?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=STUDI+PENGGUNAAN+UV-VIS+SPECTROSCOPY+DAN+METODE+SIMCA+%0D%0AUNTUK+KLASIFIKASI+MADU+HUTAN+BERDASARKAN+LETAK+%0D%0AGEOGRAFIS&rft.creator=MUHAMMAD+FEBRIANDIKA+ZAINI%2C+1514071051&rft.subject=630+Pertanian+dan+teknologi+yang+berkaitan&rft.description=The+quality+and+character+of+honey+is+determined+by+the+specific+flora+and+vegetation+%0D%0Ain+the+area+from+which+the+origin+of+honey+and+the+diversity+of+ecosystems+that+live+in+%0D%0Athe+area+and+the+geographical+origin+of+honey+are+often+associated+with+the+price+value+%0D%0Aof+honey.+In+addition+there+is+the+term+geographical+indication+in+the+world+of+%0D%0Amarketing%2C+which+has+a+function+as+an+identification+of+a+product+and+informs+that+the+%0D%0Aproduct+is+produced+from+a+certain+location+that+has+certain+qualities+and+%0D%0Acharacteristics.+Therefore%2C+this+research+was+conducted+to+find+a+way+to+classify+honey+%0D%0Atypes+based+on+their+geographical+location.%0D%0AThis+study+aims+to+identify+three+types+of+honey+based+on+their+geographical+location+%0D%0Ausing+UV-Vis+Spectroscopy+with+the+soft+method%0D%0Aindependent+modeling+of+class+analogy+(SIMCA).+The+composition+of+material+used+%0D%0Ain+this+study+is+1+ml+with+a+total+sample+of+100+Muara+Enim+multiflora+honey+samples+%0D%0A(MME)%2C+100+Jambi+multiflora+honey+samples+(MMJ)%2C+and+100+Riau+multiflora+honey%0D%0Avi%0D%0Asamples+(MMR).+The+honey+sample+is+preheated+using+a+waterbatch+at+60+%E2%84%83+for+30+%0D%0Aminutes%2C+then+1+ml+of+the+honey+sample+is+diluted+with+20+ml+of+distilled+water+and+%0D%0Astirred+for+10+minutes+using+a+magnetic+stirrer.+Furthermore%2C+2+ml+of+the+dilution+%0D%0Asample+is+put+into+the+cuvette+and+2+times+the+repetition+of+the+spectral+data+is+%0D%0Aanalyzed+using+UV-Vis+Spectrometer+(UV-Vis+Genesys+10s%2C+Thermo+Scientific%2C+%0D%0AUSA)+at+a+wavelength+of+190-1100+nm.+Then+the+spectra+data+obtained+are+analyzed+%0D%0Ausing+the+PCA+and+SIMCA+methods+using+The+Unscrambler+software+version+9.2.%0D%0AThe+classification+results+show+that+the+PCA+and+SIMCA+methods+are+able+to+%0D%0Adistinguish+MME%2C+MMJ%2C+and+MMR.+The+best+PCA+analysis+results+are+obtained+%0D%0Athrough+a+spectral+repair+process%2C+using+a+combination+of+multiplicative+scatter+%0D%0Acorrection+(MSC)+and+9+segment+moving+average+spectra+correction+methods%2C+at+a+%0D%0Awavelength+of+190-1100+nm+(full+wavelength).+In+the+development+of+MSC+and+9+%0D%0Asegment+moving+average+spectral+models%2C+the+PC1+value+of+91%25+and+PC2+of+8%25+%0D%0Ameans+that+the+total+of+the+two+PCs+is+99%25.+As+for+the+SIMCA+classification%2C+the+%0D%0Aaccuracy+value+(AC)+is+100%25%2C+the+sensitivity+value+(S)+is+100%25%2C+the+specificity+value+%0D%0A(SP)+is+100%25%2C+and+the+false+alarm+rate+(FP)+is+0%25+in+the+MME-MMJ+sample.+While+%0D%0Athe+MME-MMR+sample+has+an+accuracy+value+(AC)+of+100%25%2C+a+sensitivity+value+(S)+%0D%0Aof+100%25%2C+a+specificity+value+(SP)+of+100%25%2C+and+a+false+alarm+rate+(FP)+of+0%25%2C+and+an+%0D%0AMMJ-MMR+sample+has+an+accuracy+value+(AC)+of+100%25%2C+a+sensitivity+value+(S)+of+%0D%0A100%25%2C+a+specificity+value+(SP)+of+100%25%2C+and+an+error+value+(FP)+of+0%25.+Based+on+%0D%0AROC+curve+analysis+all+classifications+are+stated+as+excellent+classification.%0D%0Avii%0D%0AKeywords%3A+Honey%2C+Classification%2C+UV+Vis+Vis+Spectroscopy%2C+Principal+Component+%0D%0AAnalysis+(PCA)%2C+Soft+Independent+Modeling+of+Class+Analogy+(SIMCA).%0D%0AKualitas+dan+karakter+madu+ditentukan+oleh+flora+tertentu+dan+vegetasi+di+daerah+dari+%0D%0Amana+asal+madu+dan+keragaman+ekosistem+yang+hidup+di+daerah+tersebut+dan+asal+%0D%0Ageografis+madu+sering+dikaitkan+dengan+nilai+harga+dari+madu.+Di+samping+itu+%0D%0Aterdapat+istilah+indikasi+geografis+dalam+dunia+pemasaran%2C+yang+mempunyai+fungsi+%0D%0Asebagai+tanda+pengenal+dari+suatu+produk+dan+menginformasikan+bahwa+produk+%0D%0Atersebut+dihasilkan+dari+suatu+lokasi+tertentu+yang+mempunyai+kualitas+dan%0D%0Akarakteristik+tertentu.+Oleh+karena+itu%2C+dilakukan+penelitian+ini+untuk+mendapatkan+%0D%0Acara+mengklasifikasikan+jenis+madu+berdasarkan+letak+geografisnya.%0D%0APenelitian+ini+bertujuan+untuk+mengidentifikasi+tiga+jenis+madu+berdasarkan+letak+%0D%0Ageografisnya+dengan+menggunakan+UV-Vis+Spectroscopy+dengan+metode+soft+%0D%0Aiii%0D%0Aindependent+modelling+of+class+analogy+(SIMCA).+Komposisi+bahan+yang+digunakan%0D%0Adalam+penelitian+ini+yaitu+1+ml+dengan+jumlah+sampel+sebanyak+100+sampel+madu+%0D%0Amultiflora+Muara+Enim+(MME)%2C+100+sampel+madu+multiflora+Jambi+(MMJ)%2C+dan+100+%0D%0Asampel+madu+multiflora+Riau+(MMR).+Sampel+madu+dipanaskan+terlebih+dahulu+%0D%0Adengan+menggunakan+waterbatch+pada+suhu+60+%E2%84%83+selama+30+menit%2C+kemudian+1+ml+%0D%0Asampel+madu+diencerkan+dengan+aquades+sejumlah+20+ml+dan+diaduk+selama+10+menit%0D%0Amenggunakan+magnetic+stirrer.+Selanjutnya+2+ml+sampel+hasil+pengenceran%0D%0Adimasukkan+ke+dalam+kuvet+dan+diambil+data+spektranya+sebanyak+2+kali+%0D%0Apengulangan+dengan+menggunakan+UV-Vis+Spectrometer+(UV-Vis+Genesys+10s%2C+%0D%0AThermo+Scientific%2C+USA)+pada+panjang+gelombang+190%E2%80%93+1100+nm.Kemudian+data+%0D%0Aspektra+yang+diperoleh+dianalisis+menggunakan+metode+PCA+dan+SIMCA+%0D%0Amenggunakan+software+The+Unscrambler+versi+9.2.%0D%0AHasil+klasifikasi+menunjukkan+bahwa+metode+PCA+dan+SIMCA+mampu+membedakan+%0D%0AMME%2C+MMJ%2C+dan+MMR.+Hasil+analisis+PCA+terbaik+diperoleh+melalui+proses+%0D%0Aperbaikan+spektra%2C+dengan+menggunakan+metode+perbaikan+spektra+kombinasi+%0D%0Amultiplicative+scatter+correction+(MSC)+dan+moving+average+9+segmen%2C+pada+panjang+%0D%0Agelombang+190+%E2%80%93+1100+nm+(panjang+gelombang+penuh).+Pada+pengembangan+model+%0D%0Aspektra+kombinasi+MSC+dan+moving+average+9+segmen+menghasilkan+nilai+PC1+%0D%0Asebesar+91%25+dan+PC2+sebesar+8%25+yang+artinya+total+dari+kedua+PC+tersebut+sebesar+%0D%0A99%25.+Sedangkan+untuk+klasifikasi+SIMCA+diperoleh+nilai+akurasi+(AC)+sebesar+%0D%0A100%25%2C+nilai+sensitivitas+(S)+sebesar+100%25%2C+nilai+spesifitas+(SP)+sebesar+100%25%2C+dan+%0D%0Anilai+false+alarm+rate+(FP)+sebesar+0%25+pada+sampel+MME-MMJ.+Sedangkan+sampel+%0D%0Aiv%0D%0AMME-MMR+memliki+nilai+akurasi+(AC)+sebesar+100%25%2C+nilai+sensitivitas+(S)+sebesar+%0D%0A100%25%2C+nilai+spesifitas+(SP)+sebesar+100%25%2C+dan+nilai+false+alarm+rate+(FP)+sebesar+0%25%2C+%0D%0Adan+sampel+MMJ-MMR+memiliki+nilai+akurasi+(AC)+sebesar+100%25%2C+nilai+sensitivitas+%0D%0A(S)+sebesar+100%25%2C+nilai+spesifitas+(SP)+sebesar+100%25%2C+dan+nilai+error+(FP)+sebesar+0%25.%0D%0ABerdasarkan+analisis+kurva+ROC+seluruh+klasifikasi+dinyatakan+sebagai+excellent+%0D%0Aclassification.%0D%0AKata+Kunci%3A+Madu%2C+Klasifikasi%2C+UV-Vis+Spectroscopy%2C+Principal+Component+%0D%0AAnalysis+(PCA)%2C+Soft+Independent+Modelling+of+Class+Analogy+(SIMCA).%0D%0A&rft.publisher=FAKULTAS+PERTANIAN&rft.date=2019&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F56906%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F56906%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F56906%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++MUHAMMAD+FEBRIANDIKA+ZAINI%2C+1514071051++(2019)+STUDI+PENGGUNAAN+UV-VIS+SPECTROSCOPY+DAN+METODE+SIMCA+UNTUK+KLASIFIKASI+MADU+HUTAN+BERDASARKAN+LETAK+GEOGRAFIS.++FAKULTAS+PERTANIAN%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F56906%2F