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Komparasi Performansi Antara Proportional Integral Derivative Controller (PID) Dan Fuzzy Logic Controller (FLC) Pada Penjejak Cahaya Dengan Tiga Sensor Gunawan, Doni; Away, Yuwaldi; Sara, Ira Devi; Novandri, Andri
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 6 No. 2 (2022)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v6i2.552

Abstract

The technology of light tracking monitors the solar panels to track the sun with full efficiency, and the solar panels can be upright to the sunlight in order to maximize the absorption of solar energy, so this system has a higher efficiency than non-tracking systems. This study aimed to obtain a controller that works accurately between the Proportional, Integral, and Derivative Controller (PID) and the Fuzzy Logic Controller (FLC) Algorithm by comparing the performance of the two algorithms in regulating the direction of the light tracker to detect the presence of sunlight. This solar prototype uses nine lamps as a simulation to determine the accuracy and precision of the angles of the two light trackers. The parameters compared in this test were the aspects of angular velocity and angle accuracy. The mean value of angular velocity obtained from the PID light tracking test results was 0.16 rad/s and the average linear velocity was 0.092 m/s whereas in the FLC light tracker, the average angular velocity value was 0.207 rad/s. Tests using a PID light tracker resulted in an X-axis accuracy of 45% and a Y-axis accuracy of 30%. The FLC light tracker, on the other hand, had an X-axis accuracy of 80% and a Y-axis accuracy of 30%.The precision value obtained by the PID light tracker on the X axis was 45% and the Y axis was 38%, while the precision value obtained by the FLC light tracker on the X axis was 71% and the Y axis was 33%. Based on the overall calculations, it can be concluded that the FLC light tracker has an increase in the speed value of 29% and an increase in the value of accuracy in the accuracy aspect by 35% and the precision aspect by 26% compared to the PID light tracker in previous studies.
Pemanfaatan Google Spreadsheet Untuk Akuisisi Data Online Bagi Guru SMK di Banda Aceh Dirhamsyah, Muhammad; Away, Yuwaldi; Muslimsyah; Jamil, M.; Putra, T. Edisah; Ibrahim, Masri; Novandri, Andri
Kawanad : Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 1 (2023): March
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/kjpkm.v2i1.100

Abstract

Data acquisition is the process of collecting data or information from various sources, including sensors, software, hardware, or humans, for use in analysis or decision-making. The purpose of data acquisition is to collect data that is accurate, reliable, and useful for further analysis or decision-making. In introducing the concept of data acquisition, acquisition introduction training was conducted for the teaching staff. Data acquisition training covers the process of transferring data from sensors to Google Sheets. For teaching staff at SMK Negeri 2 Banda Aceh, the use of Google Spreadsheets is still too common. Therefore, the community service team successfully carried out training activities on Wednesday, April 13, 2022. The training included an introduction to the ESP8266 microcontroller, then continued with the introduction of Google Spreadsheets, taught how to assemble hardware in the form of DHT11 sensors and ESP8266 microcontrollers, and carried out the process sending data as well as storing data on Google Sheets. This activity has a positive impact on improving the ability of teaching staff and indirectly can be applied in teaching materials or applied in everyday life.
Shrimp Pond Monitoring System using Cooperative Wireless Sensor Network Multi-Hop Technique based on Internet of Things Zickri, Zickri; Novandri, Andri; Adriman, Ramzi; Nasaruddin
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 3: November 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n3.1133.2023

Abstract

Water quality is a crucial factor in maintaining the survival and growth of shrimp. Manual water quality monitoring in shrimp ponds is no longer effective due to the need for periodic monitoring to maintain stable water quality. Therefore, online monitoring using various sensors installed in each pond is necessary. However, there are several challenges to overcome, such as the large expanse of the shrimp ponds, which may lead to data loss due to signal disruptions, and limited energy to power the sensors. To address these issues, this paper proposes the cooperative Wireless Sensor Network (WSN) technique with a multi-hop method for communication in the monitoring process. The system consists of five sensor nodes: temperature sensor, pH sensor, water level sensor, intake water flow sensor, and drain water flow sensor. The cooperative WSN multi-hop technique helps reduce energy consumption in the sensor nodes during measurement and data transmission, while also preventing data packet loss. This is achieved through the use of relay nodes that strengthen signals and forward data to the sink node. As a result, the battery life is extended, and energy usage in the monitoring process can be optimized. The system enables real-time online monitoring and can be accessed through a smartphone application. The results of this study show that the total energy consumption for data transmission in the sensor nodes is 9.64 J, while the total energy consumption for data forwarding in the relay nodes is 9.15 J. The total energy consumption in the transmit and receive processes is 18.79 J or 5.2 mWh. Therefore, it can be concluded that the energy savings of the proposed system is 4.3 mWh or approximately 45%, and is more efficient than the previous system.
Strategi Asesmen Diagnostik pada Proses Commissioning Transformator Tipe 20kV 630kVA di Fakultas Kedokteran, Universitas Syiah Kuala Away, Yuwaldi; Munadi, Rizal; Mahmuddin, Mahmuddin; Muslimsyah, Muslimsyah; Safrizal, Safrizal; Fathurrahman, Fathurrahman; Zichri, Zichri; Novandri, Andri
PESARE: Jurnal Pengabdian Sains dan Rekayasa Vol 2, No 1 (2024): Februari 2024
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/pesare.v2i1.36956

Abstract

Proses commissioning transformator adalah tahap pemeriksaan untuk memastikan operasional yang optimal pada transformator sebagai sistem kelistrikan. Sebelum melakukan commissioning, terdapat tahap pra-commissioning. Tahapan pra-commissioning melibatkan pemeriksaan dari berbagai aspek. Sementara itu, tahapan commissioning mencakup pemeriksaan tahanan isolasi, sambungan lead, level minyak, dan peralatan pengamanan. Pemasangan kabel dan pentanahan dilakukan untuk keamanan dan stabilitas. Proses ini dilakukan di Fakultas Kedokteran, Universitas Syiah Kuala untuk menjaga pasokan listrik, mendukung kegiatan medis, dan proyek penelitian. Kolaborasi antara produsen, vendor, dan petugas pelaksana yang terlibat, dalam menjalankan asesmen diagnostik sebelum diintegrasikan ke jaringan listrik PLN. Hasil commissioning yang menunjukkan hasil yang sangat baik dari hasil pemeriksaan pada berbagai aspek, termasuk kelistrikan, mekanikal, sipil, aspek sains bangunan, aspek pendinginan, aspek pemantauan dan aspek keamanan. Dengan demikian, proses asesmen diagnostik pada proses commissioning transformator tidak hanya menjamin kualitas operasional transformator secara elektrik, tetapi juga memastikan integrasi yang efisien dalam lingkungan fisik dan infrastruktur untuk mendukung operasional yang keberlanjutan.
Improved Histogram of Oriented Gradient (HOG) Feature Extraction for Facial Expressions Classification Ramiady, Luthfiar; Arnia, Fitri; Oktiana, Maulisa; Novandri, Andri
Jurnal Rekayasa Elektrika Vol 20, No 3 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v20i3.34044

Abstract

Facial expression classification system is one of the implementations of machine learning (ML) that takes facial expression datasets, undergoes training, and then utilizes the trained results to recognize facial expressions in new facial images. The recognized facial expressions include anger, contempt, disgust, fear, happy, sadness, and surprise expressions. The method employed for facial feature extraction utilizes histogram-oriented gradient (HOG). This study proposes an enhancement method for HOG feature extraction by reducing the feature dimension into multiple sub-features based on gradient orientation intervals, referred to as HOG channel (HOG-C). Classifier testing techniques are divided into two methods for comparisonsupport vector machines (SVM) with HOG features and SVM with HOG-C features. The testing results demonstrate that SVM with HOG achieves an accuracy of 99.9% with an average training time of 18.03 minutes, while SVM with HOG-C attains a 100% accuracy with an average training time of 18.09 minutes. The testing outcomes reveal that the implementation of SVM with HOG-C successfully enhances accuracy for facial expression classification.