- Department of Mathematics, Hasanuddin University
- Language
- en
Abstract
English
Inflation is one of the most important indicators to analyze a country’s economy. Therefore, it is necessary to forecast the inflation rate. Forecasting can be done by various methods, one of which is Fuzzy Time Series Cheng. In this study, several modifications were made to the method used. The purpose of this study is to forecast using the Modified Fuzzy Time Series (FTS) Cheng method and determine the accuracy of the forecasting results obtained. The results of this study indicate that the Modified FTS Cheng method can be used in forecasting, either by determining the interval average-based or using the Sturges equation. Based on the results of the calculation of forecasting accuracy using Mean Absolute Percentage Error (MAPE), the accuracy for Modified FTS Cheng by determining the average-based interval for forecasting based on the current state and next state is 11.58% and 5.78%, respectively. Furthermore, the Modified FTS Cheng by determining the interval using the Sturges equation resulted in a MAPE value of 9.61% and a FTS Cheng of 7.54%. The MAPE value of each method is less than 10%, which means that the method has a very good performance, except for Modified FTS Cheng by determining the average-based interval for forecasting based on current state has good performance with MAPE values between 10 % and 20%.
Bahasa Indonesia
Inflasi merupakan salah satu indikator penting yang digunakan dalam menganalisa perekonomian di suatu negara. Oleh karena itu, perlu dilakukan peramalan terhadap tingkat inflasi. Peramalan dapat dilakukan dengan berbagai metode, salah satunya Fuzzy Time Series Cheng. Pada penelitian ini dilakukan beberapa modifikasi pada metode yang digunakan. Tujuan penelitian ini adalah melakukan peramalan menggunakan metode Fuzzy Time Series Cheng yang Dimodifikasi dan menentukan akurasi dari hasil peramalan yang diperoleh. Hasil dari penelitian ini menunjukkan bahwa metode Fuzzy Time Series Cheng Dimodifikasi dapat digunakan dalam melakukan peramalan, baik dengan penentuan interval berbasis rata-rata maupun menggunakan persamaan Sturges. Berdasarkan hasil perhitungan keakuratan peramalan menggunakan Mean Absolute Percentage Error (MAPE) diperoleh akurasi untuk Fuzzy Time Series Cheng Dimodifikasi dengan penentuan interval berbasis rata-rata untuk peramalan berdasarkan current state dan next state masing-masing sebesar 11,58% dan 5,78%. Selanjutnya, Fuzzy Time Series Cheng Dimodifikasi dengan penentuan interval meggunakan persamaan Sturges menghasilkan nilai MAPE sebesar 9,61% dan Fuzzy Time Series Cheng sebesar 7,54%. Nilai MAPE dari masing-masing metode kurang dari 10% yang berarti bahwa metode tersebut mempunyai kinerja yang sangat baik, kecuali Fuzzy Time Series Cheng Dimodifikasi dengan penentuan interval berbasis rata-rata untuk peramalan berdasarkan current state mempunyai kinerja yang baik dengan nilai MAPE berada antara 10% dan 20%.
Keywords
Collaboration network of the authors
19 authors · 33 co-authorship links
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- State University of Makassar
- Telkom University
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Naimah Aris | Affiliation unknown | 5 |
| Budi Nurwahyu | Affiliation unknown | 3 |
| Faisal Faisal | Affiliation unknown | 2 |
| Khaeruddin Khaeruddin | State University of Makassar | 1 |
| Meriam Meriam | Affiliation unknown | 1 |
| Islamiyah Abbas | Affiliation unknown | 1 |
| Hasmawati Basir | Affiliation unknown | 1 |
| Muh. Ali Imran | Affiliation unknown | 1 |
| Aswad Hariri Mangalaeng | Affiliation unknown | 1 |
| Salsabila Ammari | Affiliation unknown | 1 |
| Hasmawati Hasmawati | Telkom University | 1 |
| Ananda Dwi Nabila Nanda | Affiliation unknown | 1 |
| Ervie Yuniarti Astika Mustafaputri Yuniarti | Affiliation unknown | 1 |
| Heryati Nur Fatimah Sari | Affiliation unknown | 1 |
| Dermawan Saputra | Affiliation unknown | 1 |
| Cindy Cindy | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.