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Journal : Sainstek : Jurnal Sains dan Teknologi

PENGEMBANGAN CATU DAYA PRESISI DISPLAY DIGITAL UNTUK PRAKTIKUM FISIKA LISTRIK DINAMIS Hamid, Bushra; Agustiyanto, Frans Rizal; Yulkifli, Yulkifli
Sainstek : Jurnal Sains dan Teknologi Vol 8, No 2 (2016)
Publisher : IAIN Batusangkar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.309 KB) | DOI: 10.31958/js.v8i2.482

Abstract

This study aims to generate power supply precision instrument digital display a valid and practical for students of physics 3rd semester of the school year 2014/2015. This research includes development research (research development) of the power supply circuit that has been common there are some drawbacks, namely, the output of output that does not fit, there is still AC voltage on the output value, the output voltage is unstable, so that the results of the lab basic physics 2 be not in accordance with the results of the theory. The addition of the diode bridge circuit helps perfect output voltage into DC, the capacitors in the circuit capacity was raised as a reliever ripple or ripples form to obtain a stable DC voltage value, for a voltage stabilizer is also used IC9815 surge protector. Limited trial conducted in STAIN Batusangakar to 26 students. Based on the results of data analysis has been carried out can be summarized as follows: (1) The results of the validation tool precision power supply digital display is very valid. (2) The results of trials carried out showed that the practicalities have met the criteria that can be used and implemented in a lab with practicality very practical value.
APLIKASI COMPUTER VISION PADA KUALITAS KEMATANGAN BUAH AGUSTIYANTO, FRANS RIZAL
Sainstek : Jurnal Sains dan Teknologi Vol 4, No 2 (2012)
Publisher : IAIN Batusangkar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (643.922 KB) | DOI: 10.31958/js.v4i2.139

Abstract

This paper introduces the computer vision with the comparison of color methods to classify the variants of fruit (tomatoes, chilies, and apples) which is based on the level or stage of ripe.  The color comparison method is quite simple; the tomato images captured by the camera (CCD) will be cropped partly. Then its characteristic color will be extracted and the color grade level will be calculated. The calculation of R (red), G (green) and B (blue) and the transformation of the color to Hue, Saturation, and Value was conducted in order to classify the fruit maturity. Thus, the ripe can be classified into 3, namely Ripe, Half-Ripe, and Un-ripe (not ripe). On contrary, over-ripe cannot be classified because the characteristics of the color is similar with the ripe tomato but the skin texture is slack, so it is not enough to characterize the color used to draw conclusion of being Over-ripeKey words: image processing, computer vision, RGB, HVS