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"Different morphologies of zinc oxide (ZnO) can be obtained through various synthesizing methods, such as that of the water bath. By synthesizing under various conditions, different ZnO morphologies can be seen as the result of the water bath method. Replacing ZnO nanoparticles with vertically aligned ZnO nanorods results in a much higher energy conversion efficiency. Yet vertically aligned nanorods can only be grown through difficult and expensive methods. Several researchers have studied the growth of one-dimensional (1D) nanorods on homogeneous film with various growth conditions. However, there has been little in the way of research on ZnO nanorods grown on ZnO seed layers using the water bath method. In this research, vertically aligned nanorods with an optimum size ratio were formed through a simple water bath method. This method reveals that the ZnO nanorods are well aligned and grown with a high density and uniformity on the substrate. Their X-ray diffraction patterns reveal that the nanorods are grow in the [001] direction. The density, diameter, and length of the ZnO nanorods can be altered by changing the growing condition. All of the samples were characterized using a scanning electron microscope, X-ray diffraction, and micro Raman spectroscopy. To investigate crystal growth, zinc nitrate and zinc acetate were used when preparing the solution. The results demonstrate that the morphology and alignment of ZnO nanorods are determined by the precursor’s type and deposition time."

"Kepemilikan dan penggunaan kendaraan mobil memiliki berbagai risiko negatif, seperti terjadinya kecelakaan. Untuk mengurangi beban risiko tersebut, perusahaan menjual produk asuransi mobil. Asuransi mobil merupakan salah satu produk perusahaan asuransi kendaraan yang bertujuan sebagai upaya perlindungan pemilik kendaraan mobil dari kerugian finansial yang terjadi pada kendaraan yang diasuransikannya. Untuk menawarkan produk asuransi, beberapa perusahaan menggunakan teknik penjualan dengan cara cold calling. Teknik penjualan tersebut akan lebih efektif menjual produk asuransi jika terlebih dahulu data nasabah calon pembeli asuransi diprediksi atau diklasifikasi ke dalam kelas membeli atau tidak membeli.

Pada skripsi ini, dilakukan klasfikasi dengan metode Support Vector Machine (SVM), Random Forest (RF),dan Logistic Regression (LR) dengan implementasi metode seleksi fitur One Dimensional Naïve Bayes Classifier (1-DBC). Data yang diperoleh berjumlah 4000 data dengan total 18 fitur. Diperoleh hasil bahwa akurasi SVM lebih tinggi dibandingkan dengan kedua metode lainnya. Selain itu, mplementasi metode seleksi fitur telah berhasil meningkatkan akurasi dari metode Random Forest, dan Logistic Regression. Dengan implementasi 1-DBC, ketiga metode klasifikasi memperoleh hasil akurasi tertinggi pada penggunaan 15 fitur.

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Ownership and use of car vehicles have a variety of negative risks, such as accidents. To reduce the risk burden, the company sells car insurance products. Car insurance is one of the products of a vehicle insurance company that aims to protect vehicle owners from financial losses that occur on their insured vehicles. To offer insurance products, some companies use sales techniques using cold calling. The sales technique will be more effective in selling insurance products if first the prospective customer buyer data is predicted or classified into the class of buying or not buying.

In this paper, classification is done using the method of Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression (LR) by implementing the One Dimensional NaA-ve Bayes Classifier (1-DBC) feature selection method. The data obtained amounted to 4000 data with a total of 18 features. The results were obtained that the accuracy of SVM was higher compared to the other two methods. In addition, the implementation of the feature selection method has succeeded in increasing the accuracy of the Random Forest, and Logistic Regression. With the implementation of 1-DBC, the three classification methods obtained the highest accuracy results with the use of 15 features."