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PENGELOMPOKKAN DATA WAJAH MENGGUNAKAN METODE AGGLOMERATIVE CLUSTERING DENGAN ANALISIS KOMPONEN UTAMA Altien J. Rindengan 1) dan Deiby Tineke Salaki 1) 1) Program Studi Matematika FMIPA Universitas Sam Ratulangi Manado 95115 ABSTRAK Pada penelitian ini dilakukan analisis pengelompokkan data wajah dengan analisis komponen utama untuk mengambil beberapa akar ciri yang cukup mewakili data tersebut dan pengelompokkannya menggunakan metode agglomerative clustering. Dengan menggunakan program Matlab, data wajah yang terdiri dari 6 orang dengan 10 image dapat dikelompokkan sesuai data aslinya.  Pengelompokkannya cukup menggunakan 3 akar ciri pada selang 68 %. Kata kunci: agglomerative clustering , analisis komponen utama, data wajah FACE DATA CLUSTERING USING AGGLOMERATIVE CLUSTERING METHODS WITH PRINCIPAL COMPONENT ANALYSIS ABSTRACT In this research, face data is grouped using principal component analysis by getting some of its eigenvalues which are representative enough to describe the data and then by using agglomerative clustering the data is clustered.  By running the Matlab program, face data which is consist of 6 people with 10 images can be clustered to fit the original data.  The clustering is enough using 3 eigenvalues with 68 % of interval. Keywords: agglomerative clustering, principal component analysis, face data