LOGISTIC REGRESSION WITH ITEM RESPONSE THEORY (LRIRT): SENSITIVITY DETECTING DIFFERENTIAL ITEM FUNCTIONING
Kata Kunci:
Logistic Regression with IRT, differential item functioning, dif, biasAbstrak
Analisis butir sangat penting pada tes untuk mendapatkan informasi awal layak atau tidaknya suatu tes digunakan dalam penilaian. Salah satu kriteria baiknya suatu butir yaitu tidak terjadi diskriminasi atau menguntung pada golongan dalam menjawab benar suatu butir. Hal ini disebut dengan perbedaan fungsi butir disebut differential item functioning (DIF). Tujuan penelitian ini, apakah metode LRIRT lebih sensitif mendeteksi DIF dengan 2000 responden daripada 200 responden. Metode penelitian yang digunakan yaitu desain eksperimen, analisis yang digunakan two independent samples t-test. Data penelitian menggunakan hasil ujian nasional (UN) 2015. Hasil penelitian pertama,metode LRIRT lebih sensitif mendeteksi perbedaan fungsi butir (DIF) yang menggunakan 2000 responden daripada 200 responden. Kesimpulannya, metode LRIRT lebih sensitit deteksi DIF pada ukuran sampel 2000 daripada ukuran sampel 200
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