Nurindriati, Yunita (2013) APLIKASI ANALISIS KLASTER TERHADAP SEGMENTASI PASAR PEMIRSA BERITA PROGRAM TELEVISI. S1 thesis, Universitas Pendidikan Indonesia.
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Abstract
Segmentasi Pasar adalah proses membagi sebuah pasar ke dalam kelompok-kelompok pembeli yang berbeda yang mungkin menghendaki pemasaran atau produk yang terpisah. Metode analisis yang dapat digunakan untuk melakukan proses segmentasi pasar berdasarkan ciri-ciri karakteristik yang dimilikinya adalah dengan metode Analisis Klaster. Analisis Klaster terdiri dua metode, yaitu klaster hirarki dan klaster non-hirarki. Karena dalam penelitian ini data yang digunakan sangat banyak, maka analisis klaster yang digunakan analisis klaster dengan metode K-Mean untuk mengelompokkan pemirsa program berita berdasarkan variabel-variabel dalam suatu berita seperti kekritisan berita, narasumber yang terpercaya, keanekaragaman berita, dinikmati oleh semua kalangan, jam tayang yang sesuai, kedalaman isi berita, bahasa yang mudah dimengerti, keaktualan berita, berita dapat dipercaya, berita disajikan secara menarik, penampilan penyaji berita dan durasi program sehingga terbentuk beberapa segmen pasar program berita. Hasil dari penelitian ini, segmentasi pasar terbagi menjadi 5 klaster. Klaster 1 memiliki pangsa pasar yang rata-rata memiliki karakteristik yang selalu mengkritisi setiap berita yang ditonton; Klaster 2 memiliki pangsa pasar yang rata-rata menyukai keaktualan berita dari setiap berita yang ditonton; Klaster 3 memiliki pangsa pasar yang rata-rata hanya menikmati setiap berita yang ada; Klaster 4 memiliki pangsa pasar yang rata-rata menyukai jika suatu berita dikemas atau disajikan secara menarik; dan Klaster 5 memiliki pangsa pasar yang rata-rata menyimak berita yang hanya bisa dinikmati oleh semua kalangan dan usia. Kata Kunci: Analisis Klaster, K-Means, Segmentasi Pasar. Market Segmentation is the process of dividing a market into groups of buyers who might require different or separate product marketing. Analytical methods that can be used to make the process of market segmentation based on the characteristics of its characteristics is the method of Cluster Analysis. Cluster analysis comprises two methods, namely hierarchical cluster and non-cluster hirarki. Karena in this study used data very much, then used cluster analysis, cluster analysis with K-Means methods to segment audiences based news program variables in the news as criticality news, sources are reliable, diversity news, enjoyed by all people, appropriate airtime, the depth of news content, easy to understand language, news actuality, trustworthy news, the news is presented in an interesting, news presenter appearance and duration programsehingga formed several segments market news program. Because the data in this study used very much, then used cluster analysis with K-Means method for classifying news program viewers based on variables such as criticality in a news story, sources are reliable, diversity news, enjoyed by all people, appropriate airtime, the depth of news content, easy to understand language, news actuality, trustworthy news, the news is presented in an interesting, news presenter appearance, and duration of the program to form a market segment of news programs. The results of this research, market segmentation is divided into 5 clusters. Cluster 1 has a market share on average have characteristics that always criticize any news that is watched; Cluster 2 has a market share on average like actuality news from any news that is watched; Cluster 3 has a market share on average just enjoying every news there; Cluster 4 has a market share on average like if a packed news or presented in an interesting, and Cluster 5 has a market share on average listening to the news that can only be enjoyed by all walks of life and ages. Keywords : Cluster Analysis, K-Means, Market Segmentation.
| Item Type: | Thesis (S1) |
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| Subjects: | Universitas Pendidikan Indonesia > Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Pendidikan Matematika |
| Divisions: | Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Pendidikan Matematika |
| Depositing User: | Riki N Library ICT |
| Date Deposited: | 27 Aug 2013 07:16 |
| Last Modified: | 27 Aug 2013 07:16 |
| URI: | http://repository.upi.edu/id/eprint/327 |
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