BKG

Cahyoningtyas, Retno Ayu (2019) Metode Ward Dan Average Linkage Clustering Untuk Segmentasi Objek Wisata Di Malang Raya. Sarjana thesis, Universitas Brawijaya.

Indonesian Abstract

Analisis cluster merupakan teknik multivariat yang bertujuan untuk mengelompokkan objek-objek berdasarkan kemiripan karakteristik. Tujuan dari penelitian ini adalah melakukan pengelompokan objek wisata Malang Raya berdasarkan kepuasan wisatawan dengan menggunakan metode Ward dan Average Linkage Clustering. Selain itu, pada penelitian ini akan membandingkan hasil pengelompokan metode Ward dan Average Linkage berdasarkan rasio simpangan baku antar cluster dan dalam cluster. Teknik pengambilan sampel menggunakan metode nonprobability sampling dengan basis accidental sampling dan quota sampling. Ukuran sampel pada penelitian ini adalah 264 wisatawan yang terbagi di 17 objek wisata Malang Raya. Hasil analisis cluster menunjukkan bahwa berdasarkan indeks validitas cluster, jumlah cluster optimal pada metode Ward sebanyak lima cluster dan jumlah cluster optimal pada Average Linkage Clustering sebanyak tiga cluster. Berdasarkan nilai rasio simpangan baku antar cluster dan dalam cluster menunjukkan bahwa hasil pengelompokan metode Ward lebih baik dibandingkan hasil pengelompokan Average Linkage dengan nilai rasio sebesar 0,634. Hasil analisis cluster metode Ward adalah cluster satu terdiri dari empat objek wisata dengan kepuasan wisatawan tertinggi pada aspek environment, cluster dua terdiri dari empat objek wisata dengan kepuasan wisatawan tertinggi pada aspek dining, cluster tiga terdiri dari tiga objek wisata dengan kepuasan wisatawan tertinggi pada aspek lodging, cluster empat terdiri dari tiga objek wisata dengan kepuasan wisatawan tertinggi pada aspek dining dan cluster lima terdiri dari dua objek wisata dengan kepuasan wisatawan tertinggi pada aspek environment.

English Abstract

Cluster analysis is a multivariate technique that aims to classify objects based on characteristic similarities. The purpose of this study is to classify Malang attractions based on tourist satisfaction using the Ward and Average Linkage method. In addition, this research will compare the results of grouping of Ward method and Average Linkage based on standard deviation ratio between groups. The sampling technique used in this study is the nonprobability sampling method on the basis of accidental sampling and quota sampling. The sample size in this study was 264 tourists divided into 17 tourist attractions in Malang. The results of the analysis show that based on the cluster validity index, using Ward method, five clusters are selected as the optimal cluster and using Average Linkage method, three clusters are selected as the optimal cluster. Based on the ratio of standard deviation between clusters and in clusters, the results of Ward method is better than Average Linkage with ratio value of 0.634. Ward method group results are cluster one, consisting of four tourist objects with the highest satisfaction on environment aspect, cluster two consists of four tourist objects with the highest satisfaction on dining aspect, cluster three consists of three tourist objects with the highest satisfaction on lodging aspect, cluster four consists of three tourist objects with the highest satisfaction on dining aspect and cluster five consist of two tourist objects with the highest satisfaction on environment aspect.

Other Language Abstract

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Item Type: Thesis (Sarjana)
Identification Number: SKR/MIPA/2019/69/051910771
Uncontrolled Keywords: Analisis Cluster, Metode Ward, Average Linkage, Objek Wisata Malang Raya, Cluster Analysis, Ward’s Method, Average Linkage, Malang Raya Tourism Object
Subjects: 500 Natural sciences and mathematics > 519 Probabilities and applied mathematics > 519.5 Statistical mathematics > 519.53 Descriptive statistics, multivariate analysis, analysis of variance and covariance
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam > Statistika
Depositing User: Budi Wahyono
URI: http://repository.ub.ac.id/id/eprint/176834
Text
Retno Ayu Cahyoningtyas (3).pdf

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