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PEMODELAN MATEMATIKA. Kudang B. Seminar. KARAKTERISTIK BUAH JERUK KEPROK GARUT MELALUI PEMODELAN RANGKAIAN LISTRIK YANG DIDASARKAN PADA SIFAT RESISTIF DAN KAPASITIFNYA (J. Juansah , W. Budiastra , K. Dahlan , K.B. Seminar 2013).

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PEMODELAN MATEMATIKA

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## PEMODELAN MATEMATIKA

Kudang B. Seminar

KARAKTERISTIK BUAH JERUK KEPROK GARUT MELALUI PEMODELAN RANGKAIAN LISTRIK YANG DIDASARKAN PADA SIFAT RESISTIF DAN KAPASITIFNYA (J. Juansah, W. Budiastra, K. Dahlan, K.B. Seminar 2013)

### PenurunanRumus Dari Model

INTERPRETASI: Hal itujugamenjadipertimbanganbahwabijidominanresistif, sementarakulit, SACS, danbuahutuhmemilikikomponenkapasitif

### Coefficient of Determination

The coefficient of determination, denoted R2 and pronounced R squared, indicates how well data points fit a line or curve.

### PengukuranAkurasi Model

The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation (MAPD), is a measure of accuracy of a method for constructing fitted time series values in statistics, specifically in trend estimation. It usually expresses accuracy as a percentage, and is defined by the formula:

At :The actual value Ft :The forecast value

The root-mean-square deviation (RMSD) or root-mean-square error (RMSE) is a frequently used measure of the differences between values predicted by a model or an estimator and the values actually observed. The RMSD serves to aggregate the magnitudes of the errors in predictions for various times into a single measure of predictive power. RMSD is a good measure of accuracy, but only to compare forecasting errors of different models for a particular variable and not between variables, as it is scale-dependent.

: predicted values for times t

: regression dependent variable

Koefisendeterministik (a), MAPE (b), dan RMSE (c) padahasilsimulasiuntuk model barupadabeberapatingkatkeasaman (pH). Nilai parameter impedansi (Z/m), reaktansi (X/m), danresistansi (R/m) dalamorde

### HubunganantaraResistensidan Tingkat KeasamanJerukKeprok

INTERPRETASI: Makin tinggitingkatkeasamanmakinrendahnilairesistensinya.

### HubunganantaraResistensidan Tingkat KekerasanJerukKeprok

INTERPRETASI: Makin tinggitingkatkekerasanmakintingginilairesistensinya.

HubunganantaraKapasitansidan Tingkat KeasamanJerukKeprok

INTERPRETASI: Makin tinggitingkatkeasamanmakintingginilaikapasitansinya.

HubunganantaraKapasitansidan Tingkat KeasamanJerukKeprok

INTERPRETASI: Makin tinggitingkatkekerasanmakinrendahnilaikapasitansinya.

NilaiKomponen Internal BerdasarkanHasilKomputasi Model Yang Dikembangkan

### KesimpulanPengamatan

• InterpretasisifatlistrikmemberipeluangdankesempatanuntukmeninjauperilakukematanganJerukKeprokGarut.

• Taksatu pun dari model listrikmampumemprediksisemuaperubahanperilakusecarasempurna.

• Model yang dikembangkanJuansahet almemilikikinerjaakurasi yang lebihbaikdibandingkanmodel Hayden danZhang

• Pembentukan model listriktelahmembantupemahamankitatentangkarakteristikbuahJerukKeprokGarut.

• Perubahankekerasandankeasamandalambuah-buahandiikutidenganperubahankapasitansimembrandanresistansikomponenjaringanpenyusunbuah.