Temuan dalam penelitian ini memberikan beberapa saran yang terkait dengan saran mengenai prosedur evaluasi hasil pengukuran serta saran mengenai replikasi penelitian maupun kemungkinan peneltian lanjutan dari penelitian ini.
1. Melalui perbandingan ketepatan estimasi koefisien reliabilitas, didapatkan bahwa terdapat koefisien selain Koefisien Alpha yang juga memiliki ketepatan estimasi yang akurat. Penggunaan koefisien reliabilitas alternatif selain Koefisien Alpha perlu disosialisasikan untuk menambah khasanah kajian evaluasi hasil pengukuran. 2. Hasil penelitian ini menemukan bahwa ketepatan estimasi koefisien reliabilitas
tergatung pada model data yang hendak dianalisis. Oleh karena itu sebelum mengestimasi besarnya reliabilitas pengukuran, peneliti diharapkan mengidentifikasi model yang tepat dari data yang didapatkan. Pengujian model dilakukan dengan menggunakan Analisis Faktor Konfirmatori untuk melihat model mana yang tepat untuk menjelaskan variasi data hasil pengukuran yang dimiliki peneliti.
3. Selama ini evaluasi pengukuran di psikologi banyak berorientasi pada asumsi data yang unidimensi dengan mengestimasi reliabilitas berdasarkan semua butir tes
tanpa mengidentifikasi terlebih dahulu kemungkinan adanya kemajemukan dimensi data. Disarankan kepada peneliti yang hendak mengevaluasi hasil pengukuran untuk mengidentifikasi dahulu dimensionalitas data. Apabila ditemukan dimensi data yang majemuk, maka disarankan untuk menguji reliabilitas pada tiap-tiap dimensi. Salah satu cara yang dapat dipakai adalah dengan melakukan analisis faktor.
4. Penelitian ini menemukan bahwa Koefisien Alpha kurang sensitif terhadap kemajemukan dimensi data karena meskipun pada data yang memiliki dimensi majemuk (multidimensional) ditemukan bahwa Koefisien Alpha menghasilkan nilai estimasi reliabilitas yang tinggi. Hal ini dapat menyebabkan kesimpulan evaluasi hasil pengukuran menjadi bias. Oleh karena itu disarankan kepada para peneliti untuk mengidentifikasi dimensionalitas data yang dimiliki sebelum menggunakan Koefisien Alpha. Apabila ditemukan dimensi yang majemuk, disarankan untuk mengaplikasikan Koefisien Alpha pada masing-masing dimensi daripada pada butir secara keseluruhan.
5. Data simulasi dalam penelitian ini digenerasikan dengan menggunakan prosedur kajian semi Monte Carlo karena tidak melakukan replikasi pada pengambilan data sampel dari data populasi yang ditetapkan. Diharapkan kepada peneliti yang meneliti dengan tema yang sama untuk melakukan replikasi prosedur pengambilan sampel.
6. Terdapat beberapa koefisien reliabilitas tidak dilibatkan dalam penelitian ini sehingga diharapkan kepada peneliti yang melakukan penelitian dengan tema yang sama untuk melibatkan koefisien reliabilitas tersebut.
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LAMPIRAN
Lampiran A
A. MODEL PARALEL
Inter-Item Correlation Matrix
1.000 .036 -.165 -.128 -.019 -.113 .125 .221 .093 .097 .314 .036 1.000 -.154 -.060 .427 .009 .059 -.071 -.007 -.149 -.069 -.165 -.154 1.000 -.186 -.053 .167 -.238 -.293 -.039 .063 -.053 -.128 -.060 -.186 1.000 .016 -.090 -.210 -.015 -.154 -.087 -.126 -.019 .427 -.053 .016 1.000 -.185 -.127 .115 .082 -.079 .013 -.113 .009 .167 -.090 -.185 1.000 -.072 -.166 -.014 -.036 -.017 .125 .059 -.238 -.210 -.127 -.072 1.000 .579 .621 .448 .469 .221 -.071 -.293 -.015 .115 -.166 .579 1.000 .575 .584 .584 .093 -.007 -.039 -.154 .082 -.014 .621 .575 1.000 .586 .500 .097 -.149 .063 -.087 -.079 -.036 .448 .584 .586 1.000 .622 .314 -.069 -.053 -.126 .013 -.017 .469 .584 .500 .622 1.000 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5
The covariance matrix is calculated and used in the analysis.
B. MODEL TAU EQUIVALENT
Inter-Item Correlation Matrix
1.000 .014 .002 .025 -.023 -.008 .770 .780 .778 .728 .714 .014 1.000 -.019 .011 .023 -.002 .648 -.001 .018 .026 .008 .002 -.019 1.000 .006 .024 .000 -.010 .627 .005 .018 .001 .025 .011 .006 1.000 .012 .006 .026 .023 .647 .027 .022 -.023 .023 .024 .012 1.000 -.005 -.003 -.003 -.010 .669 -.020 -.008 -.002 .000 .006 -.005 1.000 -.008 -.006 -.002 -.009 .694 .770 .648 -.010 .026 -.003 -.008 1.000 .594 .604 .571 .549 .780 -.001 .627 .023 -.003 -.006 .594 1.000 .609 .578 .557 .778 .018 .005 .647 -.010 -.002 .604 .609 1.000 .572 .559 .728 .026 .018 .027 .669 -.009 .571 .578 .572 1.000 .518 .714 .008 .001 .022 -.020 .694 .549 .557 .559 .518 1.000 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5
1.000 -.012 -.016 -.023 -.014 .007 .744 .754 .751 .738 .738 -.012 1.000 -.004 -.007 -.003 .019 .660 -.011 -.014 -.011 .004 -.016 -.004 1.000 .001 -.014 -.013 -.015 .644 -.011 -.021 -.020 -.023 -.007 .001 1.000 -.006 .013 -.022 -.017 .644 -.021 -.008 -.014 -.003 -.014 -.006 1.000 .003 -.012 -.020 -.015 .665 -.008 .007 .019 -.013 .013 .003 1.000 .018 -.003 .014 .007 .680 .744 .660 -.015 -.022 -.012 .018 1.000 .559 .555 .547 .557 .754 -.011 .644 -.017 -.020 -.003 .559 1.000 .567 .550 .551 .751 -.014 -.011 .644 -.015 .014 .555 .567 1.000 .551 .560 .738 -.011 -.021 -.021 .665 .007 .547 .550 .551 1.000 .546 .738 .004 -.020 -.008 -.008 .680 .557 .551 .560 .546 1.000 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5
The covariance matrix is calculated and used in the analysis.
D. MODEL CORRELATED ERROR
Inter-Item Correlation Matrix
1.000 .013 -.009 -.010 .008 -.001 .875 .872 .871 .875 .873 .013 1.000 .497 .508 .500 .513 .495 .255 .261 .253 .262 -.009 .497 1.000 .252 .244 .238 .233 .482 .116 .110 .109 -.010 .508 .252 1.000 .257 .244 .237 .115 .482 .116 .110 .008 .500 .244 .257 1.000 .248 .249 .127 .134 .491 .128 -.001 .513 .238 .244 .248 1.000 .247 .115 .118 .119 .487 .875 .495 .233 .237 .249 .247 1.000 .881 .883 .883 .885 .872 .255 .482 .115 .127 .115 .881 1.000 .820 .821 .818 .871 .261 .116 .482 .134 .118 .883 .820 1.000 .824 .819 .875 .253 .110 .116 .491 .119 .883 .821 .824 1.000 .822 .873 .262 .109 .110 .128 .487 .885 .818 .819 .822 1.000 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5 T1 E1 E2 E3 E4 E5 X1 X2 X3 X4 X5
Lampiran B
Sampel Estimasi Reliabilitas a) Koefisien Alpha
b) Koefisien Guttman Lambda c) Koefisien Feldt
d) Koefisien Reliabilitas Maksimal e) Koefisien Revelle Beta
f) Koefisien HB Omega g) Koefisien Theta Armor
h) Koefisien Reliabilitas Komposit i) Koefisien Reliabilitas Konstrak
Reliability
Case Processing Summary
5000 100.0 0 .0 5000 100.0 Valid Excludeda Total Cases N %
Listwise deletion based on all variables in the procedure. a.
Reliability Statistics
.872 5
Cronbach's
Alpha N of Items
A. KOEFISIEN GUTTMAN LAMBDA (Program SPSS)
Reliability
Case Processing Summary
5000 100.0 0 .0 5000 100.0 Valid Excludeda Total Cases N %
Listwise deletion based on all variables in the procedure. a. Reliability Statistics .698 .883 .872 .795 .898 .871 5 1 2 3 4 5 6 Lambda N of Items
A B FORMULA
1. INPUT
2. Korelasi Antar Belahan 0.76
3. Varian Belahan 1 443.85
4. Varian Belahan 2 201.29
5. Varian Skor Total 1102.21
6. 7. Dev. Std. Belahan 1 21.07 8. Dev. Std. Belahan 2 14.19 9. Dev. Std. Belahan 2 33.20 10. 11. 12. 13. OUTPUT 14. KOEFISIEN FELDT 0.87 B14 = (4*B2*B7*B8)/(B5-(((B3-B4)/B9)^2))
C. KOEFISIEN RELIABILITAS MAKSIMAL (Program Microsoft Excel Diprogram Peneliti)
A B FORMULA
1. INPUT
2. Korelasi 0.765
3. Rerata Korelasi Belahan 1 0.530
4. Rerata Korelasi Belahan 2 0.584
5. 6. OUTPUT 7. Pembagi 1.374 B7 = B2/((B3*B4)^0.5) 8. Reliabilitas Maksimal 0.900 B8 = (((3*B3)/(1-B3))+((3*B4)/(1- B4)))/((((3*B3)/(1-B3))+((3*B4)/(1-B4)))+(2/(1+B7)))
D. KOEFISIEN REVELLE BETA (Program Microsoft Excel Diprogram Peneliti)
A B FORMULA
1. INPUT
2. Jumlah Butir 5
3. Rerata Kovarian Butir 11.05
4. Varian Skor Tes 306.77
5.
6. OUTPUT