[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126204-en":3,"doc-seo-126204-105":31,"detail-sidebar-cat-0-en-105":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126204,549768702563,"Sage","https://ap-avatar.wpscdn.com/avatar/8000c4aa63b76e948b?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786536092046926083",8,"Research & Report","Advancing precision in air quality forecasting through machinelearning integration","Environmental concerns are increasing, making air quality forecasting a key instrument to reduce pollution-related harm to public health and ecosystems. Urban activity in places like Bandar Lampung can intensify pollution, so more advanced forecasting approaches are needed to support mitigation. This study compares LSTM and Prophet for long short-term air quality prediction using data from January 12, 2022 to November 9, 2023, showing LSTM delivers lower errors and higher reliability for monitoring and policymaking.","# Article Info          \n\nArticle history:  \nReceived Mar 21,2024Revised Feb 12,2025Accepted Mar 15,2025  \n# Keywords:\n\nAir quality  \nForecasting  \nMachine learning  \nPrecision  \nPublic health  \n# Corresponding Author:\n\nMuhamad Komarudin  \n# 1.  INTRODUCTION\n\n# Advancing precision in air quality forecasting through machinelearning integration\n\nMuhamad Komarudin¹²,Sri Ratna Sulistiyanti¹,Suharso³,Muhammad Irsyad⁴,Hery Dian Septama¹,Titin Yulianti¹,Ali Sophian⁵,Michel¹  \nDepartment ofElectrical and Informatics Engineering.Faculty ofEngineering.University ofLampung.Bandar Lampung.Indonesia²Environmental Science Graduate School,University of Lampung.Bandar Lampung.Indonesia  \n³Department of Chemistrv.Faculty of Mathematics andNatural Sciences.University ofLampung.Bandar Lampung.IndonesiaDepartment of Mechanical Engineering.Faculty of Engineering.University ofLampung.Bandar Lampung.Indonesia⁵Department of Mechatronics Engineering.International Islamic University Malaysia,Selangor,Malaysia  \n## ABSTRACT                             \n\nIn an era where environmental concerms are escalating,air quality forecastingemerges.Forecasting is a crucial tool for addressing the adverse impacts ofpollution on public health and ecosystems.In urban centers like BandarLampung,economic activities intensify pollution levels.This conditionleveraging advanced machine leaning forecasting methods can significantlymitigate these effects.This study evaluates the precision of long short-termmemory (LSTM)and Prophet methods in predicting air quality.This studyutilizes data from January 12,2022 to November 9,2023.The results reveal adistinct advantage of the LSTM method over the Prophet.The LSTM methodshowcases superior accuracy across all evaluation metrics.Specifically,theLSTM method achieved an average root mean squared error (RMSE)of 5.38,mean absolute error (MAE)of 3.94,and mean absolute percentage error(MAPE)of 0.07.In contrast,the Prophet method recorded higher error rates,with an average RMSE of 18.48,MAE of 15.61,and MAPE of 0.25.Thesenumbers underscore the LSTM method's robustness and reliability inforecasting air quality.The result highlights its potential as a pivotal resourcefor environmental monitoring and policymaking to safeguard public health andpromote sustainable urban development.  \nThis is an open access article under the CC BY-SA license  \nEnvironmental Science Graduate School and Department of Electrical and Informatics Engineering,Faculty of Engineering,University of LampungBandar Lampung,IndonesiaEmail:m.komarudin@eng.unila.ac.id  \nAir pollution is a major environmental issue affecting public health,ecosystems,and climate.Thisissue makes it critical to implement proper monitoring and control strategies [1].The presence of dust,smoke,gases,and water vapor pollutants contributes to air pollution.It can lead to short-term and long-termdiseases in various body systems.This disease may impact the respiratory tract,heart,eyes,skin,andreproductive and nervous systems [2].Particulate matter,nitrogen dioxide,sulfur dioxide,and ground-levelozone are the primary air pollutants responsible for various illnesses [3].Exposure to these pollutants canresult in respiratory diseases,strokes,lung diseases,cardiovascular diseases,liver and blood diseases,andother health issues [4].The inhalation of particulate matter and gaseous pollutants can cause pulmonaryinflammation,chronic obstructive pulmonary disease,heart rate variability,ischemic heart disease,mentaland behavior disorders,and insulin resistance [5].The effects of air pollution on health depend on various  \nfactors,such as pollutant concentrations,chemical properties,age,general health,duration of exposure,weather conditions,and distance from emission sources.Urbanization,industrialization,and globalizationhave increased air pollution,particularly in developing countries [6].Other issues include rapid urbanization,industrialization,vehicular emissions,and deforestation.These sources emit a wide ra","cbCaitfdoQ6BoHR0","https://ap.wps.com/l/cbCaitfdoQ6BoHR0","pdf",4770381,5,1,17,"English","en",105,"# 1. INTRODUCTION\n# Advancing precision in air quality forecasting through machinelearning integration\n## ABSTRACT\n## Article Info\n## Keywords","[{\"question\":\"What forecasting methods are evaluated for air quality prediction?\",\"answer\":\"The study evaluates long short-term memory (LSTM) and Prophet methods for predicting air quality accuracy.\"},{\"question\":\"Which method achieves better precision, and what metrics support this?\",\"answer\":\"LSTM shows a distinct advantage over Prophet across all evaluation metrics, including average RMSE 5.38, MAE 3.94, and MAPE 0.07 versus Prophet’s RMSE 18.48, MAE 15.61, and MAPE 0.25.\"},{\"question\":\"What dataset period is used to build and test the models?\",\"answer\":\"The study uses data from January 12, 2022 to November 9, 2023.\"}]","Advancing precision in air quality forecasting through machinelearning integration | PDF",1785903779,43,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"advancing-precision-in-air-quality-forecasting-through-machine-learning-integration","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/advancing-precision-in-air-quality-forecasting-through-machine-learning-integration/126204/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-24","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"What forecasting methods are evaluated for air quality prediction?","Question",{"text":77,"@type":78},"The study evaluates long short-term memory (LSTM) and Prophet methods for predicting air quality accuracy.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"Which method achieves better precision, and what metrics support this?",{"text":82,"@type":78},"LSTM shows a distinct advantage over Prophet across all evaluation metrics, including average RMSE 5.38, MAE 3.94, and MAPE 0.07 versus Prophet’s RMSE 18.48, MAE 15.61, and MAPE 0.25.",{"name":84,"@type":75,"acceptedAnswer":85},"What dataset period is used to build and test the models?",{"text":86,"@type":78},"The study uses data from January 12, 2022 to November 9, 2023.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":20,"slug":139},19,"General","general"]