PENAKSIRAN FUNGSI DENSITAS TIPE KERNEL DENGAN METODE CROSS-VALIDATION (C-V)

The choice of the bandwidth h is the main problem of kernel density function. In some situations it might be quite useful to have a set of retes corresponding to different bandwidth.It is necessary to agree which bandwidth is an appropriate one. Cross-Validation (C-V) is a well-known method to optimize the smoothing parameter h. In this research, we will analysis about three methods of Cross-Validation: Maximum Likelihood Cross-Validation, Least-Square Cross-Validation (Unbiased Cross-Validation) and Biased Cross-Validation with bandwidth choice optimal

ANALISIS DISKRIMINAN, REGRESI LOGISTIK, NEURAL NETWORK DAN MARS PADA PENGKLASIFIKASIAN DATA

The purpose of this research is to apply and compare the discriminant analysis, logistic regression, Neural Network (NN) and Multivariate Adaptive Regression Spline (MARS) at HBAT and IRIS data. Next will be the classification of fourth methods using the SPSS statistical software, MINITAB, MARS, and R. The results showed that the data HBAT predictor variables affected to the response variable which is the quality of the product (X6), Complaint resolution (X9) and Salesforce image (X12), whereas all predictor variables on the IRIS data affect the response variable. A more precise method used in HBAT data classification is NN and discriminant analysis because the value of the resulting classification accuracy is greater, especially for testing. While a more precise method used in the IRIS data classification is discriminant analysis because the value of the resulting classification accuracy is greate

ANALISIS VARIANS MULTIVARIAT PADA EKSPERIMEN DENGAN RANCANGAN ACAK LENGKAP

Metode Statistika Multivariat adalah teknik analisis statistik yang memperlakukan sekumpulan variabel dependent yang saling berhubungan sebagai satu sistem, dengan memperhitungkan kuatnya hubungan antar variabel-variabel tersebut. Analisis yang demikian biasanya dikenal atau disebut Analisis Statistik Multivariat atau disingkat Analisis Multivariat.Tujuan analisis dengan metode ini adalah menemukan dan menafsirkan struktur yang mendasari data. Pada analisis ini data yang diolah adalah data dari hasil pengukuran beberapa variabel tak bebas dan dapat saja ditambah dengan hasil pengukuran dari satu atau beberapa variabel bebas. Dengan demikian yang diukur adalah satu atau beberapa kelompok variabel, sedang datanya adalah beberapa kelompok skor.Analisis Varians adalah tehnik analisis statistik, yang biasanya digunakan untuk komparasi beberapa rata-rata populasi, berdasarkan perbandingan pasangan taksiran varians faktor-faktor tertentu. Pada kondisi multivariat, dimana analisis ini merupakan perluasan atau generalisasi dari analisis varians adalah Analisis Varians Multivariat, dan merupakan tehnik analisis data tentang perbedaan pengaruh beberapa variabel terhadap sekelompok variabel kriteria

PRAKIRAAN CURAH HUJAN KECAMATAN KAIRATU KABUPATEN SERAM BAGIAN BARAT DENGAN MODEL AUTOREGRESIVE INTEGRATED MOVING AVERAGE (ARIMA)

Forecasting is an activity to use the past data as the basic to predict the future event that will occur. The result from the prediction is an un-sure event or just a guess, but with some certain methods then the prediction will be more than a guess, it means that it is a scientific guess. The data analysis technique with autoregressive integrated moving average (ARIMA) method can give the early information that is needed as the material for the consideration to take the decision and the action itsel

SISTEM PAKAR FUZZY UNTUK MANAJEMEN DAUR HIDUP PRODUK

Every product has its certain life cycle, whether, for example, it preserve in the market or have to be withdrawed from the market. Some criterias are important to determine those decisions. But they are not in numerical form but categorial one. Fuzzy logic is a tool to transform those categorial form to numerics using membership function. This research was trying to helps management as an expert system to make a decision based on computer software