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All Journal Elektron Jurnal Ilmiah JOIV : International Journal on Informatics Visualization International Journal of Wireless And Multimedia Communications
Milda Yuliza
Politeknik Negeri Padang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Artificial Neural Network Application for Aroma Monitoring on The Coffe Beans Blending Process Susanti Roza; Zas Ressy Aidha; Milda Yuliza; - Suryadi; Surfa Yondri
JOIV : International Journal on Informatics Visualization Vol 2, No 3 (2018)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (761.278 KB) | DOI: 10.30630/joiv.2.3.86

Abstract

This study aims to identify the type of coffee powder aroma from the coffee beans blending using backpropagation artificial neural network (ANN). Backpropagation is a controlled training implementing a weight adjustment pattern to achieve a minimum error value between the the predicted and the actual output. Within this study, the coffee aroma testing utilized electronic tasting sensor system consisted of 4 sensors namely TGS 2611, TGS 2620, TGS 2610 and TGS 2602. The coffee aroma monitoring and data collection in this system applied LabVIEW software as a virtual instrumentation. The testing result of this ANN was able to distinguish the coffee variety of Robusta, Arabica coffee powder and the one without any coffee aroma. The backpropagation architecture was formed by 3 layers consisting of 1 input layer with 4 input nerve cells, 1 hidden layer with 8 neural cells, and 2 output layers by applying the backpropagation training algorithm. The training data was taken from 70 data samples of each circumstance of coffee with 5 testing times. The results of the training and testing showed that the established backpropagation was capable to identify and differenciate the coffee powder in accordance with the given input with different average success rate;  91.96% for Robusta coffee, 100 % for Arabica coffee, and no 84.24% for without coffee aroma.
Aplikasi WiMAX Yenniwarti Rafsyam; Milda Yuliza; Lifwarda Lifwarda
Elektron : Jurnal Ilmiah Vol 1 No 1 (2009): Elektron Jurnal Ilmiah
Publisher : Teknik Elektro Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (276.655 KB) | DOI: 10.30630/eji.1.1.11

Abstract

WiMAX is Broadband Wireless Acces (BWA) technology evolution with interactive fitur. WiMAX not only have issue about data speed problem but also about open standard. It means, communications between WiMax instruments between some different vendors are not proprietary. WimAX orientations are not only for fixed market, but also for portable and mobile market. WiMAX with high speed data (up to 70 MBps) is suitable to apply in last mile broadband connections, backhaul and high speed enterprise.
Design of Monitoring and Control System For Air Temperature And Humidity In Oyster Mushroom Cultivation Room Based on IOT Raffa Aulia Mutaqi; Milda Yuliza; Yul Antonisfia; Nisa Rahima Sakinah Nisa
International Journal of Wireless And Multimedia Communications Vol. 2 No. 1 (2025): International Journal of Wireless And Multimedia Communications
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/jowim.v2i1.59

Abstract

Oyster mushroom cultivation is very popular among rural and urban communities, both on a small, medium and industrial scale. Oyster mushroom cultivation requires controlling the temperature and humidity in the mushroom barn to get optimal mushroom body growth. In general, the optimal temperature for oyster mushroom growth in the fruiting phase is 26-30°C with a humidity of 70-95%RH. This system describes the workings of the device used to monitor temperature and humidity using a DHT22 sensor through a microcontroller, which is displayed on the Blynk application and a 20x4 LCD. Measurements in lowland areas show a temperature of 29°C and humidity of 95%. The percentage error of the temperature measurement with the DHT22 sensor is 6.37%, with an average error of 1.60%. As for humidity, the measurement error is 0.71% with an average error of 0.82%. With this system, mushroom farmers can monitor the environmental conditions of the cultivation room in real-time through an IoT platform connected to the sensor.
Co-Authors - Suryadi Lifwarda Lifwarda Nisa Rahima Sakinah Nisa Raffa Aulia Mutaqi Roza Susanti Surfa Yondri Yenniwarti Rafsyam Yul Antonisfia Zas Ressy Aidha