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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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Utilizing Genetic Algorithms To Enhance Student Graduation Prediction With Neural Networks Pangesti, Witriana Endah; Ariyati, Indah; Priyono; Sugiono; Suryadithia, Rachmat
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13161

Abstract

The prediction of student graduation plays a crucial role in improving higher education efficiency and as-sisting students in graduating on time. Neural networks have been used for predicting student graduation; however, the performance of neural network models can still be enhanced to make predictions more accurate. Genetic algorithms are optimization methods used to improve the performance of neural network models by optimizing their parameters. The problem at hand is the suboptimal performance of neural networks in predict-ing student graduation. Thus, the objective is to leverage genetic algorithms to improve the accuracy of stu-dent graduation predictions, measure the improvements obtained, and compare the accuracy results between the genetic algorithm-optimized neural network model and the neural network model without optimization. The training process of the neural network model is conducted using training data obtained through experiments, and the accuracy results of the neural network model with and without genetic algorithm optimization are compared. The research findings indicate that by harnessing genetic algorithms to optimize the parameters of the neural network model, the accuracy of student graduation predictions increased by 2.78%. Furthermore, the Area Under the Curve (AUC) also improved by 0.037%. These results demonstrate that integrating genetic algorithms into the neural network model can significantly enhance prediction performance. Thus, this study successfully utilized genetic algorithms to improve student graduation predictions using a neural network model. Experimental results show that prediction accuracy and AUC values significantly increased after opti-mizing the neural network model's parameters with genetic algorithms. Therefore, the use of genetic algorithms can be considered an effective approach to improving student graduation predictions, thereby assisting educa-tional institutions in improving efficiency and helping students graduate on tim.
Microcell Planning Analysis Using Cell Splitting Method In 4G LTE Network Yuhanef , Afrizal; Zurnawita, Zurnawita; Berliana Syafira , Gerin; Septima, Uzma; Setiawan, Herry
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13168

Abstract

As the growth of technology and telecommunication network, demands of mobile technology is also raised. The quality of the network will decrease by the insufficient number of network and cell to support the growth of user, and the scope of e-Node B is not optimal. The method of cell splitting can be used to solve the problem, this method splitting macro cell network become smaller size of cell with scoping area of each without interruption. The planning of new site as microcell implemented in area of Flamboyan Baru using XL operator. As the count gained, 1 site microcell and 2 cell with the antenna of 18,5 meters and power of 38 dBm, cell splitting method could increase network quality and improve the average number of parameter RSRP, SINR, and throughput, also proving that the implementation of cell splitting in microcell could escalate the quality of LTE network, the improvement of network quality in SINR parameter with average number of 24,23 dB with category of very good, RSRP parameter with average number of -94,28 dBm with category good, and the average number of throughput reach 63.094,91 kbps with category very good.
Implementation of K-Means Clustering in Food Security by Regency in East Java Province in 2022 Tuslaela, Tuslaela; Rusdiansyah, Rusdiansyah; Supendar , Hendra; Suharyanti , Nining
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13169

Abstract

Food is the main need that society must fulfill. If food security is disrupted, it will have a negative impact on the nation's life. The agricultural sector has an important role in West Java Province. This province has a large area of agricultural land, so it has high potential to produce abundant agricultural production. However, knowing the adequate number of farmers is very important. Therefore, the implementation of K-Means Clustering can make a significant contribution to the East Java Provincial Agriculture Service in grouping farmers by district. To achieve optimal results, determining the best K value needs to be considered carefully. K-Means Cluster Analysis is a method of non-hierarchical Cluster Analysis that groups data into one or more groups. Data with the same characteristics is grouped into one cluster and data with different characteristics is grouped into another cluster. The data used in this research are land area and rice production in the Regency of East Java Province in 2022. Based on the results of research with the object of Food Security, it can be concluded that, the results of the analysis of the application of manual data mining calculations in Excel Software using the K-Means Clustering method, resulted in two types of clustering in the form of C0, namely the Highest Land Area and Production group with 4 districts: Jember Regency, Ngawi Regency, Bojonegoro Regency and Lamongan Regency, for C1 clustering, namely the Lowest Land Area and Production group with 25 districts in East Java Province
Implementation Of The Arnold Catmap On A Combination Of Symmetric And Asymmetric Cryptography Riza, F.; Martiano, Martiano; Siregar, Farid Akbar
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13175

Abstract

The escalating need for robust data security has propelled cyber security practitioners into a perpetual quest for innovative solutions. This endeavor involves the strategic amalgamation of cryptographic algorithms with meticulously customized alterations to specific algorithmic processes. In this pursuit of heightened data protection, the Arnold Cat Map emerges as a pivotal tool, a mathematical transformation that gracefully elucidates the intricate movement of points within a two-dimensional plane. This movement occurs in a systematic and repetitive manner, rendering it an indispensable asset in the domains of cryptography and image scrambling. The Arnold Cat Map operates by meticulously relocating each point within the two-dimensional plane to a fresh coordinate, all the while adhering to an intricately structured pattern. The result is a formidable "mixing" effect that enhances data security. When applied theoretically to widely employed encryption methods like Advanced Encryption Standard (AES) for symmetric encryption and the Rivest-Shamir-Adleman (RSA) algorithm for asymmetric encryption, the Arnold Cat Map exhibits the potential to significantly augment the randomness of the encrypted output. This augmentation of randomness, in turn, fortifies the security of digital assets and communications, making them more resilient against adversarial attacks. By introducing this innovative concept into the realm of cryptography, cyber security practitioners endeavor to fortify data security, offering a higher degree of confidence in the protection of sensitive information and digital assets against a backdrop of ever-evolving cyber threats.
Analysis and Implementation of CNN in Real- time Classification and Translation of Kanji Characters Annisa, Putri; Gultom, Zuli Agustina; Sary, Yoshida
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13176

Abstract

This research explores the training outcomes of the Convolutional Neural Network (CNN) algorithm applied to Kanji character recognition. It employs a CNN architecture with 10 layers for recognizing digital image of Kanji characters from N5 to N1 levels. The training of the CNN model reveals varying accuracies, influenced by factors such as architecture, training data size, and data quality. The lowest accuracy, occurring at the beginning of training, highlights challenges like poor random weight initialization and suboptimal architecture. Conversely, the highest accuracy demonstrates the optimal predictive ability of the model after multiple training iterations. The iterative training process refines the model's accuracy over time, with initial challenges paving the way for a better understanding of the data for future improvements. In the subsequent analysis and system development phase, two algorithms are compared to assess the effectiveness of the CNN algorithm in Kanji character recognition. Testing is conducted at various complexity levels to systematically evaluate accuracy. This testing involves complexity levels at each Kanji character level to assess system accuracy. The developed model shows potential for real-time classification of Kanji characters, with a focus on error rate and accuracy during training and testing. The built model can essentially be used to evaluate the ability to recognize Kanji characters effectively. The model's performance can be assessed based on the error rate and accuracy achieved during the training and testing processes.
Decision Making Model for Temple Revitalization in Bali Using Fuzzy-SMARTER Combination Method Erlina Putri, Ni Putu Mita; Sudipa, I Gede Iwan; Wiguna, I Komang Arya Ganda; Sarasvananda, Ida Bagus Gede; Sunarya, I Wayan
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13177

Abstract

Bali is dominated by Hindus and temples as places of worship. Revitalization is carried out periodically in order to preserve the temple. Many factors are taken into consideration in revitalization decisions so that they can be approved by a group or government. Through the decision-making model of temple revitalization in Bali, the entire complexity of decision-making factors can be integrated so as to produce an objective priority ranking of improvements as supporting data for a revitalization decision. The combination of fuzzy sets and the SMARTER (Simple Multi Attribute Rating Technique Exploiting Rank) method can help solve unstructured problems in determining temple revitalization decisions. The calculation between the Alternative sacred building and the complexity factor criteria with a final value of more than 0.5 is included as a revitalization priority suggestion.
Improving Data Embedding Capacity in LSB Steganography Utilizing LSB2 and Zlib Compression Kurniawan, Joshua Calvin; Nugraha, Adhitya; Prayogo , Ariel Immanuel; Novanto , The, Fandy
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13185

Abstract

In an increasingly advanced era, the exchange of information through digital tools has become a common practice. With easy access and advancing facilities, securely and covertly exchanging data has become a challenging task. Therefore, the technique of steganography can be used as a solution for data hiding and protection, enabling safer data exchanges. Steganography is a method to conceal data within a transmission object, which can be an image, video, audio, and more. In this research, steganography will be performed using images as the transmission object. This study is done to offer a modification of the Least Significant Bit (LSB) steganography technique by utilizing the LSB-2 method, along with the utilization of the Zlib compression algorithm. The modification and use of the Zlib compression algorithm aim to increase the message capacity that can be embedded in the transmission object while preserving the image quality. The results of the experiments will be presented in tabular form by comparing the original image with the steganography-processed image using metrics such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM) as measures of image quality. The experiments conducted results in an increase of capacity of approximately 36.54%, an increase in PSNR value of approximately 4.72%, accompanied by a decrease in MSE value in average of 49.19%, and SSIM values constantly at 0,99999 thus proving the proposed method successfully increased the embedded massage capacity while preserving even enhance the quality of the stego image produced by the embedding process
Enhancing Least Significant Bit Steganography Image Fidelity Using Brotli Compression Prayogo , Ariel Immanuel; Nugraha, Adhitya; The, Fandy Novanto; Joshua Calvin Kurniawan
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13186

Abstract

The rapid growth of technology has provided extensive convenience and openness in accessing information, yet this hasn't been balanced with an equivalent enhancement in information security. Steganography plays a crucial role in concealing and protecting data, with the Least Significant Bit (LSB) method being a commonly used algorithm that operates by substituting the least significant bits in the image pixels with the bits of the data to be hidden, aiming to preserve the image quality. This research aims to enhance the quality of the steganography result using LSB by employing the Brotli compression technique, coupled with increasing image's capacity. Brotli compression aims to reduce the size of the resulting stego image by combining embedded data that share identical values. Experiment results will be obtained by comparing the original image with the stego image using metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM). The experiments successfully demonstrated that the integration of LSB with Brotli compression outperformed the regular LSB method, showing a 6.64% increase in PSNR, followed by a decrease in MSE by approximately 63.79%, and an increase in SSIM by around 0.0039%. This was accompanied by a continuous increase in compression values depending on the input data size. These results indicate that the integration of LSB with Brotli compression was successfully implemented to enhance the fidelity of the stego image
Optimizing Digital Image Steganography through Hybridization of LSB and Zstandard Compression Novanto , Fandy; Nugraha, Adhitya; Joshua Calvin Kurniawan; Ariel Immanuel Prayogo
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13187

Abstract

In response to the growing need for secure digital communication globally, this research delves into an innovative strategy for enhancing data transmission security through steganography. This inventive approach involves the integration of the conventional Least Significant Bit (LSB) method with Zstandard (Zstd) compression to elevate the quality of stego images. The study carefully explores how the synergistic use of LSB and Zstd contributes to an improved equilibrium between embedding capacity and visual quality in stego images. This hybrid methodology capitalizes on the efficiency of Zstd in reducing file size, thereby facilitating more effective data concealment using LSB. The experimental outcomes showcase a notable 51.2% increase in embedding capacity, a 4.70% elevation in PSNR value, accompanied by a substantial 51.03% decrease in MSE value. Additionally, SSIM values hover around 0.007%, indicating a perceptually minimal difference between the original and steganographically modified images. These compelling results underscore the efficacy of the proposed method, highlighting its proficiency in preserving and enhancing the quality of stego images generated through the embedding process. This research signifies a significant stride in the realm of secure digital communication, demonstrating a promising fusion of traditional LSB with advanced Zstd compression for optimizing digital image steganographic.
Usability Evaluation of Tokopedia Application Version 3.242 Using System Usability Scale (SUS) Method Manurung, Romarta Yemima; Dwi Krisbiantoro; Dias Ayu Budi Utami
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13191

Abstract

Indonesia is currently experiencing rapid growth in the e-commerce sector. Its One of the existing e-commerce is the Tokopedia application, Users of this application reach more than 10 million users so that there are a lot of positive and negative reviews given by users. After manually analyzing there are still many negative reviews on the application, not only that, there are still other problems found such as expeditions that cannot be selected, then payment methods that cannot COD or pay on the spot, and sometimes force closes that come out by themselves suddenly. Therefore, researchers tried to conduct a study on Tokopedia application user satisfaction with the SUS method to measure the level of usability of the application. System Usability Scale (SUS) method to evaluate its usability aspect. The evaluation results showed that the app earned an SUS score of 55, with a percentile rank of about 30%, placing it at grade D. Although still above average, the slight difference with the standard SUS score (68) indicates a potential improvement. In interpretation based on nature (Adjective), the application is in the OK category, with the level of acceptance (Acceptable) is in the Marginal category. The Net Promoter Score (NPS) results show the Detractor category, indicating a tendency to lack user enthusiasm for the application. Further evaluation is needed to identify aspects of usability that affect user perception and cause unsatisfactory NPS categories. Future research can design improvement strategies based on these findings, with the aim of increasing SUS scores and changing the NPS category to be more positive

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