Jurnal Elektro (p-ISSN: 1979-9780; e-ISSN: 2746-4288) is a double-blind peer-reviewed, by a minimum of two independent reviewers, open-access scientific journal published by the Department of Electrical Engineering, School of Bioscience Technology and Innovation, Universitas Katolik Indonesia Atma Jaya. The journal aims to provide a platform for the dissemination of high-quality research and advances in the field of electrical engineering. Jurnal Elektro welcomes original research articles and reviews covering a broad spectrum of topics, including but not limited to power engineering, electronics, control systems, robotics, telecommunications, computer engineering, operations research, information systems, human-machine interaction, service quality, algorithms, artificial intelligence, internet of things, statistics, and various other relevant subfields contributing to the advancement and practical implementation of electrical engineering. By fostering academic and industrial collaborations, Jurnal Elektro strives to showcase cutting-edge research and technological innovations, making significant contributions to the global scientific community. Editor in chief : Dr. Ir. Karel Octavianus Bachri, S.T., M.T. The journal is published twice a year, in April and October. The editorial team can be contacted at: Dept. of Electrical Engineering, School of Bioscience Technology and Innovation, Atma Jaya Catholic University of Indonesia, BSD City, Jl. Cisauk, Sampora, Cisauk Tangerang, Banten 15345 Tel. : +62 21 570 8826 Fax : +62 21 579 00573 Email : jurnal.elektro@atmajaya.ac.id p-ISSN: 1979-9780 e-ISSN: 2746-4288 indexed by:
Prodi Teknik Elektro, Fakultas Teknik Unika Atma Jaya Jakarta
Design and Implementation of a Vision-based Wheeled Mobile Robot Using HSV Color Segmentation and P-D Control
This study presents the design and implementation of a wheeled mobile robot capable of detecting and tracking a ping-pong ball using vision-based processing. The system integrates a Raspberry Pi 3 Model B+ as the main controller, a Raspberry Pi Camera Rev 1.3 for visual input, and DC motors driven by an L298N motor driver for actuation. Object detection is achieved through color segmentation in the HSV color space using the OpenCV library, followed by morphological filtering and contour analysis. A proportional-derivative (PD) control algorithm is employed to adjust motor speeds dynamically based on the ball's horizontal position in the frame. The experimental results demonstrate that the robot can successfully detect and follow a ping-pong ball, although it exhibits limitations in processing speed and motion stability. The average frame rate during operation was 5 FPS, which is sufficient for basic tracking tasks but suboptimal for high-speed applications. This project highlights the feasibility of vision based robotic systems for simple object tracking tasks.
Deep Learning-Based Brain Tumor Classification Using Convolutional Neural Network
An essential noninvasive medical diagnostic technique is magnetic resonance imaging (MRI), which is particularly useful for identifying brain cancers. While earlier algorithms proved effective on smaller MRI datasets, their performance suffered on bigger datasets. This study addresses the need for a swift and reliable brain tumor classification system capable of sustaining optimal performance across comprehensive MRI datasets. The convolutional neural network is implemented using the Keras library, incorporating the ResNet50 architecture as a pre-trained model. The ResNet50 model is fine-tuned for the specific brain tumor classification task, with a Global Average Pooling layer, dropout, and a final dense layer with softmax activation. Data augmentation techniques are employed to enhance the model’s robustness, including rotation, width and height shifts, and horizontal flips. The training process involves optimizing the model using the Adam optimizer with a learning rate of 0.0001. Early stopping, learning rate reduction on plateau, and model checkpointing are implemented as callbacks to ensure efficient training and prevent overfitting. The proposed model achieves a remarkable accuracy of 99.28 percent after 15 epochs. The classification task involves distinguishing among four classes: glioma, meningioma, pituitary, and no tumor.
Classification Of Multi-Class Face Expression Using Modification Of VGG-16 Model
In the era of modern technology, facial recognition has become an important application in various fields, such as security, education and health. One method used to recognize faces is a Convolutional Neural Network (CNN), specifically the VGG-16 architecture which is known for its consistent performance. But even though CNN can recognize faces, its accuracy in recognizing faces is inadequate. This research aims to increase the accuracy of facial expression classification so that it is more optimal by modifying the CNN VGG-16 architecture. This research uses GridSearch techniques, K-Fold Cross Validation, and utilizes multiple datasets. The dataset used consists of two image datasets, namely SMIC and SAMM facial-micro expressions, each of which has been normalized and converted to a grayscale scale measuring 48x48 pixels. The GridSearch process is applied to optimize parameters such as the number of filters, learning rate, dropout rate, activation function, and batch size. The K-Fold Cross Validation technique with five folds was used to ensure the generalization of the model to new data. The research results show that this modification is able to achieve validation accuracy of up to 98.31% in the training process, showing a significant improvement compared to the standard method. And showed an increase in accuracy in testing of 98.04% in research.
Performance Analysis of Deep Neural Network to Noisy Digit Dataset
This work investigates the impact of noise on model performance by training a neural network on a digit dataset with varying Signal-to-Noise Ratios (SNR) to assess its resilience and generalization ability. The experimental setup involved training the model on datasets with noise levels ranging from clean images to highly distorted ones (SNR 5%–25%), analyzing accuracy, mini-batch loss, and training time. Results indicate that while the model achieves high accuracy (96.88%) at mild noise levels (SNR 5%), performance declines significantly at higher noise levels, with accuracy dropping to 78.91% at SNR 25%. The analysis of mini-batch loss and training time reveals that noise slows convergence and increases computational complexity. The confusion matrix further confirms that while the model effectively distinguishes between classes, noise-induced misclassifications become more frequent at lower SNRs. These findings emphasize the importance of noise reduction techniques and data preprocessing to improve model robustness in real-world applications.
Pengukuran Backup Time Uninterruptible Power Supply Untuk Penentuan Kapasitas Baterai VRLA
A battery is a device that stores power in an Uninterruptible Power Supply (UPS) system. The most common type of UPS battery found today is Valve Regulated Lead Acid (VRLA). So that the UPS can work optimally according to its capacity and backup time, it is necessary to determine the battery capacity. In this research, the capacity of the VRLA battery on a particular UPS was determined based on direct testing and based on calculations. VRLA battery capacity calculations refer to the UPS and battery datasheet. The calculation stage starts from calculating the current and battery power used according to the load power absorbed by the UPS and referring to the table of constant current discharge and constant power discharge characteristics. Determining battery capacity based on testing is done by measuring the backup time of the UPS. The calculation results and test results directly show that there is a difference in backup time because the battery used is an old stock battery. The research results also prove that determining battery capacity by calculation can ensure that the battery capacity is more appropriate or not too large so it is more economical.
Frequency Extraction of Phonocardiogram Signal using Fourier Transform
This article presents Fourier Transform application to extract features of Phonocardiogram Signals into its frequency components. Data was taken from Physionet Dataset of Phonocardiogram which comprises of normal and abnormal heart condition. Raw data was preprocessed using time clipping of 2 seconds at certain area that contains less noise. A lowpass filter was applied to denoise the raw signals. Experiments show the PCG of normal hearts has a dominant frequency of 50Hz to 150Hz, with the subdominant frequencies of 450 Hz to 650 Hz. The subdominant frequency of the normal hearts sometimes show anomaly with more amplitude compared to the dominant frequency.
Pengembangan Perangkat Lunak Untuk Akuisisi Data Konsumsi Daya Listrik Dari Power Meter
Technological developments make it possible to monitor electricity consumption in real-time via the internet. The system developed uses a power meter to collect data, Python to process data and IoT connectivity via NodeMCU ESP8266 to send data to the internet. Python is used so that measurement data can be processed and presented in an easy-to-understand format. The test results show that electrical data measurements can be displayed with an error ranging from 0.04% -11.56%. This is because there is a delay from the time the power meter is measured until the data is displayed on ThingSpeak.
Studi Performa Panel Surya 100 WP Menggunakan Software Homer Di Universitas Pamulang
Studies on designs and systems for solar panels are currently continuing to be developed. One application is to design a Homer-based solar power generation system (PLTS) with a solar panel capacity of 100 Wp and analyze the system performance at different loads. This research was conducted to determine the amount of power that solar panels can produce, load consumption, and determine a suitable system configuration to meet electricity needs at different loads. The method used is design, determining parameters on the homer and creating a simulation with loading. The research results show that the amount of power that can be produced by solar panels is 75,2kWh/year and can meet electricity needs at different loads. It is hoped that this research can be a solution to optimize the use of solar energy on a small scale and support renewable energy programs in Indonesia.
Implementasi dan Analisis Alat Kompres Demam Suhu Hangat dengan Sensor DS18B20 dan Pengendali Arduino Uno
Fever is a condition where the body temperature rises above normal levels, often caused by an infection. Non-medical management of fever can be done by using cold or warm compresses. Warm compresses are more effective but require a complex and repetitive process. This study is the design of a Digital Fever Compress Device using warm temperature based on Arduino Uno. The Digital Fever Compress Device is designed for non-medical fever management. The Digital Fever Compress Device is equipped with a DS18B20 sensor, Liquid Crystal Display (LCD), Relay, cartridge heater as a heating element, three pushbuttons, XL4005 stepdown module, and one On-Off switch. The Digital Fever Compress Device can produce warm temperatures and adjust them according to the user's preferences with a minimum limit of 37.5°C and a maximum of 42°C with a timer for 20 minutes. Environmental temperature affects the temperature setting processing carried out by the microcontroller. Based on the tests conducted in an air-conditioned room, the average time from the initial temperature to the setpoint is 6 minutes and 15 seconds, and the temperature increase from the setpoint ranges from 45.6°C or 15.079%. Meanwhile, testing in a non-air-conditioned room, the average time from the initial temperature to the setpoint is 2 minutes and 26 seconds, and the temperature increase from the setpoint ranges from 44.64°C or 12.37%.
Perancangan Aplikasi Koperasi Berbasis Android
The development of information technology cannot be separated from the use of mobile applications, which are increasingly varied. Mobile applications allow users to easily connect to internet services anywhere. Cooperatives are joint business entities that generally still use the manual method for recording members, transactions and so on, which can lead to human errors and time inefficiencies. The existence of a website-based cooperative mobile application that is implemented on smartphones using the Xamarin.Forms framework can reduce these problems. Smartphones will make online cooperatives more effective because they are portable, easy to use and more affordable.
Perbaikan Kurva Beban Harian pada Industri Kecil: Studi Kasus PT. X
This paper presents the improvement of daily load and load balance curve of home-scale garment industry with the study case in PT. X. Research is started with load measurement on every machine, proceeded by plotting schedule of each machine. The next step is rescheduling daily load and per-phase load balancing. Initial data shows unbalance load sharing between phase with the average load of 4916 kW and standard deviation of 2077. After being rescheduled and phase rearrangement, the interphase load sharing is more balance, with the average load of 4903 kW and standard deviation of 952.
Perbandingan Algoritma Machine Learning menggunakan Orange Data Mining untuk Klasifikasi Jenis Kendaraan pada Sistem Tilang Digital
This paper discusses the application of the Orange Data Mining application to compare several machine learning algorithms for classifying vehicle types in digital ticket systems. This research compares and analyzes the logistic regression algorithm, Support Vector Machine (SVM) and Neural Network (NN) to solve vehicle classification problems in digital traffic tickets. The research results show that in the training process and based on the dataset used, the algorithms that have the highest level of accuracy are Logistic Regression, Neural Network and Support Vector Machine. Meanwhile, during the testing process, all algorithms in the model were able to carry out classification with 100% accuracy
Comparison of Actual Results and PVSyst Simulation in the Design of Off-Grid Solar Power Generation System (PLTS) in Karuni Village, Southwest Sumba
This research aims to compare the actual production with the simulations using the PVSyst software for the Off-Grid Solar Power Plant (PLTS) in Karuni Village, Southwest Sumba. The Off-Grid PLTS in Karuni Village is a vital solution for improving remote areas' electricity access. Actual energy production data from the PLTS were obtained from monitoring systems, while simulation results were obtained through PVSyst. The analysis results indicate a difference of approximately 10% between the actual and simulated results. It observed that it is influenced by variability in local weather conditions, maintenance, system management levels, and limitations of the simulation model. The implications of this research emphasize the importance of using accurate data in simulations, improving PLTS system maintenance, and developing more sophisticated simulation models. Recommendations for further research include further analysis of factors influencing the differences in results. This study provides valuable insights into the planning and management of Off-Grid PLTS. It offers perspectives on enhancing the accuracy of future PLTS system planning and management.
Sistem Pemilahan Barang Berdasarkan Deteksi Label Menggunakan Vision Sensor
Sorting goods based on the results of checking packaging labels is an important process in controlling production quality in industry. Many industries still carry out manual sorting and label checking processes, which results in low productivity levels and is susceptible to human error. This research develops an automation system for sorting goods based on label inspection using vision sensors, programmable logic controller (PLC), and robot arm. The system controlled by a PLC will read and detect damage to packaging labels by using VeriSens vision sensor and sort them using a robot arm according to predetermined stock keeping unit (SKU) categories, namely SKU 1, SKU 2, SKU 3, SKU 4, and rejected goods. The pneumatic system is used as an actuator to push goods onto the conveyor, moving the robot arm with three degrees of freedom and vacuum. Detection is carried out by applying the edge detection concept to read text, images and code that are reprocessed with the VeriSens Application Suite software. The success rate of the goods sorting system reached 90% with a reading speed of 0.389 seconds and a work process duration ranging from 21.54 seconds to 28.99 seconds.
Effect of Combining of Shaping at Magnet Edge and Dummy Slotting at Stator Core on the Cogging Torque Reduction in Permanent Magnet Generator
Effect of combining the shaping at magnet edge and dummy slotting at stator on the cogging torque reduction in permanent magnet generator was studied. The cogging torque is the most issues in permanent magnet generator application, since it effects to reduce the generator performance. A permanent magnet generator with 24 slots and 20 poles structure is presented. For purpose of study, in the beginning the permanent magnet generator with conventional structure has been investigated as the basic reference of initial structure. In order to improve the performance of the permanent magnet generator, the magnet edge was shaped but the stator core is kept remain conventional structure. It can be found that the magnet edge effects to inprove a little bit of the performance of the permanent magnet generator. In the next investigation, the magnet edge slotting and dummy slotting in stator core of the permanent magnet generator was combined. Using the FEMM 4.2, the cogging torque value of the proposed of permanent magnet generator were analysed and compared. It was found that cogging torque reduction of the permanent magnet generator with combining the dummy slotting at stator core and magnet edge shaping can reduce the cogging torque from 0.0028554 N.m (intial base line) to 0.0000165 N.m (proposed model). In other word, the cogging torque can be to around 99.42 % compared with the base line. The magnet flux density at core of the permanent magnet generator proposed can be reduced to 35 %.
Sistem Pemantauan Cerdas Berbasis Internet of Things pada Pusat Perbelanjaan
Shopping centers in Indonesia are faced with the problem of corona virus pandemic. Shopping centers were temporarily closed by the government and experienced a decline in visitors and even income during the pandemic. In order for shopping centers to earn sufficient income, the government provides a policy for shopping centers by limiting the number of visitors, checking temperature using a thermo scanner or thermo gun, and using masks according to health protocol rules. For this reason, an intelligent monitoring system is needed to monitor the density of the number of visitors and check the temperature automatically to prevent transmission of the corona virus from crowded shopping centers. The intelligent monitoring system is realized in miniature using NodeMCU as a microcontroller, web pages as interface pages for shopping center managers in system monitoring, applications as interface pages for managers in monitoring systems and applications as interface pages for the public so they can see the number of visitors and remaining capacity. at a shopping center. The overall test results percentage obtained is 100% and it can be concluded that the intelligent monitoring system can work well.
Implementasi IoT dengan ESP 32 Untuk Pemantauan Kondisi Suhu Secara Jarak Jauh Menggunakan MQTT Pada AWS
The development of the internet of things (IoT) creates many new innovations in the industrial sector aimed at increasing effectiveness. One of them is to monitor the condition of industrial process machines remotely as discussed in this study. This monitoring can be done using a device connected to the internet. The design of this system requires a microcontroller with an ESP32 wifi module as a data receiver and sender. The data sent is data from the temperature sensor. The data is in the form of simulation data generated from the program and has a random number. Machine-to- server data communication uses the Message Queuing Telemetry Transport (MQTT) protocol. The entire machine-to-server, server-to-server communication system will be carried out in the cloud using a cloud computing platform, namely Amazon Web Services (AWS). The test results show that the payload and temperature data sent from the microcontroller can be stored in the database. To see the reliability of the system, two Normal and Stress Tests were carried out, with a success percentage of 100% fo r data storage to the database on two tests and 16.67% failure in sending data on the Stress Test. The two tests were arranged under different conditions.
Designing a Website-Based Cooperative Application
The development of the times in the field of technology allows information to be obtained quickly and easily. We often encounter exchange of information in the world of work, one of the business entities that is very dependent on the exchange of information is cooperatives. In traditional cooperatives, the use of services requires users to come directly to the physical location of the cooperative. The process of recording user data and transaction history is also still done manually, namely by writing it on a book, so it takes a long time. The cooperative system created is a web-based application with the Laravel framework and cooperative data managed using MySQL. Designing a web-based application will provide easy access to cooperative services and decrease the time required for transaction processing for users and increase the efficiency of cooperative management for cooperative managers.
A Preliminary Survey of Color Discrimination Among Indonesia Female Subjects Using Farnsworth-Munsell Hue Color Test
This study aimed to conduct a preliminary survey of the color discrimination test among Indonesian samples. The study involved 26 participants of university students and office workers. To test the ability of color discrimination, the Farnsworth-Munsell (FM) 100 Hue Color Vision Test was used. Farnsworth-Munsell test scoring software was also used to obtain the total score of each participant. Using the FM 100-hue test, the participants were classified into superior, average and low color discrimination ability. The results showed that that 19.2% female participants were classified as superior for color discrimination ability. Majority of participants were classified as average. Meanwhile for low classification, only 3.9% were classified as low color discrimination ability. Currently, many companies and industries have great need for workers with good characterized and accurate color vision. However, the study of color discrimination is still limited and unknown in Indonesia. Through this study, hopefully attention for a broader study with a larger scale could be obtained.
Simulasi Pengendali Suhu Menggunakan Algoritma Proportional, Integral, Derivative Berbasis Programmable Logic Controller Pada Modul Plant Honeywell
The process of heating in the food industry is often can be found, start from inserting water and the heating process begin to reach a certain temperature, so the process of controlling temperature is one of the important things in the food industry. Temperature controller is an important thing, to maintain certain temperature, so that it did not exceed or lower than needed. This system uses Honeywell programmable logic controller (PLC) as the automation based system. In this research, Honeywell PLC controller will be using proportional, integral, derivative (PID) algorithm to maintain the required temperature. The research will be using the Honeywell module in Automation Laboratorium, Engineering Faculty, Atma Jaya Catholic University of Indonesia. The heating process will begin if the water level in the tank is filled to the required level. System will turn on the heater based on the PID output in the PLC program, so the temperature is maintained to a required setpoint 35oC. The simulation system can be controlled through a human machine interface (HMI) HCix08 that was made with XDesigner Plus software. The maintained temperature has ±5% tolerance or ±1,75˚C. The result of the research shows that the best parameter for setpoint 35˚C is using a PD controller with the values for Kp is 8 and Kd is 2.
Sistem Pemberi Makan dan Minum Pintar Pada Hewan Peliharaan Berbasis Website dan Aplikasi Android
Based on a survey by “Mars”, about 59% of dogs and 52% of cats weighed more than they should. This is the motivation of this research in designing a feeding and drinking automation for pets so that it is easier for owners to take care their pet's health diet, and so that owners don't have to worry about forgetting to feed their pets. To connect to the internet, ESP32 is used. The supporting components consist of load cell (weight sensor), three ultrasonic sensors (proximity sensor), servo motor and pump motor. These components are combined to carry out the function of feeding and drinking automatically. The device will run after being given an order via website or application. For the feeding system, the animal owner can provide input on the schedule, frequency and portion of feeding. While the drinking system, the owner can press the calibration button and the pause button. Tests are carried out on each sensor, to measure its accuracy and testing of the entire system is carried out to ensure all components work together to carry out their functions. The test results show that every hardware and software component has worked in accordance with the designed objectives.
Klasifikasi Gender Berdasarkan Gambar Menggunakan Metode Deep Learning Pada MATLAB
In the present era, machine intelligence, also known as Artificial Intelligence (AI), is demanded not only to execute specific commands but also to recognize, analyze, or even make decisions, thereby providing desired outputs. By harnessing the power of AI, it is anticipated that desired outcomes will be more accurate and goal achievement will be optimized, minimizing losses. With the capabilities of AI in mind, a research study has been conducted on AI's ability to analyze and make decisions based on specific data. In this study, data in the form of images of men and women were utilized. The objective of this research is to analyze the ability of AI, particularly in gender classification. The method employed in designing this system is Deep Learning, with GoogLeNet as the Convolutional Neural Network utilized. In testing, the data accuracy ranged from 61.8% to 100% for the system without training algorithm options and from 97.5% to 100% for the system with training algorithm options. Testing was also carried out on a smaller set of training data and grayscale images, yielding lower accuracy ranges. From this research, it can be concluded that the quantity of training data, image preprocessing, and training algorithm options are crucial indicators for enhancing prediction accuracy.
Prototipe Sistem Pencegah Banjir dengan Pengontrolan Pintu Air Waduk menggunakan Kontrol PID berbasis PLC & HMI
The purpose of research on this flood prevention system prototype design is to prevent flood caused by overflowing reservoir water. This system prototype uses the Modicon M340 Programmable Logic Controller as a controller and is equipped with a Human Machine Interface feature as a medium for managing and monitoring system performance virtually. This system is supported by a Water-Level Sensor to measure the water level in the reservoir and also the rate of addition of water in the reservoir. The sluice mechanism is driven by a Stepper Motor assisted by the ULN2003 Driver Module based on Proportional, Integral and Derivative (PID) control to maintain the water level in the reservoir. PID control in this system successfully runs optimally at constant KP = 3.5, KI = 2, and KD = 1, with an error result of 0,048%. This constant has the best response time compared to other constants, where rise time = 11.76 s, settling time = 13.95 s, and steady state time = 14.07 s.
Perancangan Jaringan Fiber To The Home Berbasis Gigabit Passive Optical Network Di Citra Garden Puri Cluste Denza
This research aims to design a GPON-based Fiber to The Home (FTTH) line in the Citra Garden Puri cluster Denza . The method used is to carry out field observations, by conducting surveys to determine the need for equipment that will be used in designing the route. After the survey is conducted, this project requires Google Earth Pro software to do the mapping of the spot that is used for the ODP and to create passages for the fiber. To make sure that all planning already meets the requirement, there are several calculationdone in this research such as; link loss budget, power link budget, power margin and risetime budget. The distance that were used in the calculation are calculated from the STO Cengkareng until the ONT on each customer. Based on the calculation, the result of the biggest loss for link loss budget are obtained from the upstream, in the amount of 22,0456 dB and the loss from downstream are equals to 21,5721 dB. The result that obtained for the upstream loss of power link budget are equals to -17,0456 dBm and -16,5172 dBm for downstream. The next calculation is power margin, from this project we obtained the lowest power margin for the upstream 6,9544 dB and 7,4288 dB for downstream. The last calculation obtained for this project is rise time budget, from the calculation the shortest data for the rise time budget upstream is 0,1001 ns and for the downstream is 0,1019 ns. Based on all the calculation, this project can be concluded as a success because all the calculation are between the boundary that is tolerated by PT Telkom.
Analisis Audio Capture untuk Pengumpulan Data pada Smart Speaker
Internet of Things or IoT is a technology that is currently trending, because it can help human in their daily routine. One of the IoT product that used in homes is smart speaker. However, every latest technological innovation does not escape from vulnerabilities and one of them is the microphone on the smart speaker. Several studies and research have found that security vulnerabilities in smart speakers, such as dolphin attacks and audio capture. To find out how this audio capture technique works, an experiment was made to understand how it works and the impact of this technique. This experiment uses a smart speaker with voice assistant Alexa, using the Alexa Skills Kit services and Flask-Ask framework to create an audio capture program. The results of this program testing are expected to be used as a benchmark to prevent smart speakers from becoming the target of this technique anymore.
Internet of Things Analystics Menggunakan ELK Stacks Dalam Pabrik Perangkat Server
The internet is an information and communication technology that makes it easier for human activities to access data and send information into networks. For industry, the internet is also used to store data both internally and externally. There are several application facilities that are open source to help the industry save data via the internet to the cloud, one of which is the ELK stack. In this research, a simulation of a temperature and humidity monitoring system is designed for a server device factory and simultaneously calculates the amount of production. The data obtained is sent to Elasticsearch as a cloud so that the measurement data can be monitored and visualized in the form of graphs. The system is realized using a microcontroller, ESP8266, DHT11 sensor and proximity sensor. This design is equipped with an ELK system that can collect data and filter the required data so that it can be monitored and visualized in real time. The results of testing the temperature and humidity obtained are in the optimal value range and also proves that this research can be used on a large scale. It is recommended that this design be implemented in a factory or smart home to make it easier to obtain and retrieve the required data.
Strategi Persaingan Pemasaran Indomaret dan Alfamart di Salatiga Menggunakan Game Theory
Indomaret and Alfamart are minimarket businesses that are currently experiencing significant growth, especially in the city of Salatiga. Each company strives to achieve maximum profit, and thus, it is essential to determine the most optimal competitive strategy to attract customers. This research was conducted using a questionnaire to understand what influences consumers in choosing a minimarket for shopping, providing valuable insights for determining minimarket strategies. Game Theory is employed to represent the respondents. The results of the study indicate that Alfamart will employ a location-based strategy in their stores, while Indomaret will utilize discount and promotion strategies for their easily accessible minimarkets.
Prediksi Ekspor Migas Indonesia Dengan Double Exponential Smoothing
In Indonesia, there are several forms of exports, one of which is oil and gas exports. The Double Exponential Smoothing method is a forecasting method that can be used to forecast oil and gas export data. This method uses two smoothing parameters, namely the average smoothing parameter alpha (α), the trend smoothing parameter beta (β). In this study, the population used is data on oil and gas exports in Indonesia. And the sample used is Indonesia's oil and gas export data from January 2020 to October 2021, we get 22 data sourced from the Central Statistics Agency (BPS). The Double Exponential Smoothing method is used because the data to be processed has a trend, both an up and a down trend and gas exports in Indonesia have an up and down pattern. The Double Exponential Smoothing method can also predict the prediction of oil and gas exports in Indonesia in the next months, November 2021 to February 2022. To process the data, the researcher used the Holt Double Exponential Smoothing method .
Pengolahan Data Buah Menggunakan Metode Deep Learning
The use of artificial intelligence is increasingly widespread, one of which is in the use of detecting an object. In general, object detection is often used in tools that capture images such as cameras on cell phones or CCTV which is applied to e-tickets (electronic tickets). With deep learning technique in this article to detect fruit, it is hoped that it can be useful in everyday life such as a fruit sorting machine based on the level of maturity based on color or separating fruit from leaves in the fruit picking process.
Simulasi Sistem Pengendalian Motor Stepper dengan Metode Pulse Width Modulation
This paper discusses the control of a stepper motor using Pulse Width Modulation (PWM) methods. In this paper, the author presents two designs: one using a stepper motor controller with an astable multivibrator as a pulse generator and the other utilizing a microcontroller as the pulse generator. The design of the stepper motor controller with an astable multivibrator involves using the IC timer 555 to control the stepper motor speed and a latch circuit to control the direction of the stepper motor rotation. Meanwhile, the design of the stepper motor controller with a microcontroller employs the Arduino UNO R3 to control both the direction and speed of the stepper motor. Testing is conducted through a simulation of the system design using Proteus software. From the test results, it is observed that an increase in the PWM value leads to a faster rotation speed of the stepper motor, conversely, a decrease in PWM value results in a slower rotation speed of the stepper motor.