Judul: Model Based Analysis Cluster Study in Normal Distribution Multivariate Data
Abstrak: Cluster analysis is data method classify objects into groups based on similarity or dissimilarity. One of approach is model based clustering. The assumptions used is the data derived from a mixture of two or more distribution probability with certain proportions. The final cluster is determined by BIC. The object of each cluster were obtained by EM algorithm. This study aims to assess the effectiveness of the model based clustering on the data are from multivariate normal distribution. Effectiveness would include the percentage of classification errors produced at a several distance, comparing with the k-means, and their application. If the distance between the center of a large and diverse cluster each different variables, then averaging the resulting classification error rate small. generally model based to cluster is more effective than the method of k-means. The MAP was better than the MLE since it can overcome the singularity problem, the rest same as MLE.
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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: Pembuatan Sel Surya TiO2 Tersensitisasi Dye Padat Dengan Elektrolit Polimer
Abstrak: Telah dibuat sebuah sel surya berbasis TiO2 tersensitisasi dye menggunakan ruthenium sebagai fotosensitizer. Sel surya dibentuk dengan struktur sandwich, dimana dua elektroda mengapit elektrolit polimer yang mengandung kopel redoks I-/I3 -. Salah satu elektroda, yaitu elektroda kerja berupa lapisan TiO2 pada substrat kaca berlapis bahan ITO (indium tin oxide) disensitisasi dengan dye ruthenium sebagai donor elektron dalam sistem sel surya ini. Elektroda lain berupa karbon sebagai elektroda lawan. Elektrolit gel berbasis PEG (polyethylene glycol) mengandung kopel redoks I-/I3 - digunakan sebagai pengganti elektrolit cair pada sel fotoelektrokimia. Hasil karakterisasi XRD terhadap TiO2 yang digunakan menunjukkan bahwa struktur kristal yang terbentuk yaitu anatase dan rutile dengan perbandingan masing-masing 33% dan 67% pada pemanasan 200 oC. Dye dan TiO2 yang digunakan memiliki daerah serapan cahaya masing-masing pada panjang gelombang 500 - 575 nm dan 360 – 450 nm. Sehingga sel surya ini optimal digunakan pada cahaya dengan panjang gelombang 300 - 580 nm. Berdasarkan kurva arus - tegangan (I -V) diketahui bahwa daya yang dihasilkan sebesar 0.017 mW dengan kemampuan konversi energi matahari 0,012%.
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