Judul: Perbandingan Hasil Penggerombolan Metode K-Means, Fuzzy K-Means, dan Two Step Cluster
Abstrak: The main principle of cluster analysis is to classify objects into clusters based on similarity measures. K-means and fuzzy k-means can be classified as popular clustering methods, which are suitable for large data with continuous variables. However, a new method has been developed to be used for large data, that is the two step cluster method. This method allows processing data with different types of variables, which in this case are continuous and categorical. The aim of this research is to compare the clustering results of k-means, fuzzy kmeans, and two step cluster method, in order to determine the ideal number of clusters for each method. This research uses hypotetical data taken from SPSS software, which fit the purpose to compare several methods. The results of this study show that in the case of two clusters, k-means and fuzzy k-means methods have more similarities with respect to the number objects in clusters, whereas the two step method gives unequal number of objects in clusters. All methods show that 2 clusters is an ideal number. It is influenced by the ratio between mean squares within clusters, which is smaller than the ratio in the case of 3 and 4 clusters.
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Judul: Perbandingan metode fuzzy c-means dan K-Means pada analisis gerombol
Abstrak: Salah satu metode penggerombolan tak berhirarki yang umum digunakan dalam analisis gerombol ialah metode K-Means yaitu suatu metode yang digunakan untuk mengelompokkan sekumpulan objek ke dalam beberapa gerombol dan banyaknya gerombol awal telah ditentukan sebelumnya dimana tingkat keanggotaannya bernilai 1 bagi anggota gerombol dan bernilai 0 bagi objek yang bukan anggota gerombol. Metode K-Means berkembang menjadi metode Fuzzy CMeans (FCM) dimana untuk menentukan objek masuk dalam suatu gerombol (tingkat keanggotaan) digunakan logika fuzzy yang nilainya berkisar antara 0 hingga 1. Semakin dekat objek terhadap pusat gerombol, maka tingkat keanggotaannya akan semakin mendekati 1 dan mendekati 0 untuk sebaliknya. Pada penelitian ini ingin diketahui ketepatan metode Fuzzy CMeans dan K-Means dalam menggerombolkan data pada beberapa kondisi data dengan membandingkan hasil penggerombolan kedua metode tersebut. Metode Fuzzy C-Means menggunakan besaran tingkat kesamaran. Tingkat kesamaran yang baik besarnya sekitar 2. Sehubungan dengan hal itu, pada penelitian ini juga ingin diketahui pengaruh tingkat kesamaran pada metode Fuzzy C-Means. Data yang digunakan pada penelitian ini ialah 3 set data bangkitan yang masing-masing set terdiri dari 3 gerombol dengan kondisi (1) ketiga gerombol terpisah (jarak jauh), (2) ketiga gerombol beririsan (jarak sedang), dan (3) ketiga gerombol bercampur (jarak dekat). Adapun banyaknya data yang akan digerombolkan dengan kondisi tersebut sebanyak 600 data, 150 data, dan 30 data. Pada kondisi ketiga gerombol terpisah dan kondisi ketiga gerombol beririsan metode K-Means lebih tepat digunakan. Sedangkan pada kondisi ketiga gerombol bercampur metode Fuzzy C-Means lebih tepat digunakan. Pengaruh tingkat kesamaran pada metode Fuzzy C-Means berpengaruh pada tingkat keanggotaan, semakin tinggi tingkat kesamaran yang dipilih akan mengakibatkan tingkat keanggotaan objek pada gerombol sebenarnya akan mengalami penurunan. Sebaliknya, tingkat keanggotaan objek pada gerombol yang salah akan semakin meningkat. Tingkat kesamaran pada metode Fuzzy C-Means memberikan tingkat keanggotaan yang sesuai pada tingkat kesamaran 2 dan 2.25.
Keyword: Analisis Gerombol, K-Means, Fuzzy C-Means, Bogor Agricultural University

Judul: Manajemen Pemeliharaan Kuda (Equus caballus) Untuk Upacara Kenegaraan Dan Sarana Kesenjataan Di Detasemen Kavaleri Berkuda (DenKavkud) TNI-AD Parongpong
Abstrak: Cavalry Horse Detachement (Denkavkud) Indonesian National Army-Cavalary Parongpong is one of the Indonesian military units that utilize the horse and train it as a means of purpose of formal state ceremony and armed forces. Skills possessed by the horse cavalry was the result of care management and specialized training provided by the trainer. Aspects of care management are breeding, feeding, and management. Horses that are kept in the Denkavkud, Parongpong are stallions, mares, foals, and military horses. Total populations of horses at Denkavkud are 183 horses. Besides commited horse training (remonte), Denkavkud also did breeding program to produce horses that can be trained and used as a military horse. There are some issues contained in Denkavkud, such as some of the nutrients needed by the horses not being met from feed given. One of these is crude protein and lysine. Lactation mares was crude protein and lysine deficiency. The number of death in 2010 is higher than previous years. Based on the number of horses that died from January until June 2010 is 11 horses. The average mortality was caused by colic. Colic is caused by excessive eating, excessive drinking during hot, moldy food, and even by investment roundworms. Animal welfare in Denkavkud can be enhanced by improvement of feed given and improving the health of livestock through improved sanitation.
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