Pengembangan Lightweight Data Analytic Pada Perangkat Edge - Agus Adyandana; Eko Sakti Pramukantoro; Fariz Andri Bakhtiar (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Nowdays, Internet of Things (IoT) technology developed to solve human problem. IoT technology developed in many fields already. Internet of Health Things (IoHT) is an IoT technology that developed in health field. IoT device produce an unuseful data for human before it's analyzed and visualized. Therefore we need an application that can store data, analyze data, and show analysis result. Researcher tried to solve it by developing a lightweight data analytic on resource constrained device in edge computing environment. Lightweight data analytic is an application that can store data, analyze data, and show analysis result which in order implemented by MongoDB, Sklearn, dan Flask. This research decided to focus on applications ability to analyze data with lightweight technology. This research use machine learning as application data analyzer. Testing is done by functional testing and scalability performance testing. The results of functional testing found that all application lightweight data analytic functional was running accordance what it needed. While scalability performance testing divided into data analytic testing and resource usage with runtime, CPU usage, memory usage, and disk I/O usage parameters. The results of data analytic performance testing found that application could handle 1000 data on used devices. But application still work on edge device, that is Raspberry Pi Zero W device and Raspberry Pi 3B+ device. Based on it, researcher can conclude that this application could be a solution of lightweight data analytic development on edge device with resource constraint.