RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA
Rainfall is very influential in daily life, including in agriculture. According to the Jember Regency Government, the majority of the economic activities of the Jember people come from the agricultural sector. Significant changes in rainfall conditions will adversely affect the agricultural sphere....
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Universitas Pattimura
2023-09-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8997 |
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| author | Abduh Riski Wakhidatun Nafi’u Haqqi Ahmad Kamsyakawuni |
| author_facet | Abduh Riski Wakhidatun Nafi’u Haqqi Ahmad Kamsyakawuni |
| author_sort | Abduh Riski |
| collection | DOAJ |
| description | Rainfall is very influential in daily life, including in agriculture. According to the Jember Regency Government, the majority of the economic activities of the Jember people come from the agricultural sector. Significant changes in rainfall conditions will adversely affect the agricultural sphere. The Water Resources Office of Jember Regency measures rainfall directly. Precipitation measurement can also be made indirectly using the Global Satellite Mapping of Precipitation (GSMaP), a project promoted by the Japan Aerospace Exploration Agency (JAXA) to produce rainfall accumulation globally. Rainfall predictions are urgently needed to address rainfall-related issues. The Adaptive Neuro-Fuzzy Inference System (ANFIS) method is an effective method for prediction because its working principle combines adaptive methods of artificial neural networks and fuzzy logic. The RMSE in the ANFIS training and testing process on daily rainfall was 12.7464 and 14.6268. Furthermore, RMSE in ANFIS training and testing on monthly rainfall was 7.6336 and 8.1456. The predicted daily rainfall in Jember Regency on January 1, 2023, is 3.1971 mm. Meanwhile, the predicted monthly rainfall in Jember Regency in January 2023 is 19.9114 mm. |
| format | Article |
| id | doaj-art-375fdd6dbfb84d30b6c9334c57256df5 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-375fdd6dbfb84d30b6c9334c57256df52025-08-20T04:00:55ZengUniversitas PattimuraBarekeng1978-72272615-30172023-09-011731713172410.30598/barekengvol17iss3pp1713-17248997RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATAAbduh Riski0Wakhidatun Nafi’u Haqqi1Ahmad Kamsyakawuni2Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Jember, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, University of Jember, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, University of Jember, IndonesiaRainfall is very influential in daily life, including in agriculture. According to the Jember Regency Government, the majority of the economic activities of the Jember people come from the agricultural sector. Significant changes in rainfall conditions will adversely affect the agricultural sphere. The Water Resources Office of Jember Regency measures rainfall directly. Precipitation measurement can also be made indirectly using the Global Satellite Mapping of Precipitation (GSMaP), a project promoted by the Japan Aerospace Exploration Agency (JAXA) to produce rainfall accumulation globally. Rainfall predictions are urgently needed to address rainfall-related issues. The Adaptive Neuro-Fuzzy Inference System (ANFIS) method is an effective method for prediction because its working principle combines adaptive methods of artificial neural networks and fuzzy logic. The RMSE in the ANFIS training and testing process on daily rainfall was 12.7464 and 14.6268. Furthermore, RMSE in ANFIS training and testing on monthly rainfall was 7.6336 and 8.1456. The predicted daily rainfall in Jember Regency on January 1, 2023, is 3.1971 mm. Meanwhile, the predicted monthly rainfall in Jember Regency in January 2023 is 19.9114 mm.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8997predictionrainfalladaptive neuro fuzzy inference system (anfis)gsmap |
| spellingShingle | Abduh Riski Wakhidatun Nafi’u Haqqi Ahmad Kamsyakawuni RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA Barekeng prediction rainfall adaptive neuro fuzzy inference system (anfis) gsmap |
| title | RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA |
| title_full | RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA |
| title_fullStr | RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA |
| title_full_unstemmed | RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA |
| title_short | RAINFALL PREDICTION IN JEMBER REGENCY WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON GSMaP SATELLITE DATA |
| title_sort | rainfall prediction in jember regency with adaptive neuro fuzzy inference system based on gsmap satellite data |
| topic | prediction rainfall adaptive neuro fuzzy inference system (anfis) gsmap |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8997 |
| work_keys_str_mv | AT abduhriski rainfallpredictioninjemberregencywithadaptiveneurofuzzyinferencesystembasedongsmapsatellitedata AT wakhidatunnafiuhaqqi rainfallpredictioninjemberregencywithadaptiveneurofuzzyinferencesystembasedongsmapsatellitedata AT ahmadkamsyakawuni rainfallpredictioninjemberregencywithadaptiveneurofuzzyinferencesystembasedongsmapsatellitedata |