<p>Denyut jantung dan suhu tubuh merupakan salah satu faktor penentu atau tanda tanda vital dalam penentuan kesehatan. Denyut jantung dan suhu tubuh dilakukan untuk mengetahui tanda klinis dan berguna untuk memperkuat diagnosis suatu penyakit. Pada proses pemeriksaan denyut jantung dan suhu tubuh masih menggunakan sistem manual dimana pasien harus datang ke rumah sakit untuk memeriksa denyut jantung dan suhu tubuh. Sistem ini kurang efektif karena memakan banyak waktu. Pada penelitian ini dibuat sebuah sistem monitoring denyut jantung dan suhu tubuh sebagai indikator level kesehatan pasien berbasis iot (internet of things) dengan metode fuzzy menggunakan android. Sistem ini menggunakan pulse sensor untuk mendeteksi denyut jantung dan LM35DZ untuk mendeteksi suhu tubuh. Pemroses data menggunakan arduino uno dan nodemcu yang sekaligus berfungsi sebagai media pengiriman data menggunakan internet of things. Sistem ini mendeteksi denyut jantung dan suhu tubuh jarak jauh. Sistem ini dilengkapi dengan fitur interface android dan desktop, simpan data dan keputusan sehat atau tidak. Dari hasil pengujian tingkat keberhasilan mendeteksi denyut jantung adalah 97.71%, suhu tubuh sebesar 99.69%, tingkat keberhasilan pengiriman data sebesar 50%, dan keputusan sesuai dengan rule kesehatan yang telah ditentukan. Dari hasil tersebut sistem sesuai dengan yang diharapkan.</p>
Energy is one of the basic needs for human being. One of the most vital energy sources is electricity. Electricity is a type of energy that sustains survival of human being, more particularly in industrial sector. Efficiency in industrial sector refers to a state where electricity is used to as little as possible to produce the same amount of product. The case study was conducted in marine commodity sector, anchovy and jellyfish supplier. The supplier was classified as SME that installed 33,000 VA electric powers (B2). The data were in the form of energy consumption intensity (ECI) and specific energy consumption (SEC) to determine the energy efficiency level. The objective of the study was to classify the efficiency level of electricity consumption using Sugeno Fuzzy method. The findings of the study were 1) the average ECI between January, 2016 and April, 2017 was 1,949 kWh/m2; it was classified as efficient; 2) the average SEC at the same period was 126,108 kWh/ton; it was classified as excessive. Sugeno Fuzzy logic was implemented to determine efficiency level of electricity in this company. Based on the average ECI and SEC, the electricity consumption of the company was categorized as excessive with FIS Sugeno output of 0.803.
Garbage is one of the causes of a problem that is difficult to solve in Indonesia and even in other countries, many cities in Indonesia are filled with garbage. Maybe one of the factors is the scattering of garbage everywhere because humans themselves are lazy to throw away their place or are already accustomed to littering, causing rubbish to be scattered everywhere which can eventually lead to garbage pollution, unpleasant odors and ultimately can cause flooding. In this research, we will make a tool for sorting organic and inorganic waste, namely by making a tool such as a conveyor to sort the types of organic waste and the types of inorganic waste which will later be classified separately and collected in their own place so that they are not mixed together. To distinguish which organic and inorganic waste we will use a capacitive proximity sensor as a sorter, atmega 16 as a microcontroller to run all the work of the appliance system. DC motor as a conveyor drive. The LDR sensor detects the presence of waste. From the test, the organic and inorganic waste sorting tool has pretty good results with an average success rate of detecting organic waste of 66.67% and the success rate for inorganic waste is 63.33%.
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