Peneraan Forward Chaining Untuk Mendianogsa Penyakit Malaria Dan Pencegahanya Berbasis Web

Febrianti, Eka Lia; Christi, Tika

doi:10.33330/jurteksi.v4i1.32

Cited by 2 publications

(2 citation statements)

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“…Penderita Malaria jenis ini mengalami demam tidak teratur dengan disertai gejala terserangnya bagian otak, bahkan memasuki fasekoma dan kematian yang mendadak. Pernisiosa malaria ini disebabkan oleh Plasmodium ovale" [13]. Informasi yang ditampilkan pada menu ini adalah penderita malaria sesuai jenis yang dipilih oleh pengguna.…”

Section: Gambar 6 Halaman Penderita Penyakit Malaria / Rtunclassified

Sistem Informasi Geografis Penderita Malaria pada Kelurahan Cereme Taba Kota Lubuklinggau

Hutrianto

Syakti

2019

Digitalzone

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Sesuai dengan undang-undang berkaitan dengan kesehatan yaitu undang-undang nomor 36 tahun 2009 menyatakan dengan jelas yaitu anggaran untuk kesehatan merupakan 5% dari anggaran pendapatan dan belanja negara (APBN). Untuk itu perhatian dan kepedulian pemerintah menjadi sangan penting untuk dilakukan baik pemerintah tingkat nasional, provinsi, kabupaten, kecamatan atau bahkan pemeritnah tingkat kelurahan. Salah satu sektor yang patut diperhatikan yaitu sektor pencegahan berkaitan dengan penyakit malaria. Namun untuk melakukan pencegahan tersebut membutuhkan data yang valid serta aktual. Untuk itu di dalam penelitian ini dilakukan pengembangan sistem informasi geografis penderita malaria sebagai salah satu cara dalam penyajian informasi untuk penanggulangan oleh pemerintah. Dalam proses pengembangan sistem informasi geografis digunakan waterfall seabgai metode pengembangan dengan tahapan communication, planning, modeling, construction, dan deployment. Sistem informasi geografis yang dihasilkan memiliki fitur yang dapat menyajikan data pendertia malaria dengan atribut nama, jenis Malaria, RT, alamat, telepon dan lama menderita malaria dan telah dilakukan pengujian. Hasil pengujian menunjukkan semua komponen dapat berfungsi dengan baik. Kata kunci: SIG, Penderita Malaria, Waterfall Abstract By the law relating to health, namely law number 36 of 2009 states clearly that the budget for health constitutes 5% of the state budget (APBN). For this reason, the attention and concern of the government become very important to be carried out either at the national, provincial, district, sub-district, or even village level government. One sector that needs attention is the prevention sector related to malaria. But to do this, prevention requires valid and actual data. For this reason, in this research, the development of a geographic information system for malaria sufferers was carried out as a way of presenting information for countermeasures by the government. In the process of developing a geographic information system, a waterfall used as a method of development with stages of communication, planning, modelling, construction, and deployment. The resulting geographic information system has a feature that can present supplementary malaria data with the attribute name, type of malaria, RT, address, telephone, and duration of disease and has tested. The test results show all components can function correctly. Keywords: GIS, Malaria sufferers, Waterfall

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Section: Gambar 6 Halaman Penderita Penyakit Malaria / Rtunclassified

Sistem Informasi Geografis Penderita Malaria pada Kelurahan Cereme Taba Kota Lubuklinggau

Hutrianto

Syakti

2019

Digitalzone

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“…Malaria is a tropical disease that infects red blood cells, malaria is caused by infection with the plasmodium parasite that can multiply in human red blood cells (Febrianti & Christi, 2017). Malaria is transmitted to humans through the bite of a female Anopheles mosquito, malaria symptoms begin to occur about 10 to 15 days after being bitten by an infected mosquito (Pratiwi et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Detection Malaria Base Microscope Digital Image with Convolutional Neural Network

Untoro

Muttaqin

2022

SinkrOn

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Malaria is a tropical disease that infects human red blood cells caused by infection with the plasmodium parasite. Plasmodium parasites spread to humans through female Anopheles mosquitoes and can reproduce in human blood cells. Malaria is a health problem that is at risk of causing other health problems such as anemia and even death. The current gold standard for malaria diagnosis is laboratory diagnosis by microscopic examination to find the malaria parasite through the blood cells of the patient. However, the diagnosis of malaria through microscopic observation of blood cells has the potential to take a long time, because the plasmodium parasite has a very small size. The malaria detection system using the Convolutional Neural Network (CNN) method is designed to detect malaria in human blood cells. CNN is a machine learning method designed to classify objects in an image. The system was built in three stages of development, namely the development of a CNN model for malaria detection, software development and hardware development. The hardware components used in the system include Raspberry pi, Raspberry Pi camera module, and LCD. The results of the malaria detection test using the CNN model gave an accuracy of 98.76% which was tested on blood cell images from a microscope

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Peneraan Forward Chaining Untuk Mendianogsa Penyakit Malaria Dan Pencegahanya Berbasis Web

Cited by 2 publications

References 0 publications

Sistem Informasi Geografis Penderita Malaria pada Kelurahan Cereme Taba Kota Lubuklinggau

Sistem Informasi Geografis Penderita Malaria pada Kelurahan Cereme Taba Kota Lubuklinggau

Detection Malaria Base Microscope Digital Image with Convolutional Neural Network

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