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Journal : Jurnal Informatika: Jurnal Pengembangan IT

Peranti Pengukur Kadar Gangguan Mata Miopi dan Hipermetropi Berlandas Android Helda Yenni; Leni Apriani Sagita
Jurnal Informatika: Jurnal Pengembangan IT Vol 6, No 2 (2021): JPIT, Mei 2021
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v6i2.2433

Abstract

The vital organs of humans are enabled to see are the eyes. The eye is a camera that plays an important role in supporting daily human activities. An object can be seen clearly or not depends on the ability of light refraction in the eye. If there are abnormalities or eye diseases, it can interfere with one's vision. Visual disturbances related to light refraction namely myopia, hypermetropy, and astigmatism. Currently, there are several steps to help patients overcome these disorders, such as the use of glasses, medicines, surgery, and the use of certain technological devices. However, to follow the above method, the patient cannot detect early for any visual impairment, and the patient must go directly to the ophthalmologist at the clinic or hospital. This is less efficient if the patient has limited distance, time, up to the cost to consult directly. This research is aimed at making devices measuring myopia (nearsightedness) and hypermetropy (farsightedness) in the eye. The main components used are Raspberry Pi as the main microcontroller to process data, LCD viewer to display the results of measurement information, Android smartphone is used to display letters as a test medium that will be answered by patients so that the Raspberry Pi processes sound data from patients whether the answer is true or false. With this system, it can provide convenience for users in early detection of nearsightedness and farsightedness tests independently, so that information on farsightedness can be known from the results of tests carried out without having to consult a doctor directly.  Keywords - devices, gauges, visual disturbance, early detection, smartphones