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Sinkron : Jurnal dan Penelitian Teknik Informatika
Published by Politeknik Ganesha Medan
ISSN : 2541044X     EISSN : 25412019     DOI : 10.33395/sinkron.v8i3.12656
Core Subject : Science,
Computer Science & IT
Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial Neural Network 14. Fuzzy Logic 15. Robotic
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 1,196 Documents
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Using Edmodo as a Media of E-Learning Learning in Educational Technology Courses Thoiyibi, Muhammad; Nuzli, Muhammad
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11349

Abstract

Abstract: New concepts in IT-based learning, often known as e-learning, were born because of the use of technology in the learning process. Teachers can choose from a variety of online learning media as a medium of learning in e-learning, one of which is Edmodo. Edmodo is a Non-Governmental Organization (NGO) that offers several tools for instructors to use in their classrooms. The purpose of this study is to describe the usage of Edmodo as an e-learning medium in pai class education technology courses, to determine Civitas Academica's reaction to Edmodo as an e-learning medium, and to determine the benefits and drawbacks of Edmodo as an e-learning medium. This study employs a qualitative technique in conjunction with descriptive analysis. Interviews, observations, and documentation were utilized to collect data in this study, which were aided by research equipment in the form of interview grids. There are additional guidelines for observation. This study took place in PAI classes, with 70 students and teachers from Educational Technology courses serving as the primary informants. The findings of this study revealed that Edmodo can be used as a supplemental class in PAI classes and that PAI students can benefit from the use of PAI. Edmodo as an e-learning learning medium, teachers are also greatly aided by its existence; as an e-learning learning medium, Edmodo has many advantages, particularly in terms of features offered, and the disadvantages of using Edmodo as an e-learning learning medium are highly dependent on the internet network.
A SISTEM PENDETEKSI SUHU RUANGAN: SISTEM PENDETEKSI SUHU RUANGAN DENGAN MENGUNAKAN ARDUINO Afira, Riandana; Purnama, Ayu Widya; Putra, Teri Ade; Wisky, Irzal Arief
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11351

Abstract

In this era, all agencies, be it companies, offices, and industries, take advantage of technological developments with computerized systems. This progress gives an important role in human life. Currently, computers are not only used to process data, they can even be used to control an electronics-based system, such as in the field of controlling external equipment, controlling robots, electronic equipment, and so on. Along with the development of these technologies, the authors try to develop a type of electronic component, namely the LM35DZ Temperature Sensor and Arduino. This research was conducted to create a system that can measure temperature in a room using Arduino and the LM35DZ temperature sensor as the main components. This LM35DZ temperature sensor functions to convert the temperature scale into an electrical quantity in the form of a voltage with a high level of precision but is very simple. Arduino functions as a central place for processing all data and instructions, so that it can facilitate the development of a microcontroller application, starting from writing source programs, complications, uploading complication results and testing serial terminals. The use of Arduino in this tool is combined with ATMEGA 328 and the source program used is the C programming language.
K-Means Performance Optimization Using Rank Order Centroid (ROC) And Braycurtis Distance Irwandi, Hafiz; Sitompul, Opim Salim; Sutarman, Sutarman
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11371

Abstract

K-Means is a clustering algorithm that groups data based on similarities between data. Some of the problems that arise from this algorithm are when determining the center point of the cluster randomly. This will certainly affect the final result of a clustering process. To anticipate the poor accuracy value, a process is needed to determine the initial centroid in the initialization process. The second problem is when calculating the Euclidean distance on the distance between data. However, this method only gives the same impact on each data attribute. From some of these problems, this study proposes the Rank Order Centroid (ROC) method for initializing the cluster center point and using the Braycurtis distance method to calculate the distance between data. With the experiment K=2 to K=10, the results obtained in this study are the proposed method obtains an iteration reduction of 6.6% on the Student Performance Exams dataset and 19.3% on the Body Fat Prediction dataset. However, there was an increase in iterations on the Heart Failure dataset by 24.2%. In testing the cluster results using the Silhouette Coefficient, this method shows an increase in the evaluation value of 5.9% in the Student Performance Exams dataset. However, the evaluation value decreased by 8.3% in the Body Fat Prediction dataset and 3.3% in the Heart Failure dataset.
Super Resolution Generative Adversarial Networks for Image Supervise Learning Lupitha, Mariska; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11373

Abstract

The E-Tilang application system has been widely used to support modern traffic, whereas protocol roads in big cities in Indonesia are already widely used. In principle, the plate number detection tool uses image recognition for detection. Image number plates on vehicles cannot always be read clearly, this is what causes the detection method to be a problem if the image plate number is further processed. The method for processing the plate number image uses deep learning and computer vision methods. For the condition of the image plate number that is not clear, the process of improving the image resolution from low resolution to high resolution is carried out, by applying Generative Adversarial Networks. This method consists of two main parts, namely Generate and Discriminator. Generate serves to generate an image and the Discriminator here is to check the image, can the image plate number be read or not? So that if the image plate number cannot be read, then the process is carried out again to the Generator until it is received by the Discriminator to be read. The process does not end here, the results will be carried out in the next process using Convolutional Neural Networks. Where the process is to detect the plate number image according to the classification of the plate number according to the region. The point is that an unclear image becomes clear by increasing the resolution from low resolution to high resolution so that it is easily read by the Convolutional Neural Network (CNN) algorithm so that the image is easily recognized by the CNN Algorithm. This becomes important in the CNN algorithm process because it gets the processed dataset. To produce a good model, preprocessing of the dataset is carried out. So that the model can detect the image well in terms of model performance.
Style Transfer Generator for Dataset Testing Classification Wedha, Bayu Yasa; Karjadi, Daniel Avian; Wedha, Alessandro Enriqco Putra Bayu; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11375

Abstract

The development of the Generative Adversarial Network is currently very fast. First introduced by Ian Goodfellow in 2014, its development has accelerated since 2018. Currently, the need for datasets is sometimes still lacking, while public datasets are sometimes still lacking in number. This study tries to add an image dataset for supervised learning purposes. However, the dataset that will be studied is a unique dataset, not a dataset from the camera. But the image dataset by doing the augmented process by generating from the existing image. By adding a few changes to the augmentation process. So that the image datasets become diverse, not only datasets from camera photos but datasets that are carried out with an augmented process. Camera photos added with painting images will become still images with a newer style. There are many studies on Style transfer to produce images in drawing art, but it is possible to generate images for the needs of image datasets. The resulting force transfer image data set was used as the test data set for the Convolutional Neural Network classification. Classification can also be used to detect specific objects or images. The image dataset resulting from the style transfer is used for the classification of goods transporting vehicles or trucks. Detection trucks are very useful in the transportation system, where currently many trucks are modified to avoid road fees
Development of District Civil Service Applications Ranuharja, Fadhli; Ambiyar; Indarta, Yose; Samala, Agariadne Dwinggo; Ika Parma Dewi
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11377

Abstract

This study aims to provide the needs for institutions such as urban villages to provide services, information to residents, making it easier to socialize activities and assist in the administration of correspondence permits from the urban village. The new system needs to be implemented in Tanjung Ayun Sakti Village as a solution to overcome obstacles in accessing information and services in Tanjung Ayun Sakti Village. The application of a population service information system can have a fairly good impact and be beneficial for all interested parties. The development of this system uses the PHP programming language, CodeIgniter framework, XAMPP as a database server for simulation on localhost and the SDLC (Software Development Life Cycle) method. From the results of the development of this information system, the validity test was carried out by experts, then the practicalists are very good. aims to assist the population service process in the form of sending a permit online.
Heavy-loaded Vehicles Detection Model Testing using Synthetic Dataset Karjadi, Daniel Avian; Wedha, Bayu Yasa; Santoso , Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11378

Abstract

Currently, many roads in Indonesia are damaged. This is due to the presence of large vehicles and large loads that often pass. The more omissions are carried out, the more damaged and severe the road is. The central government and local governments often carry out road repairs, but this problem is often a problem. Damaged roads are indeed many factors, one of which is the road load. The road load is caused by the number of vehicles that carry more than the specified capacity. There are many methods used to monitor roads for road damage. The weighing post is a means used by the government in conducting surveillance. This research is not a proposal to monitor the road, but this is only to create a model for the purpose of detecting heavily or lightly loaded vehicles. This research is to classify using Convolutional Neural Network (CNN) with pre-trained Resnet50. The model generated from the Convolutional Neural Network training process reaches above 90%. Generate Image deep learning algorithms such as the Generative Adversarial Network currently generate a lot of synthetic images. The testing dataset that will be used is generated from style transfer. The model is tested using a testing dataset from the generated style transfer. Style transfer is a method of generating images by combining image content with image styles. The model is pretty good at around 92% for training and 88% for testing, can it detect image style transfer? The Convolutional Neural Network model is said to be good if it is able to recognize the image correctly, considering that the accuracy of the model is very good. One of the reasons why the training model is good but still makes errors during testing, then the image dataset is overfitting
Compare VGG19, ResNet50, Inception-V3 for Review Food Rating Andrew, Andrew; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11383

Abstract

The food industry is undergoing a phase of very good improvement, where business actors are experiencing very rapid growth. Creative ideas are many and creative on several social media. When an online business is growing rapidly, many managers in the food sector market their products through online media. So it is quite easy for customers to place orders via mobile. Especially during the COVID-19 pandemic, where a ban on gatherings has become a government recommendation for many food business actors to sell online. Since then, almost all food industry players have made their sales online. There are many advantages of doing business online. The food served is in the form of pictures that attract market visitors so that it can create its own charm. Food is just a click away to order, and the order comes. No need to queue and everything has been delivered to the ordered goods. After the ordered goods arrive, the customer reviews the food or drink. Because customer reviews are the result of customer ratings. The result of the review is one of the sentiment analyses, which in this study is in the form of a review of the images available on the display marketplace. The method used is Convolutional Neural Network. The dataset will be extracted features and classifications. The research will do a comparison using VGG19, ResNet50, and Inception-V3. Where the accuracy of VGG19 = 96.86; Resnet50 : 97.29; Inception_v3 : 97.57.
CycleGAN and SRGAN to Enrich the Dataset Priswanto, Budi; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11384

Abstract

When developments in the field of computer science are growing rapidly. For example, the development of image or video predictions for various fields has been widely applied to assist further processes. The field of computer vision has created many ideas about processing using deep learning algorithms. Sometimes the problem with using deep learning or machine learning is in the availability of the dataset or the unavailability of the dataset. Various methods are used to add to or enrich the dataset. One way is to add an image dataset by creating a synthetic image. One of the well-known algorithms is Generative Adversarial Networks as an algorithm for generating synthetic images. Currently, there are many variations of the GAN to around 500 variants. This research is to utilize the Cycle GAN architecture in order to enrich the dataset. By doing GAN as a synthetic image generator. This is very important in procuring image datasets, for training and testing models of Deep Learning algorithms such as Convolutional Neural Networks. In addition, the use of synthetic images produces a deep learning model to avoid overfitting. One of the causes of the overfitting problem is the lack of datasets. There are many ways to add image datasets, by cropping, continuously rotating 90 degrees, 180 degrees. The reason for using Cycle Generative Adversarial Networks is because this method is not as complicated as other GANs, but also not as simple. Cycle GAN synthetic images are processed with Super Resolution GAN, which aims to clarify image quality. So that it produces a different image and good image quality.   
Internet of Things-based Agricultural Land Monitoring Andrew, Andrew; Haryono, Haryono
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11416

Abstract

Agriculture is an industrial sector that produces raw materials such as rice, corn, and agricultural products. In the current era, there should be no problem if there is a food shortage because society, industry, and education do not make a real contribution to supporting the agricultural industry. The state also needs good agricultural land, so that the state can fulfill the needs of its people. Without good agriculture, a country will not be able to meet the needs of its people. Modern society today is not or is rarely concerned with agriculture. Agriculture is carried out only by providing fertilizer, water, and land, paying attention to the quality of the agricultural land. One of the problems of declining agricultural production is crop failure. One of the reasons island for agriculture. Soil is the most important part of the world of agriculture. If the land is not cultivated then the land is difficult to become an ideal place for agriculture. The Internet of Things can be used as a solution to problems by tilling the soil and monitoring soil conditions. In conditions in the dry season, soil moisture needs to be done by water. In the rainy season, the land should not be flooded, let alone submerged and flooded. In order to maintain the balance of moisture and waterlogged soil, the Internet of Things is a solution for monitoring and managing agricultural land. Internet of Things is a device that can communicate with each other from one device to another, such as sensors and actuators. Good land cultivation makes agricultural land fertile. Agricultural land processing is maximized by adding a monitoring system for agricultural land using a micro-controller Arduino Uno, NodeMCU ESP8266, several sensors, and integrated devices. The purpose of this research is to make a prototype that is useful for monitoring agricultural land

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