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All Journal JURNAL INTEGRASI Journal of Applied Electrical Engineering
Maulidiah, Hana Mutialif
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Control & Systems Engineering Electrical & Electronics Engineering Other

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Journal : Journal of Applied Electrical Engineering

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Reducing Coating Defects by Implementing Auto Dripping System on The Finishing Machine Octowinandi, Vivin; Firdaus, Fadli; Arifin, Muhammad; Maulidiah, Hana Mutialif; Iqbal, Muhammad
Journal of Applied Electrical Engineering Vol 7 No 2 (2023): JAEE, December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v7i2.6722

Abstract

Finishing Process is one of the most important processes in the manufacture of resistors, because it is the process of forming the resistor body by coating the resistor with a coating liquid. However, in this process there are still many cases of product defects, one of the main causes is the uncontrolled viscosity of the coating liquid causing the formation of body resistors is not good, or what is called Body deform and body thin defects. Auto Dripping is a useful tool for automatically dripping methanol liquid which aims to control the viscosity of the coating liquid in the finishing process. Because Auto Dripping is a tool that has just been implemented and does not yet have the right parameter settings, it is necessary to do trials to find the right parameters so that Auto Dripping functions properly. In Auto Dripping there are two settings that can be controlled, namely Stroke Speed and Stroke Length, these two settings affect the output of methanol liquid that comes out. In this study using SPC tools to analyze the parameters being tested, namely the Control Chart which is used to monitor the stability of a process and study process changes from time to time. then, in this study also used the Process Capability Analysis method. This method is very effective in viewing the performance of a process, is used to measure process capability by comparing its distribution with the distribution of specifications accurately and provides a clearer picture. After carrying out this project, the authors concluded that the implementation of the Auto Dripping set up parameter has proven to be quite influential in reducing the case of coating defects caused by uncontrolled viscosity, namely by maintaining the stability of the coating viscosity so that it can produce resistors that meet specifications. From the data above, the production of resistors has been running stably with a period of 5 weeks, with 100 resistor samples being measured. With an average value of 2.82 mm. As for the Cpk value after implementing the new parameter setup, which is 3.35, this is a high result and meets the standard, which is ≥1.5.
Penerapan Computer Vision untuk Deteksi Warna dan Ukuran Buah secara Real-Time pada Alat Penyortir Buah Aryeni, Illa; Maulidiah, Hana Mutialif; Toar, Handri; Wicaksono, Muhammad Jaka Wimbang; Gunawan, Indra
Journal of Applied Electrical Engineering Vol 7 No 2 (2023): JAEE, December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v7i2.6740

Abstract

Computer vision aims to build a computer that can see like humans. Humans can immediately recognize and define an object after seeing and recording an object. This is different from computer visual systems, where camera recordings cannot be directly translated, defined, and recognized by computers, therefore digital image processing is needed first. In this study, computer vision technology was used to detect fruit based on color, size, and shape in real time. The fruit is placed on a conveyor belt, then the fruit object is captured by a webcam using object tracking. Computer vision algorithms and programs can detect fruit objects and recognize ripe and unripe fruits by converting RGB (Red, Green, Blue) colors into HSV (Hue, Saturation, Value) for the color segmentation process. After the detection process, a selector is placed at the end of the conveyor which is used to sort the fruit into 2 categories, namely ripe and unripe. In addition, this study also determines the size and shape of the fruit. From design, realization, and testing, it was found that the success rate of detecting ripe fruit was 97.33% and unripe fruit was 93.33%. To get maximum results, it needs to be supported by room lighting settings that are kept constant.
Prototype for Forest Fire Early Detection System Using the MQTT Method Simanjuntak, Frisca Tryandayani; Sani, Abdullah; Maulidiah, Hana Mutialif; Puspita, Widya Rika; Budiana, Budiana
Journal of Applied Electrical Engineering Vol 8 No 1 (2024): JAEE, June 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v8i1.7544

Abstract

The case of forest fires in Batam is one of the natural disasters that often occurs both caused by nature and human error. These forest fires certainly damage forest ecosystems. The condition of the vast forest makes it difficult to monitor the condition of the forest to find the location of the fire. In this study, the authors designed a forest fire early detection system using the concept of Wireless Sensor Network. The system is designed using the MQTT protocol in its data transmission communications. MQTT is a communication protocol that uses the concept of publish-subscribe. Fire information sent by telegram. It is hoped that with this research, it will be able to detect early fires that occur in the forest and be able to become an initial concept for further development. From the test results, it was found that the MQTT protocol sends data well, with subscribers using QoS 0 services having an average delay of 0.050 s, an average throughput of 31355 bps and packet loss of 0%. Subscribers who use QoS 1 services have an average delay of 0.064 s, an average throuhput of 30683 bps, and a packet loss of 0%. The system is able to send information notifications to telegram well. Keywords: Forest Fires, Wireless Sensor Network, MQTT, and Sensor Node
Co-Authors Aryeni, Illa Budiana, Budiana Darmoyono, Aditya Gautama Diono, Diono Dzulfiqar, Mohamad Alif Firdaus, Fadli Futra, Asrizal Deri Gusnam, Mu'thiana Handri Toar Hasnira Hasnira, Hasnira Heni Pujiastuti Kamarudin Kamarudin Mahdaliza, Rahmi Mochammad Imron Awalludin Octowinandi, Vivin Oktani, Dessy Puspita, Widya Rika Simanjuntak, Frisca Tryandayani Situmorang, Choklin Brema Tamaulina Br Sembiring Veithzal Rivai Zainal Wicaksono, Muhammad Jaka Wimbang