Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system

Ida Wahyuni; Wayan Firdaus Mahmudy; Atiek Iriany

doi:10.1109/ICITISEE.2016.7803061

Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining an accurate prediction is difficult as there are too many input parameters including the world climate change that affect the accuracy. An accurate prediction is required to arrange a good schedule for planting agricultural commodities. A good approach is required to obtain a good model as well as the accurate prediction. This paper proposes Tsukamoto fuzzy inference system (FIS) to solve the problem. An intensive effort is put in building fuzzy membership function based on rainfall data in Tengger region from ten years ago. A series of numerical experiments prove that the proposed approach produces better results comparable to those achieved by other approach. In Tutur region Tsukamoto fuzzy inference system obtain Root Mean Square Error (RMSE) of 8.64, it is better than GSTAR-SUR method that obtain RMSE of 10.89.

Original language	English
Title of host publication	Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	130-135
Number of pages	6
ISBN (Electronic)	9781509015672
DOIs	https://doi.org/10.1109/ICITISEE.2016.7803061
Publication status	Published - 30 Dec 2016
Event	1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016 - Yogyakarta, Indonesia Duration: 23 Aug 2016 → 24 Aug 2016

Publication series

Name	Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016

Conference

Conference	1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016
Country/Territory	Indonesia
City	Yogyakarta
Period	23/08/16 → 24/08/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Prediction
Rainfall
Tengger
Tsukamoto Fuzzy Inference Systems

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10.1109/ICITISEE.2016.7803061

Cite this

Wahyuni, I., Mahmudy, W. F., & Iriany, A. (2016). Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system. In Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016 (pp. 130-135). Article 7803061 (Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICITISEE.2016.7803061

Wahyuni, Ida ; Mahmudy, Wayan Firdaus ; Iriany, Atiek. / Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system. Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 130-135 (Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016).

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title = "Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system",

abstract = "Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining an accurate prediction is difficult as there are too many input parameters including the world climate change that affect the accuracy. An accurate prediction is required to arrange a good schedule for planting agricultural commodities. A good approach is required to obtain a good model as well as the accurate prediction. This paper proposes Tsukamoto fuzzy inference system (FIS) to solve the problem. An intensive effort is put in building fuzzy membership function based on rainfall data in Tengger region from ten years ago. A series of numerical experiments prove that the proposed approach produces better results comparable to those achieved by other approach. In Tutur region Tsukamoto fuzzy inference system obtain Root Mean Square Error (RMSE) of 8.64, it is better than GSTAR-SUR method that obtain RMSE of 10.89.",

keywords = "Prediction, Rainfall, Tengger, Tsukamoto Fuzzy Inference Systems",

author = "Ida Wahyuni and Mahmudy, \{Wayan Firdaus\} and Atiek Iriany",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016 ; Conference date: 23-08-2016 Through 24-08-2016",

year = "2016",

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language = "English",

series = "Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016",

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Wahyuni, I, Mahmudy, WF & Iriany, A 2016, Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system. in Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016., 7803061, Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016, Institute of Electrical and Electronics Engineers Inc., pp. 130-135, 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016, Yogyakarta, Indonesia, 23/08/16. https://doi.org/10.1109/ICITISEE.2016.7803061

Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system. / Wahyuni, Ida; Mahmudy, Wayan Firdaus ; Iriany, Atiek.
Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 130-135 7803061 (Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system

AU - Wahyuni, Ida

AU - Mahmudy, Wayan Firdaus

AU - Iriany, Atiek

PY - 2016/12/30

Y1 - 2016/12/30

N2 - Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining an accurate prediction is difficult as there are too many input parameters including the world climate change that affect the accuracy. An accurate prediction is required to arrange a good schedule for planting agricultural commodities. A good approach is required to obtain a good model as well as the accurate prediction. This paper proposes Tsukamoto fuzzy inference system (FIS) to solve the problem. An intensive effort is put in building fuzzy membership function based on rainfall data in Tengger region from ten years ago. A series of numerical experiments prove that the proposed approach produces better results comparable to those achieved by other approach. In Tutur region Tsukamoto fuzzy inference system obtain Root Mean Square Error (RMSE) of 8.64, it is better than GSTAR-SUR method that obtain RMSE of 10.89.

AB - Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining an accurate prediction is difficult as there are too many input parameters including the world climate change that affect the accuracy. An accurate prediction is required to arrange a good schedule for planting agricultural commodities. A good approach is required to obtain a good model as well as the accurate prediction. This paper proposes Tsukamoto fuzzy inference system (FIS) to solve the problem. An intensive effort is put in building fuzzy membership function based on rainfall data in Tengger region from ten years ago. A series of numerical experiments prove that the proposed approach produces better results comparable to those achieved by other approach. In Tutur region Tsukamoto fuzzy inference system obtain Root Mean Square Error (RMSE) of 8.64, it is better than GSTAR-SUR method that obtain RMSE of 10.89.

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KW - Rainfall

KW - Tengger

KW - Tsukamoto Fuzzy Inference Systems

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M3 - Conference contribution

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BT - Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 23 August 2016 through 24 August 2016

ER -

Wahyuni I, Mahmudy WF , Iriany A. Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system. In Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 130-135. 7803061. (Proceedings - 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2016). doi: 10.1109/ICITISEE.2016.7803061

Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system

Abstract

Publication series

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UN SDGs

Keywords

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