Fuzzy Rule based Enhanced Homomorphic Encryption in Cloud Computing

Analisis penyebab kematian ibu pasca postpartum sangatlah penting dalam mengurang kematian ibu. Angka kematian ibu pasca postpartum diindonesia sangatlah tinggi sekitar 359 dalam 100.000 kelahiran. Faktor -faktor kematian ibu pasca postpartum jarang dianalisis lebih dalam sehingga tidak ada penanganan berkelanjuttan. Pada penelitian ini penulis menggunakan system fuzzy rule-based fog cloud computing untuk memonitoring kematian ibu berdasarkan tanda-tanda vital dan tanda-tanda fisik dengan menggunakan 10 parameter penyebab kematian ibu masa postpartum. Fog cloud digunakan untuk pengolahaan data dalam sever local agar mengurangi beban saat menggunakan cloud computing. Analisis awal parameter kematian ibu dirubah kedalam rentang low, medium dan high kemudian dimonitoring pada tujuh hari pasca postpartum dari hasil analisis yang dilakukan didapat faktor dominan kematian ibu pasca postpartum untuk tanda-tanda vital dipengaruhi oleh Blood Pressure dengan nilai MF 0,44 dengan status “High” untuk tanda-tanda fisik dipengaruhi oleh Anogenital Lochea Sanguinolenta dengan nilai MF 0,46 dengan status dalam system “High”. Parameter lain tidak terlalu berpengaruh terhadap kematian ibu cenderung turun dari hari pertama hingga hari ke tujuh pasca postpartum.

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Examination of Healthcare Diagonosis using Iot

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.a9241.119119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 5251-5254

Keyword(s):

Cloud Computing ◽

Fuzzy Rule ◽

Classification Algorithms ◽

Computing Technology ◽

Rule Based ◽

Related Data ◽

Health Related ◽

Neural Classifier ◽

Iot Devices ◽

Existing Data

In recent years, online applications, spare many services for wellness of health related issues. The application is kept updated so that the health related data are kept modernized for future references. The application collects information from IoT devices and then compares them with other existing data from the prevailing records with the same disease. The collected data is then reserved in a database that hold all records about the healthcare issues. Cloud computing technology is used to guard and reserve the healthcare records. Cloud and IoT technology are connected to provide users with a completely developed healthcare record. The existing system makes use of Fuzzy Rule Based Neural Classifier that helps in assembling and categorizing the diabetes data under the guidance of severity analyzer. This work, present the comparison of some classification algorithms and obtain the accuracy, the dataset collected is a real-time dataset. The output and results are tabulated after the comparison of the algorithms.

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