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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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Survey Paper: Optimization and Monitoring of Kubernetes Cluster using Various Approaches Hadikusuma, Ridwan Satrio; Lukas; Karel Octavianus Bachri
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.v8i3.12424

Abstract

This research compares different methods for optimizing and monitoring Kubernetes clusters. Three referenced journals are analyzed: "Kubernetes cluster optimization using hybrid shared-state scheduling framework" by Oana-Mihaela Ungureanu, Călin Vlădeanu, Robert Kooij; "Monitoring Kubernetes Clusters Using Prometheus and Grafana" by Salma Rachman Dira, Muhammad Arif Fadhly Ridha; and "Cluster Frameworks for Efficient Scheduling and Resource Allocation in Data Center Networks: A Survey" by Kun Wang, Qihua Zhou, Song Guo, and Jiangtao Luo. These journals explore various approaches to optimizing and monitoring Kubernetes clusters. This review concludes that selecting appropriate technologies for optimizing and monitoring Kubernetes clusters can enhance performance and resource management efficiency in data centre networks. The research addresses the problem of improving Kubernetes cluster performance through optimization and efficient monitoring. The required methods include utilizing hybrid state-sharing scheduling frameworks, implementing Prometheus and Grafana for monitoring, and employing efficient cluster frameworks. The study's findings demonstrate that adopting a hybrid shared-state scheduling framework can improve Kubernetes cluster performance. Additionally, leveraging Prometheus and Grafana as monitoring tools offer valuable insights into cluster health and performance. The survey also reveals various cluster frameworks that enable efficient scheduling and resource allocation in data centre networks. In conclusion, this research emphasizes the significance of employing suitable technologies to optimize and monitor Kubernetes clusters, leading to enhanced performance and efficient resource management in data centre networks. By leveraging appropriate scheduling frameworks and monitoring tools, organizations can optimize their utilization of Kubernetes clusters and ensure efficient resource allocation
Analysis of Public Purchase Interest in Yamaha Motorcycles Using the K-Nearest Neighbor Method Triani, Diana Juni; Dar, Muhammad Halmi; Yanris, Gomal Juni
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.v8i3.12433

Abstract

This data mining will carry out a classification of people who are interested and not interested in buying Yamaha motorcycles. In the data mining process, a method is needed that can provide goals to the data mining process. That's because there are many data mining methods that can be used. In this study the method that will be used by the author is the K-Nearest Neighbor (kNN) method. This method will be used to classify people's buying interest in Yamaha motorbikes. This research was conducted because there are some people who say that Yamaha motorbikes are not good, use of wasteful fuel. Therefore this research was conducted to prove this statement. So a research was made about people's buying interest in Yamaha motorbikes. Classification results obtained from 100 community data. From the classification process that has been carried out, the results show that 41 community data (41% representation) are interested in buying Yamaha motorcycles and 59 community data (59% representation) are not interested in buying Yamaha motorbikes. The results obtained state that there are still many people who are interested in Yamaha motorbikes. But it can be used as a reference that people are interested in motorbikes that have a good appearance, use economical fuel and are affordable. These results were obtained from the community's answers in the questionnaire, they were interested in motorbikes that use little fuel, have good designs and are affordable.
A proposed User-Based Approach for eBooks Recommendation Using a Weighted Nearest Neighbor Technique Saleh, Abdullah Mohammed; Taqa , Alaa Yaseen
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.v8i3.12441

Abstract

Large book data stores were beneficial for our support systems but posed significant challenges for useful information retrieval. This issue was resolved by collaboratively filtering data depending on user needs. This study suggested a user-based methodology for recommending eBooks. The selected dataset was pre-processed, and Cross-validation was used to build a user-user similarity matrix. Three nearest neighbor algorithms (KNN Basic, KNN with Means and KNN with ZScore) were used, and weighted KNN was proposed for rating prediction. In this technique, the weight of each user was calculated based on its distance from the intended user. The evaluation process depends on the user-item matrix and user-user matrix for prediction. The proposed recommendation system was tested on the book-crossing dataset, and the results were evaluated using the root mean square error and the mean absolute value of error. The results show that the error rate of the proposed model is the lowest compared to the other methods used, specifically when using the Pearson-Baseline technique. Since the root mean square error is 1.647 and the mean absolute value of errors is 1.253. When using the cosine technique, the root mean square error is 1.742, and the mean absolute value of errors is 1.328.
Sentiment Analysis Of Tourist Reviews Using K-Nearest Neighbors Algorithm And Support Vector Machine Sari, Anita Wulan; Hermanto, Teguh Iman; Defriani, Meriska
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.v8i3.12447

Abstract

After Indonesia was awarded as a country with extraordinary natural charm, many foreign tourists came to Indonesia. According to the records of the Central Bureau of Statistics for 2020, approximately 5.47 million foreign tourists entered Indonesia. With the large number of foreign tourist visits, the need for tourist attractions is increasing, but finding information is now not difficult. One source of information for finding reviews of tourist attractions is TripAdvisor. On this website, there is a lot of information or reviews about various tourist attractions. However, the number of reviews makes tourists confused about identifying the quality of tourist attractions to be visited, so sentiment analysis needs to be done. Sentiment analysis itself is a technique to extract, identify, and understand sentiments or opinions contained in a text. In this research, two classification methods will be used in sentiment analysis techniques, namely K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM). Besides that, the object of this research will be to focus on the most popular tourist attractions in Indonesia according to Trip Advisor, namely Waterbom Bali, Mandala Suci Wenara Wana, Teras Sawah Tegalalang, Pura Tanah Lot, and Pura Luhur Uluwatu. The purpose of the research is to find out the results of accurate sentiment analysis for the five tourist attractions and compare the two algorithms used. and after testing, it was found that the Support Vector Machine algorithm is superior to the K-Nearest Neighbors algorithm.
Gold Price Prediction Using the ARIMA and LSTM Models Madhika, Yudha Randa; Kusrini, Kusrini; Hidayat, Tonny
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.v8i3.12461

Abstract

For some investors who are interested in investing for the long term, gold is one of the promising options because the price of gold has recently continued to increase. In the current condition, gold investors generally use instinct and guesswork in investing in gold because there is a benchmark gold price based on world market prices. Many empirical studies identify factors that affect gold prices to forecast them. Factual and econometric analysis recommend different informative factors. This study investigates the influence of gold prices and five supporting variables in the form of economic indicators, namely crude oil price, federal funds effective rate, consumer price index, effective exchange rate and S&P 500 stock market index between 2002 and 2022. Models were built using ARIMA and LSTM methods, evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percent Error (MAPE). With a dataset allocation of 80% for training data and 20% for testing data, the comparison of actual gold prices with the predicted values of each model shows that LSTM has the best performance compared to the ARIMA (0,1,1) model where the LSTM model has an RMSE value of 8.124 and a MAPE value of 0.023. The models also show that economic indicators affect the ounce price of gold.
Pareto Frontier Approach to Determining the Optimal Path on Multi-Objectives Pratiwi, Annisa; Nasution, M.K.M.; Herawati, E.
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.v8i3.12465

Abstract

Every issue we face in daily life can be resolved through mathematical modeling. The use of mathematical modeling to generate solutions frequently produces value that serves a single purpose. Sometimes a single-purpose function's solution does not offer the best solution value. In this study, the author models the multiobjective time-dependent vehicle routing problem using the Ant Colony Optimization (ACO) metaheuristic algorithm. The author then applies the pareto optimization principle to the determination of the optimal starting point for the route. An optimal Pareto frontier principle solution on a multi-objective model under control of the Ant Colony Optimization algorithm is the outcome of this study.
Hybrid Cryptosystem Analysis RSA Algorithm And Triple DES Algorithm Liana, Liana; Zarlis, Muhammad; Tulus, Tulus
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.v8i3.12467

Abstract

Data security is needed in terms of communication. To guarantee data security, a technique is needed to make data and information called Critography. This study aims to analyze the process of Super Encryption in symmetric and asymmetric criterias using the Triple DES Algorithm and the RSA Algorithm. This can improve data security so that data is more confidential. The method used in Triple DES which is also called the symmetric algorithm is the OFB (Output feeback) method, and the RSA Algorithm (Riverst - Shamir-Adleman) which is an asymmetric algorithm using a random number system so that when these two algorithms are combined in the Super Encryption process the more accurate the data security. Super DES Triple Encryption and RSA algorithm analysis shows that the data created by text will be encrypted into ciphertext using both methods and re-described, so that the security of the data is relatively safe. Super Encryption on the two methods Algorithm is done because the level of complexity is difficult to make Cryptanalysts to steal data and the Encryption process becomes slow but data security becomes safer and not easy to attack Cryptanalysts. The problem in this research is how to increase encryption security and speed up the encryption process by combining the RSA and Triple DES methods.
Perceived Usability Evaluation of TikTok Shop Platform Using the System Usability Scale Purwandani, Indah; Syamsiah, Nurfia Oktaviani; Siti Nurwahyuni
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.v8i3.12473

Abstract

The popularity of TikTok is getting higher because from the start TikTok is a platform that provides a new experience that combines the experience of social media as well as transacting online.TikTok allows businesses to market their products in as creative a form as possible, such as making videos and building a community with their market share. TikTok is an application that plays an important role in paid promotional media, which is of course directly related to digital marketing carried out by business people in the e-commerce sector. In this research, the author wants to know the usability of the TikTok Shop feature as an e-commerce feature that has recently become increasingly popular in society. The System Usability Scale (SUS) will be used to test whether the TikTok application, especially the TikTok Shop feature. The standard SUS version has 10 instruments. The accuracy value is then measured using acceptable rage, grade scale and adjective ratings System Usability Scale (SUS). Based on questionnaire data collected from 49 respondents, it was found that 10.6 percent of the respondents were male and 93.6 percent of the respondents were female. The accuracy value of 79.49 is included in the acceptability ranges acceptable category, meaning that the TikTok Shop platform can be accepted by users, getting a C grade scale means it is quite good and is included in the adjective ratings excellent category.
Proposed use of TOGAF-Based Enterprise Architecture in Drinking Water Companies Amanda, Djaja; Hindarto, Djarot; Indrajit, Eko; Dazki, Erick
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.v8i3.12477

Abstract

The purpose of this research is to propose an enterprise architecture framework for planning a drinking water company blueprint. In drinking water companies, it is very important to ensure that the systems and information technology used meet business needs effectively and efficiently. However, the information system that supports the company's operations still needs to be improved, to get better operational quality. In this case, companies need a framework that can assist companies in designing and developing business architectures that strengthen competitive advantage, optimize operational performance, and ensure compliance with applicable regulations and standards. Therefore, the author proposes the selection of an enterprise architecture framework based on The Open Group Architecture Framework or TOGAF. The Open Group Architecture Framework is a widely used framework for developing and implementing enterprise architectures. TOGAF consists of four main components, namely business architecture, application architecture, technology architecture, and data architecture. Enterprise Architecture helps companies develop application and technology architectures that can accelerate product and service innovation and improve operational efficiency. Data architecture, managing and utilizing data effectively in making the right business decisions. By adopting the TOGAF-based Enterprise Architecture framework, water companies optimize the use of information systems and technology, increase flexibility in anticipating changes in community needs and accelerate innovation in products and services.
Development of Augmented Reality Multiple Markers Application Used for Interactive Learning Media Pratama, Alvonda Rizqi; Sukirman
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.v8i3.12482

Abstract

Augmented Reality (AR) is a technology that can turn virtual objects in the form of two dimensions (2D) or three dimensions (3D) into an object that looks real, then able to display objects in real-time. Using AR technology, you can visualize learning material into 3D objects to make it easier to understand when using it as a learning medium. This research aims to develop an AR application with multiple marker features that can be used as an interactive learning medium. The method used is Research and Development (R&D), and the development model used is 4D. The evaluation used was the Software Usability Measurement Inventory (SUMI), involving 11th-grade which involved 30 students consisting of 20 male students and 10 female students, the parameters assessed in this evaluation were between others are Efficiency, Affect, Helpfulness, Control, and Learnability. Based on the analysis performed on these parameters, the results show that all five parameters obtain valid and reliable results for each parameter in the validity and reliability tests with a Cronbach's alpha score of 0.934 (Efficiency), 0.868 (Affect), 0.917 (Helpfulness), 0.878 (Control), and 0.919 (Learnability). Thus, this multiple marker-based interactive learning media, Augmented Reality (AR), can be used in learning activities.

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