PERBANDINGAN REGRESI LOGISTIK MULTINOMINAL DAN ANALISIS DISKRIMINAN
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Keywords

Analisis Diskriminan
Regresi Logistik
Multinominal
Keputusan Mengunjungi

How to Cite

Nabila, R., Himmati, R., & Erdkhadifa, R. (2021). PERBANDINGAN REGRESI LOGISTIK MULTINOMINAL DAN ANALISIS DISKRIMINAN. Ar Rehla: Journal of Islamic Tourism, Halal Food, Islamic Traveling, and Creative Economy, 1(2), 135-150. https://doi.org/10.21274/ar-rehla.v1i2.4820

Abstract

Abstrak: Tujuan dari penelitian ini adalah untuk membandingkan analisis regresi logistik multinomial dan analisis diskriminan untuk mengelompokkan keputusan kunjungan wisata halal di Jawa Tengah berdasarkan ketepatan pengelompokan. Analisis statistik yang digunakan adalah regresi logistik multinomial dan analisis diskriminan. Kedua analisis tersebut dapat digunakan sebagai metode pengelompokan objek, sehingga keduanya dapat dibandingkan berdasarkan ketepatan pengelompokkannya. Penelitian ini membandingkan analisis regresi logistik multinomial dan analisis diskriminan dalam pengelompokan keputusan kunjungan wisata halal. Data yang digunakan adalah worship facilities, halalness, general Islamic mortality, dan tourism destination image. Hasil analisis menggunakan metode regresi logistik multinomial menunjukkan faktor-faktor yang secara signifikan mempengaruhi pengelompokan keputusan kunjungan wisata halal adalah variabel tourism destination image, variabel halalness, dan variabel general Islamic morality. Sedangkan dengan analisis diskriminan menunjukkan bahwa semua variabel prediktor yakni worship facilities, halalness, general Islamic mortality, dan tourism destination image memberikan pengaruh secara signifikan terhadap pengklasifikasian keputusan mengunjungi destinasi wisata halal. Penelitian ini menunjukkan bahwa metode regresi logistik multinomial lebih baik untuk pengelompokkan keputusan kunjungan wisata halal dibandingan metode analisis diskriminan, dengan presetnase ketepatan pengelompokkan pada metode regresi logit multinomial sebesar 59,5%  dan analisis diskriminan sebesar 53,5%. Analisis regresi logistik multinominal lebih mudah digunakan dalam proses pengelompokan keputusan kunjuangan wisata halal karena tidak mempertimbangkan asumsi yang harus dipenuhi.

Kata Kunci: Analisis Diskriminan; Regresi Logistik Multinominal; Keputusan Mengunjungi

 

Abstract: The purpose of this study is to compare multinomial logistic regression analysis and discriminant analysis to classify decisions on halal tourism visits in Central Java based on grouping accuracy. Statistical analysis used is multinomial logistic regression and discriminant analysis. The two analyzes can be used as a method of grouping objects, so that they can be compared based on the accuracy of the grouping. This study compares multinomial logistic regression analysis and discriminant analysis in grouping decisions for halal tourism visits. The data used are worship facilities, halalness, general Islamic mortality, and tourism destination image. The results of the analysis using the multinomial logistic regression method show that the factors that significantly influence the grouping of decisions for halal tourism visits are the tourism destination image variable, the halalness variable, and the general Islamic morality variable. Meanwhile, discriminant analysis shows that all predictor variables namely worship facilities, halalness, general Islamic mortality, and tourism destination image have a significant influence on the classification of decisions to visit halal tourist destinations. This study shows that the multinomial logistic regression method is better for grouping decisions on halal tourist visits than the discriminant analysis method, with a preset percentage of grouping accuracy in the multinomial logit regression method of 59.5% and discriminant analysis of 53.5%. Multinominal logistic regression analysis is easier to use in the process of grouping halal tourism travel decisions because it does not consider the assumptions that must be met.

Keywords: Discriminant Analysis; Multinomial Logistic Regression; Visiting decision.

https://doi.org/10.21274/ar-rehla.v1i2.4820
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