Research has been conducted on the effect of variations in X-ray tube voltage to value of Contrast to Noise Ratio (CNR) on CT Scan at Bali Mandara Hospital using a phantom as a patient replacement. This research aims to determine the effect of X-ray tube voltage to the CNR value. Exposure factors used are X-ray tube voltage with variations of 80, 110, 120 and 135 kV, constant X-ray tube current of 150 mA and constant exposure time of 1 s. The readings of Io, Ib, and sb values in phantom images were performed using RadiAnt DICOM Viewer software (64 bit) and analysis of the effect X-ray tube voltage on CNR values was determined by regression test. The results of the analysis show that the variation of the X-ray tube voltage has a significant effect on the CNR value, where the greater X-ray tube voltage, the greater the CNR value. When the X-ray tube voltage is adjusted to 135 kV, the optimal CNR values are 113.52 for air, 35.06 for derlin, 13.93 for acrylic, 10.44 for nylon and 12.19 for polypropylene.

A prototype of a wind power plant had been created using a ventilator  as a generator spiner. This power plant utilizes wind speed as its propulsion. Electricity generated in the DC voltage form between 0 volts up to 7.46 volts. The MT3608 module is used to stabilize and raise the voltage installed in the input and output of the charging circuit. For instrument testing, the wind speed on 0 m/s up to 6 m/s interval used. Maximum output of this tool with a wind speed of 6 m/s is 7.46 volts.

The aim of this work was to observe homogeneity of human tooth surface using classification technique by laser-induced breakdown spectroscopy (LIBS) coupled with principle component analysis (PCA) algorithm. The human tooth was irradiated by 110 mJ Nd-YaG laser (1064 nm) under Helium gas with flow rate of 50 ml/s to produce plasma. Photon emission of the plasma was captured by ocean optic spectrometer HR 2500+ and displayed spectra of intensity as a function of wavelength. The spectra data were analysed by different strategies in PCA algorithm for classifying human tooth surface. The spectra data were split into three ranges that were a full spectral window, FW (200-850 nm), long special spectral window, LSW (380 – 660 nm) and short special spectral window, SSW (550 – 600 nm). These selected suitable input variables using spectral windows can reduce the influence of over fitting phenomena on classification results. Prior to PCA analysing, data were treated by different strategies of pre-processing namely linear baseline correction, area normalisation, and no pre-processing. The results showed that the short special spectral window (SSW) using pre-processing of area normalization could either clustering and distinguishing parts of human tooth surface clearly. Conclusion dentin surface has highest homogeneity of all.

Research has been carried out on the characterization of human nail samples by FTIR (Fourier Transform Infrared) using Chemometric PCA and Clustering methods. The sample used was left middle fingernail (TTK) from three people from one family (SKR) and two people who were not family (BKR). The test was carried out on TTK nail samples with a mass ratio of TTK nails with KBr 3:1. The results characterization by FTIR showed the presence of functional group O-H, C-H, C=O, N-H, C-N, P=O, C-O-C, nitrate, and nitrite in the TTK nail samples. The results of the analysis using the Chemometric PCA and Clustering methods showed that the TTK nail samples showed similarity in one family. This is based on the similarity of the types of molecules and their absorbance values. In addition, based on the results of PCA loading analysis, the wavenumber identity of the TTK nail samples were found in the range 1597-1479 cm-1.

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