cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Irpan Adiputra pardosi
Contact Email
irpan@mikroskil.ac.id
Phone
+6282251583783
Journal Mail Official
sinkron@polgan.ac.id
Editorial Address
Jl. Veteran No. 194 Pasar VI Manunggal,
Location
Kota medan,
Sumatera utara
INDONESIA
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
 72   73   74   75   76 
Implementation And Design of Security System On Motorcycle Vehicles Using Raspberry Pi3-Based GPS Tracker And Facedetection Sari, Indah Purnama; Al-Khowarizmi, Al-Khowarizmi; MD, Pipit Putri Hariani; Perdana, Adidtya; Manurung, Asrar Aspia
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12935

Abstract

One of the nations where land transportation is frequently employed is Indonesia, particularly on motorbikes or two-wheeled vehicles. Since there is not much economic growth to maintain the high level of sales, there are many people without jobs, which leads to criminality, particularly motorcycle theft. The rate of motorbike theft in society is currently rising. The researchers developed a security system using a GPS Tracker whose control was handled by a two-channel relay in response to the rise in motorbike theft. The webcam camera produces the greatest images when it is hidden by a tree. 100% of the time, Relay Components work to control the horn and electricity. Due to the short read-time of the location the first time, GPS has a high accuracy. The Raspberry Pi3 can send, receive, and process commands to the motorcycle security system. The motion sensors, vibration sensors, raspberry pi microcontrollers, relays, and servo motors make up the system architecture in general. This method operates when the motor produces a lot of vibration. The sensor will relay the vibration to the Raspberry Pi microcontroller's output and the microcontroller will then deliver a warning notification message. In the event of a theft, the motorcycle will be immediately within the owner's control. In addition, with security using facedetection, the public can detect the perpetrators of theft and it takes quite a long time to work on it. The security system on motorbikes using facedetection takes a long time to produce, but it can't be done optimally. The purpose of this creation is to improve the security system on motorcycles to make it more efficient and effective in identifying the perpetrators of theft. This system consists of a Raspberry Pi3 as the control center, a picamera as a face detector, and a buzzer as an alarm.
Electronic Product Recommendation System Using the Cosine Similarity Algorithm and VGG-16 Irfan Rasyid; Yudianto, Muhammad Resa Arif; Maimunah; Tuessi Ari Purnomo
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12936

Abstract

The recommendation system is a mechanism for filtering a batch of data into numerous data sets based on what the user wants. Cosine similarity is one of the algorithms used in creating recommendation model. This algorithm employs a calculation approach between two things by measuring the cosine between the two objects to be compared. Image-based recommendation systems were recently introduced since word processing to generate recommendations had the issue of duplicating product descriptions for different types of items. Before processing with cosine similarity, image feature extraction requires the use of a deep learning algorithm, VGG16. The purpose of this research is to make it easier for customers to select the desired electronic goods by providing product recommendations based on product visual similarity. This model is able to recommend 10 products that are similar to the selected product. The presented product has a cosine value near one, and the discrepancy with the selected product's cosine value is modest. The mAP technique was used for model testing, and the smartwatch category received the greatest mAP value of 94.38%, while the headphone category had the lowest value of 70.84%. The average mAP attained is 81.50%. These findings show that mAP accuracy varies by category. This disparity is due to the unequal dataset in each category.
Development of the "SINEMA STARTUP" application for an ecosystem of startup idea creators using the SDLC and Lean Startup methods Budilaksono, Sularso; Febrianty, Febrianty; Nurzaman, Fahrul; Rosadi, Ahmad; Suwarno, Muhammad Anno; Harkandi Kencana, Woro; Suwartane, I Gede Agus
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12938

Abstract

Indonesia is a country with a dense population and among them are young people who have the potential to open new jobs. Many university graduates cannot be absorbed by the industry and they have to develop new businesses. The Central Statistics Agency (BPS) reported that the number of unemployed for the August 2020 period increased by 2.67 million people. The number of startups is growing and growing in Indonesia, but the main problems for startups are in the capital, human resources, customers, laws and regulations, and market segments. This research aims to develop the "Sinema Startup" application which aims to create and develop new startups in the right ecosystem. The research methodology uses a combination of SDLC (System Development Life Cycle) and Lean Startup methods with an Object Oriented approach. Respondents are potential startup creators, mentors, developers, testers, incubators, and investors. 1. Based on the results of User Acceptance Testing for the “Sinema Startup” Application, it was found that 93% of creators had no difficulty using the application and the remaining 7% had little difficulty. For mentors, 97% had no difficulty using the application and the remaining 3% had little difficulty. The limitations of this study are that not all stages of seeding, incubation, stocking, and publication can be carried out and the results monitored. The uniqueness of this research involves many users for testing, namely prospective startup creators, mentors, developers, testers, incubators, investors, students, and students. Testing this application requires a testing process that goes along with the growth of the Sinema Startup application.
Sales Conversion Optimization Analysis Using the Random Forest Method Nugroho, Kristiawan; Wismarini , Th. Dwiati; Murti, Hari
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12943

Abstract

Sales conversion is a challenging field of work in sales and business. Companies are competing to be winners by improving their services and hoping that their product sales can increase in various ways, including by using optimization theory. However, the lack of data analysis is a problem that is often encountered in optimizing sales conversions. Various machine learning-based methods have also been used to help analyze sales conversion optimization. This research uses the Random Forest method which is one of the more robust machine learning methods compared to other methods, namely Adaptive Booster (AdaBoost) and K-Nearest Neighbor (KNN) in analyzing sales conversion optimization. The results showed that the Random Forest method had the best performance in classifying data, by using the 10 cross validation technique the results were obtained with a Mean Squared Error (MSE) value of 0.928 and a Root Mean Square Error (RMSE) of 0.963, better than the Adaptive Booster method. and K-Nearest Neighbor which has lower performance. Sales conversion optimization processing using Random Forest is proven to have the best performance as evidenced by the small Mean Squared Error and Root Mean Square Error which means it has an accurate level of performance compared to other methods.
Bounding Box and Thresholding in Optical Character Recognition for Car License Plate Recognition Sania, Wulida Rizki; Sari, Christy Atika; Rachmawanto, Eko Hari; Doheir, Mohamed
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12944

Abstract

License plate recognition plays a central role in a variety of application contexts, including traffic management, automated parking, and law enforcement. Among the various approaches available, the Optical Character Recognition (OCR) technique has proven its effectiveness in recognizing characters in license plate images. This study describes an approach for detecting and recognizing vehicle license plates by utilizing the OCR method with Bounding Box, Thresholding, and template matching. In addition, this study uses MATLAB R2022a software as the main tool in developing and implementing the method. The goal is to recognize vehicle license plates from images, describe their characteristics, and generate relevant information. This approach involves a series of image processing steps starting with the pre-processing stage, followed by the process of binarization and license plate segmentation. After successfully isolating the license plate area, isolating the character using a bounding box is performed using image separation techniques. The OCR method is used to recognize license plate characters through comparison using the correlation method. Through a series of experiments on several image datasets, this approach succeeded in showing that out of 20 sampled license plate images, the results obtained were a reading accuracy of 93.55% of 100%, recognizing 13 out of 20 license plate images accurately when tested. Thus, the findings of this research are expected to contribute to the recognition of vehicle license plates that are accurate and efficient, by utilizing image processing techniques and OCR methods implemented using MATLAB R2022a software.
Breast Cancer Detection in Histopathology Images using ResNet101 Architecture Istighosah, Maie; Sunyoto, Andi; Hidayat, Tonny
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12948

Abstract

Cancer is a significant challenge in many fields, especially health and medicine. Breast cancer is among the most common and frequent cancers in women worldwide. Early detection of cancer is the main step for early treatment and increasing the chances of patient survival. As the convolutional neural network method has grown in popularity, breast cancer can be easily identified without the help of experts. Using BreaKHis histopathology data, this project will assess the efficacy of the CNN architecture ResNet101 for breast cancer image classification. The dataset is divided into two classes, namely 1146 malignant and 547 benign. The treatment of data preprocessing is considered. The implementation of data augmentation in the benign class to obtain data balance between the two classes and prevent overfitting. The BreaKHis dataset has noise and uneven color distribution. Approaches such as bilateral filtering, image enhancement, and color normalization were chosen to enhance image quality. Adding flatten, dense, and dropout layers to the ResNet101 architecture is applied to improve the model performance. Parameters were modified during the training stage to achieve optimal model performance. The Adam optimizer was used with a learning rate 0.0001 and a batch size of 32. Furthermore, the model was trained for 100 epochs. The accuracy, precision, recall, and f1-score results are 98.7%, 98.73%, 98.7%, and 98.7%, respectively. According to the results, the proposed ResNet101 model outperforms the standard technique as well as other architectures.
Satellite Images Classification using MobileNet V-2 Algorithm Wijaya, Bayu Angga; Perisman Jaya Gea; Gea, Areta Delano; Alvianus Sembiring; Christian Mitro Septiano Hutagalung
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12949

Abstract

Satellite imagery is an invaluable source of visual information for environmental monitoring and land mapping with high resolution and wide coverage. In this modern technological era, advances in Deep Learning technology have brought great benefits in utilizing satellite images for various purposes. One of the efficient Deep Learning models for satellite image classification is MobileNet V-2, which is specifically designed for devices with limited resources such as smartphones. This study aims to develop an accurate satellite image classification model using Convolutional Neural Network algorithm and MobileNet V-2 model. The data used is taken from the RSI-CB256 dataset developed through crowdsourcing data. This research resulted in the performance of three deep learning models, namely ResNet50, MobileNet V-2, and VGG-16. ResNet50 is the highest model performed best during the training phase, achieve an accuracy of 98.40%. MobileNet V-2 and VGG-16 followed with 95.64% and 96.62% accuracy, respectively. The evaluation results demonstrate the model's strong ability to accurately classify satellite imagery and strengthen the model's ability to generalize well. With high accuracy and the ability to run on smartphone devices, this model has the potential to provide valuable information for governments and scientists in preserving the earth and better responding to environmental changes.
Virtual Space For Virtual Reality Exhibitions With Oculus Quest Devices Rusdi Rahman, Muhammad; Suyanto, M; Ariatmanto, Dhani
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12952

Abstract

Based on information from the Ministry of Cooperatives and MSMEs, currently the number of MSMEs has reached 64.2 million euros and their share of GDP is 61.07% or 8,573.89 trillion rupiah (Coordinating Ministry for the Economy of the Republic of Indonesia, 2021). The contribution of MSMEs to the Indonesian economy includes the ability to absorb 97 percent of the current total employment and generate 60.4 percent of the total investment. (Ministry of Investment, 2021). VR (Virtual Reality) technology is a technology that allows users to feel in a virtual (virtual) world in visual form and users can interact with a virtual environment simulated by a computer in the form of Android. The focus of this research is a technical way of creating a virtual space or virtual space and 3D objects in displaying products from SMEs to be marketed to consumers with the virtual reality method using the oculus quest device, this research uses the Luther method, a six-stage process for creating multimedia that includes concept, design, material gathering, assembly, testing, and distribution. System testing was carried out using black box testing and usability testing using the SUS Score standardization, with a total of 47 respondents getting an average score of 54%. This average number exceeds 50% of the standard SUS Score Analysis, so the virtual reality exhibition space is categorized as suitable and OK for use by users. And it can also help MSMEs in carrying out virtual reality-based online marketing.
Automatic OEE Data Collection and Alert System for Food Industry Sumargo, Ruly; Makmur, Amelia
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12953

Abstract

The constant demand for food and beverages to sustain human life drives fierce competition among manufacturers, focusing on product excellence in terms of timeliness, quality, and pricing. The key to competitiveness depends in optimizing manufacturing processes by efficiently utilizing company resources. To ensure the overall optimization and reliable flow of manufacturing processes, a systematic evaluation process must be used, Overall Equipment Efficiency (OEE) stands out as a prominent performance measurement metric in manufacturing process efficiency. OEE serves as a valuable diagnostic tool, exposing areas for improvement and losses transparently. Accurate OEE measurement necessitates the implementation of an automated data collection system with minimum human dependencies, human intervention, and conducting on-the-fly calculations to informed the stakeholder/user. Data quality and accuracy in OEE measurement is very critical. Low quality and accuracy data could lead to false decision. OEE categorizes losses into six groups loss to pinpoint significant factors for potential improvement. Once OEE could be maintain at high level with high data accuracy and right improvement point, an optimum manufacturing process, and cost effective in manufacturing expenses will be achieve. Base on the result comparison for OEE result before and after the system implementation, positive improvement in OEE could reach 8.06%. This scenario be adopted by other company, and could become a model for 1st phase journey in company digital transformation.
Performance of Various Naïve Bayes Using GridSearch Approach In Phishing Email Dataset Rahman, Rizki; Fauzi Abdulloh, Ferian
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12958

Abstract

The background is the increasing cybersecurity threats in the form of phishing attacks that can be detrimental to individuals and organizations. The purpose of this research is to compare the performance of four Naive Bayes variants in classifying phishing emails with a method that involves a data pre-processing stage, phishing emails are collected, cleaned, and converted into appropriate numerical features. Next, the GridSearch approach was used to find the best parameters. This research objective is to understand how each Naive Bayes variant works on phishing email datasets. This phishing detection task is based on the following performance evaluation criteria such as accuracy, precision, recall, and F1-score. In this study, Bernoulli got the best accuracy of 97.34% but when the results obtained a hyperparameter, the results showed an increase with the most optimal results and the best performance is Bernoulli 97.38%. The research results are to provide an in-depth insight into the effectiveness of each variant of Naive Bayes in dealing with phishing email datasets and researchers in selecting the most suitable Naive Bayes variant for phishing detection tasks. In addition, the applied GridSearch method can guide how to find the best parameters for Naive Bayes models in other contexts. In summary, this study focuses on analyzing the performance of four variants of Naive Bayes Gaussian, Multinomial, Complement, and Bernoulli with the best algorithms Bernoulli 97.38%.

Page 74 of 120 | Total Record : 1196

 72   73   74   75   76 

Filter by Year

2016 2025


Reset
Filter By Issues
All Issue Vol. 9 No. 4 (2025): Articles Research October 2025 Vol. 9 No. 3 (2025): Article Research July 2025 Vol. 9 No. 2 (2025): Research Articles April 2025 Vol. 9 No. 1 (2025): Research Article, January 2025 Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024 Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024 Vol. 8 No. 2 (2024): Article Research Volume 8 Issue 2, April 2024 Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024 Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023 Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023 Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023 Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022 Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022 Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022 Vol. 6 No. 1 (2021): Article Research Volume 6 Issue 1: January 2021 Vol. 5 No. 2 (2021): Article Research Volume 5 Number 2, April 2021 Vol. 5 No. 2B (2021): Article Research October 2021 Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020 Vol. 5 No. 1 (2020): Article Research, October 2020 Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019 Vol 3 No 2 (2019): SinkrOn Volume 3 Number 2, April 2019 Vol. 3 No. 2 (2019): SinkrOn Volume 3 Number 2, April 2019 Vol. 3 No. 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018 Vol 3 No 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018 Vol. 2 No. 2 (2018): SinkrOn Volume 2 Nomor 2 April 2018 Vol. 2 No. 1 (2017): SinkrOn Volume 2 Nomor 1 Oktober 2017 Vol. 1 No. 2 (2017): SinkrOn Volume 1 Nomor 2 April 2017 Vol. 1 No. 1 (2016): SinkrOn Oktober Volume 1 Edisi 1 Tahun 2016 More Issue