1. Data Subjek

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55

Kategori

Subkategori

Jumlah

Persentase

Jenis Kelamin

Pria

148 37.4 %

Wanita

248 62.6 %

Usia

13 Tahun

1 0.25 %

14 Tahun

5 1.3 %

15 Tahun

101 25.5 %

16 Tahun

53 13.4 %

17 Tahun

26 6.6 %

18 Tahun

51 12.9 %

19 Tahun

77 19.4 %

20 Tahun

38 9.6 %

21 Tahun

26 6.6 %

22 Tahun

17 4.3 %

23 Tahun

1 0.25 %

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56

1. Tabulasi Respon Subjek terhadap Subtes RA Versi Revisi

(3)

(4)

(5)

(6)

(7)

(8)

(9)

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64

a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 a16 a17 a18 a19 a20

393 P/22/S1 1 1 1 0 1 1 1 1 1 0 1 0 1 0 1 1 0 0 0 1

394 P/22/S1 1 1 0 1 1 1 1 0 1 0 1 1 0 1 0 0 0 0 0 0

395 P/22/S1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 1

396 P/22/S1 1 1 0 0 1 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0

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65

1. Hasil Analisa Faktor Subtes RA Versi Revisi

Total Variance Explained

Compon

ent

Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

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66

1. Hasil Analisa Kecocokan Model dengan Data

> fit1<-rasch(winda, constraint=cbind(length(winda) +1, 1))

> summary(fit1)

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Model Summary:

log.Lik

AIC

BIC

-3027.575

6095.15

6174.779

Coefficients:

Dffclt.X17

5.1915

0.5125

10.1296

Dffclt.X18

5.1912

0.5124

10.1304

Dffclt.X19

3.7805

0.2789

13.5567

Dffclt.X20

5.1911

0.5124

10.1305

Dscrmn

1.0000

NA

Integration:

method: Gauss-Hermite

quadrature points: 21

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67

> GoF.rasch(fit1, B=395)

Bootstrap Goodness-of-Fit using Pearson chi-squared

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Tobs: 61849856

# data-sets: 396

p-value: 0.003

2. Hasil Analisa Indeks Kesukaran Aitem Subtes RA Versi Revisi

> coef(fit1, prob=TRUE, order=TRUE)

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68

(15)

(16)

(17)

(18)

(19)

73

4. Kurva Fungsi Informasi Aitem Subtes RA Versi Revisi

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74

6. Hasil Analisa Fungsi Informasi Aitem dan Tes Subtes RA Versi Revisi

> information(fit1, c(-4,4))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 19.97

Information in (-4, 4) = 15.27 (76.46%)

Based on all the items

> information(fit1, c(-4,4))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 19.97

Information in (-4, 4) = 15.27 (76.46%)

Based on all the items

> information(fit1, c(-4,4), items=c(1))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.74 (74.1%)

Based on items 1

> information(fit1, c(-4,4), items=c(2))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.93 (92.75%)

Based on items 2

> information(fit1, c(-4,4), items=c(3))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.96 (95.99%)

Based on items 3

> information(fit1, c(-4,4), items=c(4))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

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75 > information(fit1, c(-4,4), items=c(5))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.95 (94.89%)

Based on items 5

> information(fit1, c(-4,4), items=c(6))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.96 (96.39%)

Based on items 6

> information(fit1, c(-4,4), items=c(7))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.96 (96.17%)

Based on items 7

> information(fit1, c(-4,4), items=c(8))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.96 (96.24%)

Based on items 8

> information(fit1, c(-4,4), items=c(9))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.95 (95.37%)

Based on items 9

> information(fit1, c(-4,4), items=c(10))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

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76 > information(fit1, c(-4,4), items=c(11))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.96 (96.13%)

Based on items 11

> information(fit1, c(-4,4), items=c(12))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.73 (73.5%)

Based on items 12

> information(fit1, c(-4,4), items=c(13))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.87 (87.19%)

Based on items 13

> information(fit1, c(-4,4), items=c(14))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.84 (83.97%)

Based on items 14

> information(fit1, c(-4,4), items=c(15))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.68 (68.06%)

Based on items 15

> information(fit1, c(-4,4), items=c(16))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

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77 > information(fit1, c(-4,4), items=c(17))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 0.99

Information in (-4, 4) = 0.23 (23.48%)

Based on items 17

> information(fit1, c(-4,4), items=c(18))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 0.99

Information in (-4, 4) = 0.23 (23.48%)

Based on items 18

> information(fit1, c(-4,4), items=c(19))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 1

Information in (-4, 4) = 0.55 (55.53%)

Based on items 19

> information(fit1, c(-4,4), items=c(20))

Call:

rasch(data = winda, constraint = cbind(length(winda) + 1, 1))

Total Information = 0.99