Rainfall forecasting using triple exponential smoothing for rice cultivation in lamongan, jawa timur

Rice cultivation is a major agricultural activity that is heavily influenced by weather conditions. Extreme weather events, such as heavy rainfall, can cause farmers' productivity to decline. Rainfall forecasts are important for farmers to help them make the right decisions in managing their farming businesses. This research aims to predict rainfall in Lamongan Regency, East Java province, and provide valuable information to rice farmers to plan the optimal planting season. The method used in this study is Triple Exponential Smoothing (TES), an effective forecasting technique for processing time series data with seasonal patterns. Monthly rainfall data for the last five years formed the basis of the forecast, with data sourced from NASA's Power Data Access Viewer. The analysis results include a Mean Absolute Percentage Error (MAPE) value of 97.559% for rainfall. This rainfall forecast can assist farmers in increasing rice productivity and minimizing the risk of crop failure due to unpredictable weather conditions. With the rainfall weather forecast, farmers are expected to know the suitable months for rice cultivation so that productivity increases

Authors

Institutions

Publication Details

Journal
Journal of Soft Computing Exploration
Published
2025-03-17
DOI
https://doi.org/10.52465/joscex.v6i1.519
Primary Topic
Multimedia Learning Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rainfall forecasting using triple exponential smoothing for rice cultivation in lamongan, jawa timur

Maulida Ayu Fitriani, Dimara Kusuma Hakim, Elindra Ambar Pambudi, Shafrila Widyantri
Journal of Soft Computing Exploration
Multimedia Learning Systems
article

Rainfall forecasting using triple exponential smoothing for rice cultivation in lamongan, jawa timur

Maulida Ayu Fitriani, Dimara Kusuma Hakim, Elindra Ambar Pambudi, Shafrila Widyantri
article en

Abstract

Rice cultivation is a major agricultural activity that is heavily influenced by weather conditions. Extreme weather events, such as heavy rainfall, can cause farmers' productivity to decline. Rainfall forecasts are important for farmers to help them make the right decisions in managing their farming businesses. This research aims to predict rainfall in Lamongan Regency, East Java province, and provide valuable information to rice farmers to plan the optimal planting season. The method used in this study is Triple Exponential Smoothing (TES), an effective forecasting technique for processing time series data with seasonal patterns. Monthly rainfall data for the last five years formed the basis of the forecast, with data sourced from NASA's Power Data Access Viewer. The analysis results include a Mean Absolute Percentage Error (MAPE) value of 97.559% for rainfall. This rainfall forecast can assist farmers in increasing rice productivity and minimizing the risk of crop failure due to unpredictable weather conditions. With the rainfall weather forecast, farmers are expected to know the suitable months for rice cultivation so that productivity increases

Journal of Soft Computing ExplorationVol. 6(1)
Muhammadiyah University Purwokerto (ID)
Openalex Percentile: Top 90%
Multimedia Learning Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Rainfall forecasting using triple exponential smoothing for rice cultivation in lamongan, jawa timur — Maulida Ayu Fitriani, Dimara Kusuma Hakim, et al. · Journal of Soft Computing Exploration (2025) | TGRS Research Map | TGRS