{"id":"https://openalex.org/W2909656340","doi":"https://doi.org/10.1109/icecos.2018.8605254","title":"Artificial Neural Network for Health Data Forecasting, Case Study: Number of Dengue Hemorrhagic Fever Cases in Malang Regency, Indonesia","display_name":"Artificial Neural Network for Health Data Forecasting, Case Study: Number of Dengue Hemorrhagic Fever Cases in Malang Regency, Indonesia","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2909656340","doi":"https://doi.org/10.1109/icecos.2018.8605254","mag":"2909656340"},"language":"en","primary_location":{"id":"doi:10.1109/icecos.2018.8605254","doi":"https://doi.org/10.1109/icecos.2018.8605254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecos.2018.8605254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Electrical Engineering and Computer Science (ICECOS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051188898","display_name":"Wiwik Anggraeni","orcid":"https://orcid.org/0000-0003-3010-3062","observed_orcids":["https://orcid.org/0000-0003-3010-3062"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Wiwik Anggraeni","raw_affiliation_strings":["Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012515029","display_name":"Graha Pramudita","orcid":"https://orcid.org/0000-0002-4025-7826","observed_orcids":["https://orcid.org/0000-0002-4025-7826"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Graha Pramudita","raw_affiliation_strings":["Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035922042","display_name":"Edwin Riksakomara","orcid":"https://orcid.org/0000-0002-5008-5319","observed_orcids":["https://orcid.org/0000-0002-5008-5319"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Edwin Riksakomara","raw_affiliation_strings":["Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058879549","display_name":"Radityo P.W.","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Radityo P.W.","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember, Surabaya, Jawa Timur, ID"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember, Surabaya, Jawa Timur, ID","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015523148","display_name":"Febriliyan Samopa","orcid":"https://orcid.org/0000-0002-6590-1710","observed_orcids":["https://orcid.org/0000-0002-6590-1710"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Febriliyan Samopa","raw_affiliation_strings":["Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110645801","display_name":"Pujiadi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pujiadi","raw_affiliation_strings":["Disease Eradication, Malang Regency Public Health Office, Malang, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Disease Eradication, Malang Regency Public Health Office, Malang, Indonesia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041099339","display_name":"Renny Sari Dewi","orcid":"https://orcid.org/0000-0003-0153-3098","observed_orcids":["https://orcid.org/0000-0003-0153-3098"]},"institutions":[{"id":"https://openalex.org/I4210120051","display_name":"Universitas Internasional Semen Indonesia","ror":"https://ror.org/02tmeqq57","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210120051"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Renny Sari Dewi","raw_affiliation_strings":["Department of Information Systems, Universitas Internasional Semen Indonesia, Gresik, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Universitas Internasional Semen Indonesia, Gresik, Indonesia","institution_ids":["https://openalex.org/I4210120051"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.5179,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.98332561,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10166","display_name":"Mosquito-borne diseases and control","score":0.8101000189781189,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10166","display_name":"Mosquito-borne diseases and control","score":0.8101000189781189,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T14053","display_name":"Dengue and Mosquito Control Research","score":0.11779999732971191,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.019600000232458115,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dengue-hemorrhagic-fever","display_name":"dengue hemorrhagic fever","score":0.9980000257492065},{"id":"https://openalex.org/keywords/dengue-case-forecasting","display_name":"dengue case forecasting","score":0.8679999709129333},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.878000020980835},{"id":"https://openalex.org/keywords/disease-surveillance","display_name":"disease surveillance","score":0.4869999885559082},{"id":"https://openalex.org/keywords/spatial-visualization","display_name":"spatial visualization","score":0.37700000405311584},{"id":"https://openalex.org/keywords/google-maps-api","display_name":"Google Maps API","score":0.968999981880188},{"id":"https://openalex.org/keywords/meteorological-conditions","display_name":"weather conditions","score":0.6190000176429749},{"id":"https://openalex.org/keywords/aedes","display_name":"Aedes","score":0.7020000219345093},{"id":"https://openalex.org/keywords/malang-regency","display_name":"Malang Regency","score":0.8669999837875366},{"id":"https://openalex.org/keywords/community-health-centers","display_name":"community health centers","score":0.7239999771118164}],"concepts":[{"id":"https://openalex.org/C533803919","wikidata":"https://www.wikidata.org/wiki/Q30953","display_name":"Dengue fever","level":2,"score":0.8667429089546204},{"id":"https://openalex.org/C2984671231","wikidata":"https://www.wikidata.org/wiki/Q30953","display_name":"Dengue hemorrhagic fever","level":4,"score":0.781961977481842},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45727992057800293},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.4248253405094147},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.34975937008857727},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3249736726284027},{"id":"https://openalex.org/C2779635636","wikidata":"https://www.wikidata.org/wiki/Q476209","display_name":"Dengue virus","level":3,"score":0.27559900283813477},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2292494773864746},{"id":"https://openalex.org/C159047783","wikidata":"https://www.wikidata.org/wiki/Q7215","display_name":"Virology","level":1,"score":0.17912828922271729}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icecos.2018.8605254","doi":"https://doi.org/10.1109/icecos.2018.8605254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecos.2018.8605254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Electrical Engineering and Computer Science (ICECOS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.9476000070571899,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W100138691","https://openalex.org/W1984510198","https://openalex.org/W2050964555","https://openalex.org/W2092514020","https://openalex.org/W2170583027","https://openalex.org/W2221703650","https://openalex.org/W2346227481","https://openalex.org/W2471218770","https://openalex.org/W2522137359","https://openalex.org/W2526020668","https://openalex.org/W2569662569","https://openalex.org/W2609228256","https://openalex.org/W2780163769","https://openalex.org/W2791180597","https://openalex.org/W4231980566","https://openalex.org/W4293376381"],"related_works":["https://openalex.org/W2564898725","https://openalex.org/W3112773955","https://openalex.org/W2911481247","https://openalex.org/W7065443565","https://openalex.org/W2317268086","https://openalex.org/W4408493611","https://openalex.org/W3195387801","https://openalex.org/W4298006600","https://openalex.org/W3140885983","https://openalex.org/W4391900596"],"abstract_inverted_index":{"Dengue":[0],"Hemorrhagic":[1],"Fever":[2],"(DHF)":[3],"has":[4],"become":[5],"one":[6,26,54],"of":[7,27,39,55,107,141,161,176,220,228,231,253,262,266],"the":[8,13,33,36,46,49,73,80,105,114,117,135,139,148,159,174,197,199,206,215,221,229,251,264],"most":[9],"deadly":[10],"diseases":[11],"in":[12,22,29,42,48,59,113,164,179,193,256],"world.":[14,50],"Diseases":[15],"caused":[16],"by":[17],"Aedes-type":[18],"mosquitoes":[19],"are":[20,173,202],"found":[21],"many":[23],"tropical":[24],"countries,":[25],"them":[28],"Indonesia.":[30,60],"Indonesia":[31],"becomes":[32],"country":[34],"with":[35,93,225],"highest":[37,47],"number":[38,106,160,175,230,252],"DHF":[40,94],"cases":[41,109,143,163,178,233,255],"ASEAN,":[43],"even":[44],"among":[45],"Malang":[51,119,165,194,257],"Regency":[52,258],"is":[53,65,82,102,155],"dengue":[56,108,142,162,177,254],"endemic":[57],"areas":[58],"DHF's":[61],"current":[62],"handling":[63],"strategy":[64],"more":[66],"reactive":[67],"than":[68],"anticipatory.":[69],"As":[70],"a":[71,226,235,240,246],"result,":[72],"opportunity":[74],"to":[75,91,103,137,146,157,217],"prevent":[76],"transmission":[77],"and":[78,127,190,259],"control":[79],"epidemic":[81],"reduced.":[83],"On":[84],"this":[85],"basis,":[86],"efforts":[87],"should":[88],"be":[89,100],"made":[90],"deal":[92],"cases.":[95,267],"One":[96],"effort":[97],"that":[98,110,248],"can":[99,123,249],"done":[101],"predict":[104,158,250],"will":[111],"occur":[112],"future.":[115],"With":[116],"forecasting,":[118,198],"District":[120],"Health":[121,188],"Office":[122],"immediately":[124],"formulate":[125],"strategies":[126],"take":[128],"precautions":[129],"quickly.":[130],"Also":[131],"required":[132],"visualization":[133,260],"on":[134,234],"map":[136,238],"show":[138],"spread":[140,265],"so":[144],"easy":[145],"do":[147],"analysis.":[149],"Artificial":[150],"Neural":[151],"Network":[152],"Method":[153],"(ANN)":[154],"used":[156,170],"Regency.":[166,195],"The":[167,210],"independent":[168],"variables":[169],"as":[171],"input":[172],"each":[180,219],"neighboring":[181],"Puskesmas":[182,222],"(Pusat":[183],"Kesehatan":[184],"Masyarakat":[185],"or":[186],"Community":[187],"Centers)":[189],"weather":[191],"conditions":[192],"After":[196],"results":[200],"obtained":[201],"then":[203],"visualized":[204],"using":[205],"Google":[207,211,236],"Maps":[208,212,237],"API.":[209],"API":[213],"provides":[214],"ability":[216],"display":[218],"points":[223],"along":[224],"description":[227],"forecasting":[232],"through":[239],"web":[241],"browser.":[242],"This":[243],"research":[244],"produced":[245],"model":[247],"capable":[261],"displaying":[263]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-01-25T00:00:00"}