?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=MODEL+SEASONAL+AUTOREGRESSIVE+INTEGRATED+MOVING%0D%0AAVERAGE+(SARIMA)+PADA+PERAMALAN+METODE+FUZZY+TIME%0D%0A%0D%0ASERIES+MARKOV+CHAIN+(FTS-MC)&rft.creator=GINDA+ATI+SUWANDI%2C+1717031064&rft.subject=500+ilmu+pengetahuan+alam+dan+matematika&rft.description=Metode+SARIMA+merupakan+pengembangan+dari+metode+Box-Jenkins+(ARIMA).%0D%0AModel+SARIMA+dapat+mengatasi+pola+musiman+dari+suatu+periode+waktu.+Model%0D%0Aini+memerlukan+beberapa+pendekatan+seperti+asumsi+kestasioneran%2C+pembedaan%0D%0A(differencing)%2C+dan+transformasi+data.+Namun%2C+pendekatan+ini+masih+belum%0D%0Amampu+mengurangi+nilai+kesalahan+model%2C+akibatnya+akan+mendapatkan+hasil%0D%0Aperamalan+dengan+error+yang+besar.+Pada+proses+peramalan+model+FTS-MC%0D%0Aterdapat+perhitungan+nilai+penyesuaian+yang+bertujuan+untuk+mengurangi+besarnya%0D%0Apenyimpangan+hasil+peramalan.+Penelitian+ini+bertujuan+untuk+mengetahui+apakah%0D%0Ametode+fuzzy+time+series+Markov+chain+dapat+memperbaiki+hasil+peramalan+model%0D%0ASARIMA.+Berdasarkan+hasil+penelitian+diperoleh+model+ARIMA(0%2C1%2C1)(1%2C1%2C1)12%0D%0Asebagai+model+terbaik+yang+akan+digunakan+untuk+peramalan+bulan+Januari+2015+%E2%80%93%0D%0AJuli+2016.+Hasil+peramalan+bulan+Juli+2016+akan+digunakan+sebagai+proses%0D%0Aperamalan+FTS-MC.+Nilai+MAPE+yang+diperoleh+dari+kedua+model+sama-sama%0D%0Adibawah+10%25+yang+berarti+hasil+peramalan+sangat+baik.+Namun%2C+nilai+MAPE+dari%0D%0Ametode+FTS-MC+lebih+kecil+dibandingkan+model+SARIMA.+Hal+ini+menunjukkan%0D%0Abahwa+metode+FTS-MC+dapat+memperbaiki+hasil+peramalan+model+SARIMA.%0D%0A%0D%0AKata+kunci%3A+fuzzy+time+series%2C+fuzzy+time+series+markov+chain%2C+SARIMA%0D%0AThe+SARIMA+method+is+a+development+of+the+Box-Jenkins+(ARIMA)+method.%0D%0AThe+SARIMA+model+can+overcome+the+seasonal+pattern+at+a+period+of+time.+This%0D%0Amodel+requires+several+approaches+such+as+stationarity+assumption%2C+differencing%2C%0D%0Aand+data+transformation.+However%2C+this+approach+is+still+not+able+to+reduce+the%0D%0Aerror+value+of+the+model%2C+as+a+result+it+will+get+forecasting+results+with+errors+large.%0D%0AIn+the+process+of+forecasting+the+FTS-MC+model+there+is+a+calculation+of+the%0D%0Aadjustment+value+which+aims+to+reduce+the+magnitude+of+the+deviation+of+the%0D%0Aforecasting+results.+This+study+aims+to+determine+whether+the+method+fuzzy+time%0D%0Aseries+Markov+chain+can+improve+the+forecasting+results+of+the+SARIMA+model.%0D%0ABased+on+the+research+results%2C+ARIMA(0%2C1%2C1)(1%2C1%2C1)12+model+is+the+best+model+to%0D%0Abe+used+for+forecasting+January+2015+%E2%80%93+July+2016.+The+forecasting+results+for+July%0D%0A2016+will+be+used+as+the+FTS-MC+forecasting+process.+The+MAPE+values%0D%0Aobtained+from+both+models+are+both+below+10%25%2C+which+means+the+forecasting%0D%0Aresults+are+very+good.+However%2C+the+MAPE+value+of+the+FTS-MC+method+is%0D%0Asmaller+than+the+SARIMA+model.+This+shows+that+the+FTS-MC+method+can%0D%0Aimprove+the+forecasting+results+of+the+SARIMA+model.%0D%0A%0D%0AKeywords%3A+fuzzy+time+series%2C+fuzzy+time+series+markov+chain%2C+SARIMA&rft.publisher=FAKULTAS+MATEMATIKA+ILMU+PENGETAHUAN+ALAM&rft.date=2021&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61743%2F1%2FABSTRAK-ABSTRACT%2520-%2520GINDA.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61743%2F2%2FSKRIPSI%2520FULL%2520-%2520GINDA.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61743%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN%2520-%2520GINDA.pdf&rft.identifier=++GINDA+ATI+SUWANDI%2C+1717031064++(2021)+MODEL+SEASONAL+AUTOREGRESSIVE+INTEGRATED+MOVING+AVERAGE+(SARIMA)+PADA+PERAMALAN+METODE+FUZZY+TIME+SERIES+MARKOV+CHAIN+(FTS-MC).++FAKULTAS+MATEMATIKA+ILMU+PENGETAHUAN+ALAM%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F61743%2F