Jurnal SINTA 2
Prediksi Cuaca Pada Data Time Series Menggunakan Adaptive Neuro Fuzzy Inference System (ANFIS)
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 1 No. 1 (2014) · pp. 18–24
- ISSN
- 2528-6579, 2355-7699
- Published
- 2014-07-12
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakInformasi mengenai kondisi atmosfer yang cepat,akurat, dan terperinci sangat diperlukan oleh berbagai sektor. Salah satumetode yang dapat digunakan untuk melakukan prediksi dan peramalan model yangkompleks dengan akurasi yang tinggi adalah Adaptive Neuro Fuzzy InferenceSystem (ANFIS). Dengankemampuan metode ini untuk melakukan prediksi dan peramalan, pada penelitianini dilakukan perbandingan kinerja dari kedua kemampuan ANFIS tersebut padadata time series cuaca berdasarkan parameter-parameter atmosfir yangmempengaruhinya.Padapenelitian ini, metode ANFIS baik untuk proses prediksi maupun peramalan diimplementasidengan struktur standar ANFIS yaitu lima layer. Namun pada proses peramalan dilakukan penggabungan dengan metode moving average untuk meramalkan nilai parameter input pada saat pengujian. Pengujian dilakukanpada data latih 40%, 50% dan 60% dari total data. Selain itu, pengujian jugadilakukan dengan mengelompokkan data berdasarkan musim, yaitu kemarau danpenghujan.Hasil ujicoba menunjukkan bahwa metode ANFIS cukup baik diterapkan untuk proses prediksijika tanpa pengelompokan data berdasarkan musim. Namun jika dilakukanpengelompokan berdasarkan musim, kemampuan ANFIS dalam melakukan peramalanmemiliki tingkat akurasi yang lebih tinggi dengan nilai error yang cukup rendah.Kata kunci: prediksi cuaca,peramalan cuaca, data time series, ANFISAbstractRapid and accurate information on the atmospheric conditions is required by the various sectors. One ofthe methods can be used to perform prediction and forecasting of complex modelwith high accuracy is AdaptiveNeuro Fuzzy Inference System(ANFIS).According to these two capabilitiesof ANFIS, this research is aimed to conduct comparison of accuracy on weathertime series data. This research implemented ANFIS using standard ANFISarchitecture that consists of five layers both to predict and to forecast theweather. However, the forecasting process combined ANFIS and moving averagemethod to forecast the input parameters were used at testing. This researchperformed learning process using 40%, 50% and 60% of total data. Beside, thelearning process also has been done on data was grouped into two groups basedon the season. The testing result showed ANFIS has better performance forprediction the data that were not grouped based on the season. However, ANFIShas better accuracy and lower error since the learning and testing were done onthe data that was grouped based on season.Keywords: weather prediction, weather forecasting,time series data, ANFIS
Collaboration network of the authors
40 authors · 80 co-authorship links · 6 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Lambung Mangkurat University
- Universitas Gadjah Mada
- 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 |
|---|---|---|
| Satrio Hadi Wijoyo | University of Brawijaya | 3 |
| Indriati Indriati | University of Brawijaya | 2 |
| Buce Trias Hanggara | University of Brawijaya | 2 |
| Hanifah Muslimah Az-Zahra | University of Brawijaya | 2 |
| Bayu Rahayudi | University of Brawijaya | 2 |
| Imam Cholissodin | University of Brawijaya | 1 |
| Nurul Hidayat | University of Brawijaya | 1 |
| Sutrisno . | Affiliation unknown | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Daneswara Jauhari | University of Brawijaya | 1 |
| Alfian Himawan | University of Brawijaya | 1 |
| Muhammad Alkaff | Lambung Mangkurat University | 1 |
| Yuslena Sari | Lambung Mangkurat University | 1 |
| Eka Setya Wijaya | Lambung Mangkurat University | 1 |
| Syarifah Soraya | Lambung Mangkurat University | 1 |
| Suprapto Suprapto | Universitas Gadjah Mada | 1 |
| Muhammad Ghiffari | University of Brawijaya | 1 |
| Muhamad Rifky | University of Brawijaya | 1 |
| Bondan Sapta Prakoso | University of Brawijaya | 1 |
| Andri Santoso | University of Brawijaya | 1 |
| Nadia Artha Dewi | University of Brawijaya | 1 |
| Yoke Kusuma Arbawa | University of Brawijaya | 1 |
| Ahmad Afif Supianto | University of Brawijaya | 1 |
| Yustinus Radityo Pradana | University of Brawijaya | 1 |
| Roisul Setiawan | University of Brawijaya | 1 |
| Fara Regina Isadora | University of Brawijaya | 1 |
| Aditya Rachmadi | University of Brawijaya | 1 |
| Audi Kresna Fathurino | University of Brawijaya | 1 |
| Roshidah Nur Halimah | University of Brawijaya | 1 |
| Alfi Nur Rusydi | University of Brawijaya | 1 |
| Anisah Ikhsawiyanthi | University of Brawijaya | 1 |
| Safira Nur Rahmah | University of Brawijaya | 1 |
| Pradya Mutiarahma | University of Brawijaya | 1 |
| Widhy Hayuhardhika Nugraha Putra | University of Brawijaya | 1 |
| Reyhan Ivandi | University of Brawijaya | 1 |
| Nurfatima Selle | University of Brawijaya | 1 |
| Rizal Setya Perdana | University of Brawijaya | 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.