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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 54 Documents
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Search results for , issue "Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024" : 54 Documents clear
Clustering Analysis of Socio-Economic Districts/Cities In East Java Province Using PCA And Hierarchical Clustering Methods Bhahari, Rifqi Hilal; Kusnawi, Kusnawi
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14078

Abstract

This study aims to analyze the socio-economic conditions of districts/cities in East Java using Principal Component Analysis (PCA) and Hierarchical Clustering. Socio-economic data for 2023 from 38 districts/cities includes the percentage of poor people, regional GDP, life expectancy, average years of schooling, per capita expenditure, and unemployment rate. PCA was used to reduce the dimensionality of the data, facilitating analysis and visualization. The reduced data was then analyzed using Hierarchical Clustering to group districts based on similar socio-economic characteristics. The clustering results were evaluated with the Silhouette Index and Davies-Bouldin Index. This study identified four main clusters with different socio-economic characteristics. The best clusters have high regional GDP, life expectancy, average years of schooling, and high per capita expenditure and low unemployment rates. The worst clusters show a high percentage of poor people and high unemployment rates. These results assist the government in designing more effective policies to improve welfare in East Java.
Analysis of Malnutrition Status in Toddlers Using the K-MEANS Algorithm Case Study in DKI Jakarta Province Sintawati, Ita Dewi; Widiarina, Widiarina; Mariskhana, Kartika
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14087

Abstract

Malnutrition in children is a serious health issue in various regions, including DKI Jakarta Province, which affects the physical and cognitive development of children. This research aims to classify malnutrition status in children using the K-Means algorithm, focusing on cases in DKI Jakarta. The objective is to identify patterns of malnutrition prevalence across different regions, serving as a basis for more effective interventions. The data used in this study includes the percentage of children with severely stunted, stunted, and normal nutritional status across six districts/cities in DKI Jakarta. The results of K-Means clustering show that Central Jakarta has the highest prevalence of severely stunted (10.50%) and stunted (13.01%) status, while West Jakarta has the lowest prevalence of severely stunted (4.62%) and stunted (10.22%) status. The solution offered by this research is the grouping of regions based on malnutrition prevalence, allowing for the identification of areas requiring priority intervention. The analysis results indicate that DKI Jakarta can be classified into several clusters based on malnutrition prevalence. The cluster with the highest malnutrition prevalence includes Central Jakarta, while the cluster with the lowest malnutrition prevalence includes West Jakarta and the Thousand Islands. The implementation of K-Means in this research provides an efficient approach to identifying groups of regions that need more attention in combating malnutrition in children. In conclusion, this research can serve as an important reference for policymakers in formulating more effective and efficient intervention strategies in DKI Jakarta, as well as inspire similar studies in other regions with different population characteristics
Implementation Docker and Kubernetes Scaling Using Horizontal Scaler Method for Wordpress Services Suryayusra; Destarina, Nova; Negara, Edi Surya; Supratman, Edi; Ulfa, Maria
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14091

Abstract

Container is a technology that has recently been widely used because of the additional features that are very easy and convenient to use, especially for web hosting service developers, with Container making it easier for system admins to manage applications including building, processing and running applications on Container. With Container the process of creating and using the system will be easier but along with too many user requests so that the service does not run optimally. Therefore, the Container must have good scalability and performance. Scalability is needed for systems that can adjust to the needs of user demand and performance is needed to maintain the quality of services provided. This research aims to implement scaling using Docker and Kubernetes in terms of scalability and performance. The parameters of comparison between Docker and Kubernetes are for scalability, scaling up and scaling down time and for performance. The method in this research uses the Action Research methodology, which is a research model that is simultaneously practiced and theorized. With the initial steps of problem identification, action planning, action implementation, observation and evaluation. Based on the results that have been obtained, Docker consumes more CPU & Memory Usage Resources, namely at 500 Users Kubernetes consumes Resources with an average of 94.47%-4.70% while in Kubernetes 89.11%-4.50 because in Kubernetes itself has a complex system, especially special component components such as APIs, Metrics Server, Kubernetes manager to run the Container. While in Docker only has Docker Manager and Docker Compose components.
Optimizing HEI On-Page SEO with Instagram: Owned vs. Paid Media (PMB UHW Perbanas Case) Pratama, Yudha Herlambang Cahya; Fitrani, Laqma Dica; Prasetya, Muhammad Septama; Nurhadi, Mochamad; Ajeng, Wahyu; Gita, Azam
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14114

Abstract

In today's digital age, nearly every institution, including those in education, utilizes social media. Instagram, a leading social media platform, offers a wealth of features for sharing engaging visual content. To maximize the effectiveness of new student recruitment on Instagram, UHW Perbanas needs a clear understanding and implementation of paid and owned media marketing strategies. The next step is to compare content performance before and after implementing SEO strategies, both paid and organic. Marketing strategy analysis using content on the @pmb.uhwperbanas Instagram account has demonstrably built a positive image and attracted audience attention. Relevant, informative, and engaging content fosters audience interest, creates engagement, and increases brand awareness. This research suggests that utilizing paid advertising can significantly amplify the reach and impact of existing content. The results of content with organic Instagram show insight results of 1,232 reaches, 1,626 impressions, 133 interactions and 83 profile activities. The results of content with paid Instagram show insight results of 109,173 reaches, 177 post interactions, 1,619 profile activities and 987 advertisements. This data collection platform is obtained from the features owned by Instagram Business.The conclusion of this research highlights the effectiveness of a balanced paid and organic media strategy on Instagram. By leveraging keyword analysis results from an SEO tool, UHW Perbanas can craft compelling captions that optimize search content and drive new student admissions.
Designing an Used Goods Donation System to Reduce Waste Accumulation Using the WASPAS Method Wayahdi, M. Rhifky; Ruziq, Fahmi
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14115

Abstract

This research aims to build a website application-based selection system for recipients of used goods donations using the WASPAS method. This system is designed to assist in the efficient and fair distribution of used goods to recipients in need. The WASPAS method is applied to calculate the preference value (Qi) for each alternative donation recipient based on predetermined criteria. The analysis results show that "Alternative-01" is the best alternative with the highest Qi value (1.866), while "Alternative-02" has the lowest Qi value (1.713). The significant difference in Qi values ​​between these two alternatives indicates a clear difference in preferences. The weight (w) given to each criterion plays an important role in forming the preference value (Qi). Therefore, careful consideration needs to be taken in determining the weight of each criterion to ensure that the final decision is in line with expectations. The WASPAS method has proven to be effective in the selection system for recipients of used goods donations. The advantage of this method lies in its ability to handle multi-criteria problems and uncertain data. By applying the WASPAS method, the decision-making process can be carried out more quickly, accurately and objectively. Although the WASPAS method provides a strong basis for decision making, it is also necessary to consider other relevant factors, both quantitative and qualitative. This will ensure that the final decision taken is the best decision and in accordance with the research objectives.
Enterprise Architecture of the Basic Banking Feature for a New Challenger of Digital Banking in Indonesia Sentosa, Steve; Indrajit, Richardus Eko; Dazki, Erick
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14116

Abstract

Digital transformation has significantly impacted Indonesia's banking industry, leading to the rise of digital banks that leverage technology for their operations, posing challenges to traditional banking models. This research investigates the implementation of enterprise architecture within the core features of digital banking in Indonesia, utilizing the TOGAF framework and Archimate modeling. The study's primary objective is to identify the core processes, challenges, and opportunities associated with managing the complex architecture of digital banks. Employing a qualitative methodology, data were gathered through in-depth interviews, direct observations, and a review of pertinent literature. The research identified three central processes in digital banking operations: deposits, time deposits, and loans. These processes were then modeled using the TOGAF framework and Archimate to align business strategies with operational activities more effectively. The SWOT analysis conducted highlights digital banks' strengths in operational efficiency, strategic partnerships, and innovation capabilities, while also recognizing weaknesses such as technological dependency and challenges in serving the less tech-savvy population. The study also identifies opportunities for product innovation, market expansion, and ecosystem integration. However, threats like regulatory changes, increased competition, and cybersecurity risks must be carefully managed. The research recommends adopting emerging technologies, enhancing third-party risk management, and improving customer data security and privacy to bolster digital banks' global competitiveness, operational sustainability, and service innovation.
Inorganic Waste Detection Application Using Smart Computing Technology with YOLOv8 Method Arvio, Yozika; Kusuma, Dine Tiara; BM Sangadji, Iriansyah
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14117

Abstract

Waste and renewable energy are critical issues in Indonesia, with the government aiming for renewable energy (RE) to contribute 23% to the national energy mix by 2025. This research focuses on developing a waste processing system through the TOSS (Tempat Olah Sampah Setempat) method and Peuyeumisasi technique to convert waste into biomass, such as briquettes and pellets for fuel. However, manual waste sorting remains time-consuming, prompting the need for a real-time detection system. You Only Look Once (YOLO) is an object detection approach that utilizes Convolutional Neural Networks (CNN) for object detection, making it one of the applications of intelligent computing in the field of computer vision. the latest version of YOLO is YOLO v8 offering several improvements over the previous version, can be employed in a real-time detection system to separate organic and inorganic waste. In this study, the dataset used consists of 2.000 images comprising five classes of inorganic waste: plastic bottles, plastic, glass, cans, and Styrofoam. The study demonstrates that YOLOv8 performs exceptionally well in detecting inorganic waste, with an average accuracy of 98% based on direct testing, and model evaluation showing an average accuracy of 99.33%, precision of 99.63%, recall of 96.53%, and an f1-score of 98.03%. These results indicate that the YOLOv8 method can significantly accelerate and simplify the waste sorting process, thereby supporting the conversion of waste into renewable energy. This research is expected to provide a practical solution and serve as a reference for future studies.
Comparison of K-Means and Self Organizing Map Algorithms for Ground Acceleration Clustering Simamora, Siska; Muhammad Iqbal; Andysah Putera Utama Siahaan; Khairul, Khairul; Zulham Sitorus
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14120

Abstract

This study evaluates earthquake-induced ground acceleration in Indonesia, which is located in the Pacific Ring of Fire zone, using Donovan's empirical method and comparing two clustering algorithms, Self Organizing Map (SOM) and K-Means. The main problem faced is the high risk of earthquakes in Indonesia and the need for effective methods to predict potential damage to buildings and infrastructure. The research objective is to evaluate earthquake-induced ground acceleration and identify acceleration distribution patterns using clustering techniques. The solution methods used include the application of the Donovan method to calculate ground acceleration based on BMKG data, as well as the use of SOM and K-Means algorithms to cluster the ground acceleration data. GIS and Python applications are used to visualize the clustering results. The results show that the Donovan method integrated with SOM and K-Means provides significant insights into the distribution of ground acceleration, thus assisting in risk evaluation, disaster mitigation planning, and the development of more effective earthquake-resistant infrastructure development strategies in Indonesia
The Oyster Mushroom Harvesting Determination System Based On Image Processing and Multi Layer Perceptron Husain, Nursuci Putri; Kadir, Muh. Ichwan; Muh. Dzulkifli P
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14126

Abstract

Oyster mushroom cultivation in Indonesia has seen rapid growth in recent years, particularly in South Sulawesi. The demand for oyster mushrooms is increasing as they are considered a nutritious food source. However, mushroom farmers are currently unable to fulfill market demand due to limited harvest yields. The primary factor contributing to this issue is the farmers' lack of skills in oyster mushroom cultivation. Therefore, an intelligent system is needed to identify and monitor the growth of oyster mushrooms, which can help to improve harvest yields. In this research, a system for determining oyster mushroom harvest timing will be designed using image processing techniques. This system will work by analyzing images of oyster mushrooms captured using a digital camera on the mushroom growing medium and then identifying visual characteristics that indicate mushroom maturity, such as color, texture, and size. The proposed method consists of several stages: image dataset collection, image preprocessing, image segmentation, morphological operations, feature extraction, and image classification based on Multi-Layer Perceptron (MLP). The dataset obtained includes 150 images of oyster mushrooms, divided into two classes: ready for harvest and not ready for harvest. The test results show that the proposed method can accurately identify oyster mushrooms as either ready for harvest or not. The classification model achieved an accuracy rate of 96.67%. By utilizing this technology, it is expected to enhance efficiency and consistency in the harvesting process and assist farmers in making informed decisions.
A Mixed-Integer Programming Approach on Clustering Problems with Segmentation Application Customer Elviana, Arin; Rosmaini, Elly; Nababan, Esther Sorta Mauli
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14141

Abstract

As a marketing strategy, segmentation involves categorizing customers into specific groups based on their loyalty to a brand. This process is crucial in shaping an effective business strategy, as identifying various customer types enables businesses to target their marketing efforts more precisely. This research focuses on solving the cluster optimization problem by applying a combinatorial optimization approach to develop a cluster optimization method. The combinatorial optimization utilized here operates on a binary system, using 0s and 1s to identify the optimal cluster for each object. Specifically, a value of 1 indicates that an object is assigned to an optimal cluster, while a value of 0 signifies that the object belongs to a non-optimal cluster. By designating clusters with a value of 1, the method ensures that the best optimization value is achieved. The 0-1 non-linear problem model ensures that objects with the shortest distances between them are grouped in the same cluster. Additionally, the model guarantees that each object belongs to only one cluster and that, across k tests, every cluster contains at least one object. This model can also be used to determine the ideal number of clusters for a given dataset, ensuring optimal segmentation results for business applications.

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