Judul: Sensitivitas Ukuran Amatan Model Autoregresi Fuzzy
Abstrak: The conventional time series modelling method is Autoregressive Integrated Moving Average (ARIMA). ARIMA method is more effective if it is applied in long time periode of observations that at least 50 observations. Tseng on 2001, introduced Fuzzy ARIMA method to deal time series modelling on short time periode of observations. Fuzzy ARIMA combines the advantages of fuzzy logic, ARIMA and fuzzy regression. Considering Tseng’s study the aim of this study is tracing the optimal observation range size when fuzzy ARIMA method is applied at the curent condition. The result of this study indicated that fuzzy ARIMA when the condition of time series data AR(2) with μ=50 and parameter estimation 1=0.600 and 2=0.300 was more sensitive when the observation size less than 20.
Keyword: fuzzy regression, fuzzy logic, fuzzy ARIMA

Judul: Peramalan Tingkat Inflasi dengan Metode Fuzzy Time Series
Abstrak: Inflasi merupakan salah satu indikator yang digunakan untuk menganalisa tingkat perekonomian suatu negara. Peramalan tingkat inflasi penting dilakukan karena hasil yang diperoleh digunakan sebagai salah satu indikator yang dapat memengaruhi kebijakan yang akan dibuat nantinya. Salah satu kebijakan yang menggunakan hasil peramalan ini sebagai salah satu hal yang dapat memengaruhinya adalah kebijakan ekonomi dan kebijakan moneter. Tujuan penelitian ini adalah untuk melakukan peramalan terhadap tingkat inflasi dengan menggunakan metode fuzzy time series serta metode ARIMA, dan membandingkan hasil yang diperoleh. Hasil pendugaan dengan kedua metode memiliki hasil yang mendekati nilai data aktual. Berdasarkan hasil pengukuran kesalahan dengan menggunakan Mean Square Error (MSE), diperoleh bahwa nilai MSE dengan metode fuzzy time series memiliki nilai yang lebih rendah dibandingkan dengan nilai MSE metode ARIMA. Berdasarkan hasil nilai MSE yang didapat, diperoleh hasil bahwa untuk peramalan tingkat inflasi dengan metode fuzzy time series Cheng et al relatif lebih baik dibandingkan dengan metode ARIMA.
Keyword: peramalan, tingkat inflasi, fuzzy time series, ARIMA

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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