{"id":"https://openalex.org/W7202099280","doi":"https://doi.org/10.5815/ijwmt.2026.04.02","title":"Artificial Neural Network-Based Time Series Forecasting for Higher Education Enrollment: A Case Study of NEMSU\u2013Cantilan Campus","display_name":"Artificial Neural Network-Based Time Series Forecasting for Higher Education Enrollment: A Case Study of NEMSU\u2013Cantilan Campus","publication_year":2026,"publication_date":"2026-08-08","ids":{"openalex":"https://openalex.org/W7202099280","doi":"https://doi.org/10.5815/ijwmt.2026.04.02"},"language":"en","primary_location":{"id":"doi:10.5815/ijwmt.2026.04.02","doi":"https://doi.org/10.5815/ijwmt.2026.04.02","is_oa":true,"landing_page_url":"https://doi.org/10.5815/ijwmt.2026.04.02","pdf_url":"https://www.mecs-press.org/ijwmt/ijwmt-v16-n4/IJWMT-V16-N4-2.pdf","source":{"id":"https://openalex.org/S2506422076","display_name":"International Journal of Wireless and Microwave Technologies","issn_l":"2076-1449","issn":["2076-1449","2076-9539"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Microwave Technologies","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.mecs-press.org/ijwmt/ijwmt-v16-n4/IJWMT-V16-N4-2.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5146869768","display_name":"Ariel A. Dormendo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405282484","display_name":"North Eastern Mindanao State University-Cantilan","ror":"https://ror.org/05xa5xf96","country_code":"PH","type":"education","lineage":["https://openalex.org/I246982481","https://openalex.org/I4405282484"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Ariel A. Dormendo","raw_affiliation_strings":["Department of Computer Studies, North Eastern Mindanao State University, Cantilan, Surigao del Sur, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Studies, North Eastern Mindanao State University, Cantilan, Surigao del Sur, Philippines","institution_ids":["https://openalex.org/I4405282484"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047332386","display_name":"Esmael Verano Maliberan","orcid":"https://orcid.org/0000-0002-5554-2152","observed_orcids":["https://orcid.org/0000-0002-5554-2152"]},"institutions":[{"id":"https://openalex.org/I246982481","display_name":"North Eastern Mindanao State University","ror":"https://ror.org/043jfav91","country_code":"PH","type":"education","lineage":["https://openalex.org/I246982481"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Esmael V. Maliberan","raw_affiliation_strings":["Department of Computer Studies, North Eastern Mindanao State University, Tandag City, Surigao del Sur, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Studies, North Eastern Mindanao State University, Tandag City, Surigao del Sur, Philippines","institution_ids":["https://openalex.org/I246982481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"4","first_page":"16","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.0027000000700354576,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/neural-network","display_name":"artificial neural networks","score":0.722000002861023},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.8989999890327454},{"id":"https://openalex.org/keywords/computer-science-program","display_name":"computer science program","score":0.6169999837875366},{"id":"https://openalex.org/keywords/enrollment-growth","display_name":"student enrollment growth","score":0.6000000238418579},{"id":"https://openalex.org/keywords/lagged-features","display_name":"lagged features","score":0.6880000233650208},{"id":"https://openalex.org/keywords/holt-winters-exponential-smoothing","display_name":"Holt-Winters exponential smoothing","score":0.9419999718666077},{"id":"https://openalex.org/keywords/arima","display_name":"ARIMA","score":0.9520000219345093},{"id":"https://openalex.org/keywords/multi-step-forecasting","display_name":"multi-step forecasting","score":0.722000002861023},{"id":"https://openalex.org/keywords/university-enrollment-planning","display_name":"university enrollment planning","score":0.4560000002384186},{"id":"https://openalex.org/keywords/information-technology-programs","display_name":"information technology programs","score":0.4490000009536743},{"id":"https://openalex.org/keywords/forecasting-accuracy-comparison","display_name":"forecast accuracy comparison","score":0.35199999809265137},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.4129999876022339},{"id":"https://openalex.org/keywords/prophets","display_name":"prophets","score":0.7919999957084656}],"concepts":[{"id":"https://openalex.org/C2777626052","wikidata":"https://www.wikidata.org/wiki/Q516445","display_name":"Bachelor","level":2,"score":0.7728999853134155},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.6888999938964844},{"id":"https://openalex.org/C133710760","wikidata":"https://www.wikidata.org/wiki/Q775837","display_name":"Exponential smoothing","level":2,"score":0.6252999901771545},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.5760999917984009},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5641999840736389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5163999795913696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47290000319480896},{"id":"https://openalex.org/C2993868924","wikidata":"https://www.wikidata.org/wiki/Q163727","display_name":"Bachelor degree","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4438999891281128},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4359999895095825},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.4320000112056732},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C120912362","wikidata":"https://www.wikidata.org/wiki/Q136822","display_name":"Higher education","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C2993955422","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Science and engineering","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3944000005722046},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3603000044822693},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.3490999937057495},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2781206393","wikidata":"https://www.wikidata.org/wiki/Q2748419","display_name":"Academic achievement","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2728999853134155},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26330000162124634},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C2778498041","wikidata":"https://www.wikidata.org/wiki/Q915466","display_name":"Academic year","level":2,"score":0.2572000026702881}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5815/ijwmt.2026.04.02","doi":"https://doi.org/10.5815/ijwmt.2026.04.02","is_oa":true,"landing_page_url":"https://doi.org/10.5815/ijwmt.2026.04.02","pdf_url":"https://www.mecs-press.org/ijwmt/ijwmt-v16-n4/IJWMT-V16-N4-2.pdf","source":{"id":"https://openalex.org/S2506422076","display_name":"International Journal of Wireless and Microwave Technologies","issn_l":"2076-1449","issn":["2076-1449","2076-9539"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Microwave Technologies","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5815/ijwmt.2026.04.02","doi":"https://doi.org/10.5815/ijwmt.2026.04.02","is_oa":true,"landing_page_url":"https://doi.org/10.5815/ijwmt.2026.04.02","pdf_url":"https://www.mecs-press.org/ijwmt/ijwmt-v16-n4/IJWMT-V16-N4-2.pdf","source":{"id":"https://openalex.org/S2506422076","display_name":"International Journal of Wireless and Microwave Technologies","issn_l":"2076-1449","issn":["2076-1449","2076-9539"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Microwave Technologies","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202099280.pdf","grobid_xml":"https://content.openalex.org/works/W7202099280.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2016210396","https://openalex.org/W2969150539","https://openalex.org/W3000639279","https://openalex.org/W3035738233","https://openalex.org/W4293192357","https://openalex.org/W4391560655","https://openalex.org/W4393191474","https://openalex.org/W4403566126","https://openalex.org/W4408636620","https://openalex.org/W4414439432"],"related_works":["https://openalex.org/W4391560655","https://openalex.org/W7160278165","https://openalex.org/W4408300874","https://openalex.org/W4308084261","https://openalex.org/W4385279064","https://openalex.org/W4409567591","https://openalex.org/W3191107393","https://openalex.org/W7133776284","https://openalex.org/W2183255214","https://openalex.org/W7164005997"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,67,124,136,151,199,227,272,307,327],"machine":[4],"learning-based":[5],"model":[6],"designed":[7],"to":[8,169,187,194,207,219,258,267,287,298],"forecast":[9],"trends":[10,323],"in":[11,13,28,35,43,192,217,265,279,292,320,324,337,342],"enrollment":[12,54,174,278],"the":[14,24,59,93,98,114,145,209,231,239,243,253,276,280,293,301,313,343],"Department":[15,281],"of":[16,26,33,41,51,111,142,225,242,282,296,304,317],"Computer":[17,29,36,283],"Studies":[18,284],"at":[19,147],"NEMSU\u2013Cantilan":[20],"Campus,":[21],"specifically":[22],"for":[23,64,76,167,171,330],"Bachelor":[25,32,40],"Science":[27,30,34,42],"(BSCS),":[31],"Engineering":[37],"(BSCpE),":[38],"and":[39,66,82,88,117,129,133,139,238,315,334,340],"Information":[44],"Technology":[45],"(BSIT)":[46],"programs.":[47,181],"Twenty":[48],"semesters":[49,62],"(2015\u20132025)":[50],"historical":[52,234],"program-level":[53],"were":[55],"chronologically":[56],"split,":[57],"with":[58,230],"most":[60,210],"recent":[61,249],"withheld":[63],"validation,":[65],"lagged":[68],"feature":[69],"set":[70],"(Lag":[71],"1\u2013Lag":[72],"3)":[73],"was":[74],"constructed":[75],"an":[77,104],"Artificial":[78],"Neural":[79],"Network":[80],"(ANN)":[81],"benchmarked":[83],"against":[84,135],"Holt-Winters":[85,115],"Exponential":[86],"Smoothing":[87],"ARIMA,":[89],"both":[90],"tuned":[91],"on":[92,121],"same":[94],"training":[95],"split.":[96],"Employing":[97],"ANN":[99,146],"model,":[100],"this":[101,122,148,158,248],"study":[102],"achieved":[103],"aggregate":[105],"Mean":[106],"Absolute":[107],"Percentage":[108],"Error":[109],"(MAPE)":[110],"3.62%,":[112],"outperforming":[113],"(25.59%)":[116],"ARIMA":[118],"(31.09%)":[119],"baselines":[120],"dataset,":[123],"ranking":[125],"corroborated":[126],"by":[127,196,222,269,300],"RMSE":[128],"MAE":[130],"(Table":[131,154],"6)":[132],"confirmed":[134],"small":[137],"LSTM":[138],"Prophet,":[140],"neither":[141],"which":[143,246],"outperformed":[144],"sample":[149],"size;":[150],"per-program":[152],"breakdown":[153],"7),":[155],"however,":[156],"shows":[157],"advantage":[159],"is":[160,185,205,256,285],"not":[161],"uniform,":[162],"ranging":[163],"from":[164,189,214,262,289],"3.93%":[165],"MAPE":[166],"BSCS":[168,183],"13.48%":[170],"BSIT.":[172],"The":[173,182,202],"projections":[175],"indicate":[176],"consistent":[177,229],"growth":[178,250],"across":[179],"all":[180],"program":[184,204,255],"likely":[186],"increase":[188,224],"297":[190],"students":[191,216,221,264,291],"2025":[193,218,266,297],"401":[195],"2028,":[197,270,305],"exhibiting":[198],"35%":[200],"growth.":[201],"BSIT":[203],"projected":[206],"experience":[208],"significant":[211],"expansion,":[212],"growing":[213],"1,078":[215],"2,714":[220],"2028-an":[223],"151%,":[226],"trend":[228],"program\u2019s":[232],"sharp":[233],"acceleration":[235],"after":[236],"2022":[237],"recursive":[240],"nature":[241],"multi-step":[244],"forecast,":[245],"compounds":[247],"forward.":[251],"Meanwhile,":[252],"BSCpE":[254],"expected":[257,286],"grow":[259],"more":[260],"gradually,":[261],"153":[263],"186":[268],"showing":[271],"21.6%":[273],"increase.":[274,309],"Overall,":[275],"total":[277],"rise":[288],"1,517":[290],"second":[294],"semester":[295,303],"3,031":[299],"first":[302],"marking":[306],"100%":[308],"These":[310],"findings":[311],"highlight":[312],"accuracy":[314],"adaptability":[316],"ANN-based":[318],"models":[319],"capturing":[321],"nonlinear":[322],"enrollment,":[325],"offering":[326],"valuable":[328],"tool":[329],"strategic":[331],"planning,":[332],"faculty":[333],"classroom":[335],"allocation":[336],"state":[338],"universities":[339],"colleges":[341],"Philippines.":[344]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-10T00:00:00"}