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All Journal Journal of Applied Community Engagement (JACE) Prosiding Seminar Nasional Inovasi Teknologi Terapan Jurnal Inovasi Teknologi Terapan
Parulian Silalahi
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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Pelatihan Desain Pembelajaran dengan E-learning Berbasis LMS Moodle Parulian Silalahi; Charlota Agripina; Yang Agita
Journal of Applied Community Engagement Vol 1 No 1 (2021): Journal of Applied Community Engagement (JACE)
Publisher : ISAS (Indonesian Society of Applied Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.258 KB) | DOI: 10.52158/jace.v1i1.125

Abstract

The purpose of this service is to train teachers to have knowledge and skills in designing and developing learning with E-learning based on Moodle LMS. This training was given to SMP Maria Goretti Sungailiat Bangka teachers. The method of implementing the service is carried out in three phases: phase 1. preparation; phase 2. implementation; and phase 3. Evaluation. The service is carried out face-to-face and online. Through face-to-face training, lectures and demonstrations were held for 3 meetings in July 2020 with 10 teachers participating in this training. Online provided using the Moodle application. The results of the training showed that the knowledge and skills of teachers in designing and developing learning using the Moodle LMS E-learning application increased. Furthermore, from the Moodle application that has been developed by the servant for learning that the teacher provides to students, it can be applied properly.
MESIN MINUMAN KOPI OTOMATIS BERBASIS IOT Rafli Pratama; Ramadona; Zanu Saputra; Parulian Silalahi
Prosiding Seminar Nasional Inovasi Teknologi Terapan Vol. 2 No. 02 (2022): Prosiding Seminar Nasional Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

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Abstract

Coffee is the most popular drink for Indonesian people, both young and old. However, due to their busy schedules, they do not have time to make coffee. Therefore, we need a machine that can make coffee drinks without the need to make it manually. In this manufacture, it is proposed to make this Machine with the aim that the machine can be used as a business medium that can be controlled and monitored via a smartphone. The method of making this IoT-Based Automatic Coffee Beverage Machine uses Arduino Mega as a control system with push button input and an LCD display that will be used as a menu display. Then this machine is also equipped with a DS18B20 temperature sensor as a coffee drink temperature detection, an Ultrasonic sensor as a coffee capacity detector in the glass with the addition of an ordering and monitoring system using a smartphone. Based on the results of the tests carried out, data were obtained by conducting 8 experiments with 4 different doses. In testing the filling of coffee drinks with 4 experiments using the Button and in testing the filling of coffee drinks with 4 experiments using the application. From all the experiments carried out, it was found that the average percentage error of each dose of drink made was 1/4 cup with an error of 0.154%, 1/2 cup with an error of 0.032%, 3/4 cup with an error of 0.032% and 1 cup with an error of 0. 0.0268%. In the experiment of making coffee drinks to be stable starting from a drink temperature of 30º which is then heated with a temperature increase of 3-5ºC every minute and it only takes 6 minutes for the heater to reach the maximum temperature of 70ºC from coffee drinks. After that the heater will turn off and the temperature increase will decrease to 3-1ºC and the temperature of the coffee drink will be stable between 70-80ºC.
Pendeteksi Persentase Kadar Alkohol Dengan Kontrol PID Berbasis IOT Putri Ayu Handira; M Azis Pangestu; Eko Sulistyo; Parulian Silalahi
Jurnal Inovasi Teknologi Terapan Vol. 1 No. 1 (2023): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

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Abstract

In order to find out the alcohol content in drinks circulating in the community, measurements and tests are usually carried out in the laboratory. This takes quite a long time. To solve this problem, we need a tool that can measure alcohol quickly and accurately. This research aims to design and manufacture a detector for the percentage of alcohol content, especially in drinks, using an IoT (Internet of Thing)-based MQ3 sensor as a monitoring system that is connected directly to a smartphone. The method used in this research is PID (Proportional Integral Derivative). By setting the PID tuning with a value of kp=4, ki=3, kd=0.0001 and a setpoint of 210 is used to produce an optimal reading of the alcohol content in the drink. Readings using PID control have an average error value of 1.26%, otherwise without using PID control, the average error value is 8.12%. In order to see the alcohol content of the experimental results of the type of drink detected, it will be displayed on the blynk application on the smartphone.
Co-Authors Charlota Agripina Eko Sulistyo M Azis Pangestu Putri Ayu Handira Rafli Pratama Ramadona Yang Agita Zanu Saputra