Prediksi Besaran Curah Hujan Menggunakan Metode Fuzzy Time Series

Desmonda, Diera; Tursina, Tursina; Irwansyah, Muhammad Azhar

doi:10.26418/justin.v6i4.27036

Cited by 15 publications

(15 citation statements)

References 4 publications

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“…In the case study of weather prediction, there are several tests that have been carried out by several figures using the fuzzy method, such as the Tsukamoto fuzzy , Adaptive Neuro Fuzzy Inference System (ANFIS), Time Series, and Sugeno [8], [9]. And each method has its own advantages and disadvantages.…”

Section: Issn: 2746-7686 mentioning

confidence: 99%

Rainfall Prediction in Blora Regency Using Mamdani's Fuzzy Inference System

Damayanti¹,

Wicaksono

Hakim

et al. 2022

JOSCEX

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In the case study of weather prediction, there are several tests that have been carried out by several figures using the fuzzy method, such as the Tsukamoto fuzzy, Adaptive Neuro Fuzzy Inference System (ANFIS), Time Series, and Sugeno. And each method has its own advantages and disadvantages. For example, the Tsukamoto fuzzy has a weakness, this method does not follow the rules strictly, the composition of the rules where the output is always crisp even though the input is fuzzy, ANFIS has the disadvantage of requiring a large amount of data. which is used as a reference for calculating data patterns and the number of intervals when calculating data patterns and Sugeno has the disadvantage of having less stable accuracy results even though some tests have been able to get fairly accurate results. In research on the implementation of the Mamdani fuzzy inference system method using the climatological dataset of Blora Regency to predict rainfall, it can be concluded as follows: (1) The fuzzy logic of the Mamdani method can be used to predict the level of rainfall in the city of Blora by taking into account the factors that affect the weather, including temperature, wind speed, humidity, duration of irradiation and rainfall. (2) Fuzzy logic for prediction with uncertain input values is able to produce crisp output because fuzzy logic has tolerance for inaccurate data. (3) The results of the accuracy of calculations using the Mamdani fuzzy inference system method to predict rainfall in Blora Regency are 66%.

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Section: Issn: 2746-7686 mentioning

confidence: 99%

Rainfall Prediction in Blora Regency Using Mamdani's Fuzzy Inference System

Damayanti¹,

Wicaksono

Hakim

et al. 2022

JOSCEX

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“…10, No. 1, April 2022 ISSN Cetak : 2338-4018 ISSN Online : 2620-7532 metode time series menganalisis dan menentukan pola data pada masa lampau yang dikumpulkan berdasarkan urutan waktu dan memproyeksikannya untuk mendapatkan prediksi di masa mendatang [1]. Dengan memanfaatkan data yang ada tersebut dan menerapkan metode tertentu dapat dilakukan suatu prediksi peramalan penjualan berupa seni dan ilmu pengetahuan dalam memprediksi peristiwa pada masa mendatang.…”

Section: Pendahuluanunclassified

Implementasi Metode Double Exponential Smoothing pada Prediksi Jumlah Penjualan Kain Pantai

Dorestin¹,

YS²,

Vulandari³

2022

TIKomSiN

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Y2K Batik is an SME (Small and Medium Enterprise) engaged in batik. Y2K Batik produces and sells beach wear with various motifs. One of the important things in business is inventory of merchandise, inventory of merchandise is a factor in determining the success of a trading company to achieve its goals, because the goods sold affect the level of income to increase company profits. With these considerations, it is necessary to analyze the production of beach wear for the availability of merchandise in fulfilling customer orders. Based on the above background, the scope of the problem in this study is master data collection obtained from records of selling beach batik cloth periodically from time to time. By utilizing the existing data and applying certain methods, a sales forecasting prediction can be made using the Double exponential Smoothing method. From the results of calculations and testing of forecasting data on the Mandala Motif Beach Fabric variable with the most optimal value using = 0.9 of 2127 with an error value of 19.46% and an accuracy rate of 80.54% (Good). The Canting Motif Beach Wear variable with the most optimal value using = 0.9 of 3174 with an error value of 3.61% and an accuracy rate of 96.39% (Very Good). Double Exponential Smoothing is the most widely used method to determine the trend equation of the second smoothing data through a smoothing process. The programming language uses Microsoft Visual Studio 2013 and the DBMS uses Microsoft SQL Server 2012. The purpose of this research is to create a system that can simplify the process of analyzing the production of beach wear in order to meet the availability of goods ordered by customers.

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“…Penelitian terkait prediksi curah hujan telah dilakukan oleh peneliti sebelumnya. Desmonda & Irwansyah (2018) melakukan penelitian yaitu memprediksi curah hujan di Provinsi Kalimantan Barat menggunakan metode Fuzzy Time Series (FTS) dengan hasil yang diperoleh adalah peramalan memiliki tingkat akurasi sebesar 99,849 %. Rahmawati et al, (2021) menggunakan Fuzzy Time Series Ruey Chyn Tsaur dalam meramalkan curah hujan di PPKS Sentang dengan perolehan hasil tingkat presisi akurasi metode sebesar 99,63 %.…”

Section: Pendahuluanunclassified

“…Hasil perhitungan curah hujan menggunakan FTS tidak menghasilkan akurasi yang baik, dengan nilai AFER sebesar 714,85 %. Hal ini berbeda dengan hasil penelitian Desmonda & Irwansyah (2018), Rahmawati et al, (2021), Julisman & Erlin (2014), dan Rachmawati & Anifah (2019) yang menyatakan bahwa FTS dapat dengan baik meramalkan curah hujan. Hasil AFER yang tinggi diperoleh karena rentang nilai dari curah hujan pada periode 2018 s.d 2020 sangat besar dan panjang kelas pada Tabel 3.…”

Section: Pembahasanunclassified

Rainfall Prediction Using Fuzzy Time Series

Susano

Anggraeni

2021

ncl

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Flood is one of the problems faced by DKI Jakarta Province. To be able to reduce losses caused by flooding is to predict rainfall. The type of research is quantitative research using rainfall prediction method using Fuzzy Time Series (FTS) which was developed by Stevenson & Porter (2009). The data used is rainfall data at Kemayoran Station in the period January 2018 to December 2020. The prediction accuracy results state that the FTS method has poor accuracy so that improvements are needed in the formation of interval intervals.

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Prediksi Besaran Curah Hujan Menggunakan Metode Fuzzy Time Series

Cited by 15 publications

References 4 publications

Rainfall Prediction in Blora Regency Using Mamdani's Fuzzy Inference System

Rainfall Prediction in Blora Regency Using Mamdani's Fuzzy Inference System

Implementasi Metode Double Exponential Smoothing pada Prediksi Jumlah Penjualan Kain Pantai

Rainfall Prediction Using Fuzzy Time Series

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