[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-290302-105":59,"doc-detail-290302-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","rainfall-prediction-model-in-semarang-city-using-machine-learning-neural-network-regression-performance-study","Rainfall prediction model in Semarang City using machine learning - Neural network regression performance study","","Rainfall shows an erratic pattern in Semarang City, strongly affecting daily activities and disaster preparedness. Excessive rainfall has contributed to floods and related impacts such as soil erosion, vegetation loss, and infrastructure damage during 2018–2020. This study builds a regression-based machine learning approach using daily rainfall data from BMKG, comparing multiple linear regression, random forest regression, and replicated neural networks. Model quality is evaluated with MAE and RMSE, yielding RMSE 13.055 and MAE 6.621, with the neural network performing best.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/rainfall-prediction-model-in-semarang-city-using-machine-learning-neural-network-regression-performance-study/290302/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/rainfall-prediction-model-in-semarang-city-using-machine-learning-neural-network-regression-performance-study/290302.png","ImageObject",300,407,{"name":92,"@type":93},"Olivia Brown","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-27","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why is rainfall prediction important for Semarang City?","Question",{"text":113,"@type":114},"Rainfall affects residents' daily activities and can trigger natural disasters such as floods, soil erosion, and house collapse. Better forecasts support community preparedness and reduce losses.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What machine learning regression algorithms are used in the study?",{"text":118,"@type":114},"The study uses multiple linear regression, random forest regression, and replicated neural networks to predict daily rainfall amounts for Semarang City.",{"name":120,"@type":111,"acceptedAnswer":121},"How is the model performance evaluated?",{"text":122,"@type":114},"Performance is measured using mean absolute error (MAE) and root mean squared error (RMSE). The reported results are RMSE 13.055 and MAE 6.621.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290302,1789641278,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":39,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":46,"preview_page_count":4},16904993612988,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Rainfall prediction model in Semarang City using machine  \nlearning  \nCarissa Devina Usman1, Aris Puji Widodo2, Kusworo Adi3, Rahmat Gernowo3  \n1Department of Mathematics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia 2Department of Informatics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia 3Department of Physics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia  \n\n| Article history:\u003Cbr>Received Jun 16, 2022 Revised Jan 20, 2023 Accepted Jan 23, 2023 | The erratic distribution of rainfall greatly affects people's daily activities, especially in Semarang City, so it is necessary to predict rainfall. Correct prediction of rainfall can improve community preparedness in dealing with natural disasters. Algorithms for machine learning and data mining have been extensively utilized in research involving rainfall data from various regions. The primary objectives ofthis study are to find the best regression algorithm and use machine learning algorithms to predict rainfall in Semarang. The dataset used is daily rainfall data for the City of Semarang from the meteorological, climatological, and geophysical agency (BMKG) . Machine learning algorithms such as multiple linear regression, random forest regression, and replicated neural networks will be used to conduct regression analysis on this dataset. The mean absolute error and Root mean squared error techniques are utilized to evaluate the performance of machine learning algorithms. With an error rate of 13.055 for root mean squared error (RMSE) and 6.621 for mean absolute error (MAE), the results of the research indicate that the performance of the neural network algorithm is superior to that of other algorithms.\u003Cbr>This is an open access article under the CC BY-SA license.\u003Cbr>|\n| --- | --- |\n| Keywords:\u003Cbr>Artificial neural network Machine learning Multiple linear regression Rainfall prediction Random forest regression |  |\n\nCorresponding Author:  \nAris Puji Widodo  \nDepartment of Informatics, Faculty of Science and Mathematics, Diponegoro University Semarang, Indonesia  \nEmail: [arispw@gmail.com](arispw@gmail.com)  \nArticle Info ABSTRACT  \n1. INTRODUCTION  \nResidents' day-to-day activities are significantly impacted by rainfall. Additionally, a variety of natural disasters that are certain to cause harm to residents can be brought on by severe rains. According to disaster data from the Semarang City regional disaster management body (BPBD) for the years 2018, 2019, and 2020, excessive rainfall has resulted in a variety of natural disasters, including floods, soil erosion, plant death, and house collapse. The socio-economic impact of rain ought to be examined because its effects range from disruptions in displacement networks to the destruction of flood-affected infrastructure [1] . Rainfall forecasts were also required in another study to mitigate the effects of falling agricultural production rates [2] . Therefore, increasing community preparedness, particularly in the Semarang City, Indonesia, region, necessitates calculating the amount of rainfall.  \nCloudy, light rain, medium rain, heavy rain, very heavy rain, and excessive rain are the six types of rain, according to the meteorological, climatological, and geophysical agency (BMKG) . agency. Rainfall amounts range from 0 to 0.5 millimeters per day in overcast conditions to 0.5 to 20 millimeters per day in light rain, 20 to 50 millimeters per day in medium rain, 50 to 100 millimeters per day in heavy rain, 100 to 150 millimeters per day in very heavy rain, and more than 150 millimeters per day in extreme rain. As a result, the  \nkind of rain that will fall can also be predicted if one day the severity of the rainfall is known. The minimum temperature, maximum temperature, general temperature, humidity, length of sunlight, maximum wind speed, general wind speed, and wind direction are some of the variables that can be used to assess the","cbCaiew4D2izCvXh","https://ap.wps.com/l/cbCaiew4D2izCvXh","pdf",539389,"English","# ABSTRACT\n# 1. INTRODUCTION\n## Rainfall impact and disaster context\n## Rainfall type and variables\n## Machine learning approach and regression\n## Related work\n# Article methodology and objectives","[{\"question\":\"Why is rainfall prediction important for Semarang City?\",\"answer\":\"Rainfall affects residents' daily activities and can trigger natural disasters such as floods, soil erosion, and house collapse. Better forecasts support community preparedness and reduce losses.\"},{\"question\":\"What machine learning regression algorithms are used in the study?\",\"answer\":\"The study uses multiple linear regression, random forest regression, and replicated neural networks to predict daily rainfall amounts for Semarang City.\"},{\"question\":\"How is the model performance evaluated?\",\"answer\":\"Performance is measured using mean absolute error (MAE) and root mean squared error (RMSE). The reported results are RMSE 13.055 and MAE 6.621.\"}]","Rainfall prediction model in Semarang City using machine learning - Neural network regression performance study | PDF"]