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"Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan"
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<![CDATA[Analisis Sistem Kerja Asyncronus Transfer Mode (ATM) Pada Aplikasi Canva ]]>
<![CDATA[Rahima Mahabbah]]>;
<![CDATA[Ryan Adam Hidayatullah]]>;
<![CDATA[Gelen Veranda Deanda]]>;
<![CDATA[Didik Aribowo]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.74
<![CDATA[Asynchronous Transfer Mode (ATM) is a network technology designed to support high-speed data transfer by utilizing small fixed-size data packets called cells. This study aims to analyze the implementation and performance of ATM in the context of the Canva application, a web-based graphic design platform. The study includes a theoretical review of ATM's working principles, advantages, and limitations, as well as the network performance analysis methods used.In this research, we examine how ATM can optimize data transmission in the Canva application, considering the importance of network speed and efficiency in ensuring an optimal user experience. The analysis results show that ATM can provide the high transfer speeds and stability required by the Canva application, especially in managing complex and large-sized graphic data.The conclusion of this study confirms that the implementation of ATM technology in web-based applications like Canva can significantly enhance network performance. This study also offers important insights for further development in integrating advanced network technologies for internet-based applications to support increasing data demands.]]>
<![CDATA[Implementasi Algoritma K-Means dan Knearest Neighbors (KNN) Untuk Identifikasi Penyakit Tuberkulosis Pada Paru-Paru ]]>
<![CDATA[Rachmadhany Iman]]>;
<![CDATA[Basuki Rahmat]]>;
<![CDATA[Achmad Junaidi]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.77
<![CDATA[In Indonesia, tuberculosis is ranked third in terms of prevalence among countries with the highest tuberculosis burden. Radiological examination, such as X-rays or X-rays, is a method generally used to detect tuberculosis. Chest X-ray examination is one method used to detect tuberculosis. To achieve these goals, the research will combine two powerful data processing techniques. First, the K-Means algorithm will be used to group x-ray image data based on similar characteristics, making it easier to identify typical patterns from images infected with tuberculosis. The research results show the highest accuracy of 93% using data division with a ratio of 80 : 20 with parameter K = 1. These results show that the combined model of the two algorithms can be applied to identify tuberculosis in the lungs.]]>
<![CDATA[Klasifikasi Citra Digital Bumbu dan Rempah Dengan Algoritma Convolutional Neural Network (CNN) ]]>
<![CDATA[Rexion Alondeo Boimau]]>;
<![CDATA[Yampi R. Kaesmetan]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.81
<![CDATA[Attention to spices and flavorings among the younger generation is still low. The strategy that can be used to overcome this problem is a programmed and computerized arrangement of spices and flavorings using Convolutional Neural Network (CNN) calculations. In this exploration there are 300 images of spices and flavors which will be characterized into 3 classifications. Namely ginseng, ginger and galangal. Information in each classification is divided into two, namely preparation information and testing information with a proportion of 80%: 20%. The CNN model used in computerized grouping of spice and flavor images is a model with 2 convolutional layers, where the first convolutional layer has 10 channels and the second convolutional layer has 20 channels. Each channel has a 3x3 portion frame. The channel size in the pooling layer is 3x3 and the number of neurons in the secret layer is 10. The actuation capability in the convolutional layer and secret layer is tanh, and the actuation capability in the result layer is softmax. In this model, the accuracy of preparation information is 0.9875 and the loss value is 0.0769. The precision of the test data is 0.85 and the loss value is 0.4773. Meanwhile, testing new information with 3 images for each classification resulted in an accuracy of 88.89%.]]>
<![CDATA[Pemanfaatan Parafrase Berbasis Artificial Intelligence Sebagai Salah Satu Teknologi Digital Untuk Meningkatkan Efisiensi Penyelesaian Tugas Mahasiswa di Surabaya ]]>
<![CDATA[Reza Putri Angga]]>;
<![CDATA[Kanessa Jasmine]]>;
<![CDATA[Sharleen Agustine]]>;
<![CDATA[Muhammad Aryasatya]]>;
<![CDATA[Natalia Desy Anggraini]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.88
<![CDATA[Utilization of Artificial Intelligence-Based Paraphrasing Improves Efficiency of Student Assignment Completion in Surabaya. In this era of over-evolving technology, artificial intelligence technology (AI) has made significant contributions in various fields, including education. One potential implemantation of artificial intelligence technology is an automated AI-based online paraphrasing tool in education 4.0 era. This research aims to examine the effectiveness of using AI-based online paraphrasing in improving the efficiency of student assigntment completion in Surabaya. The research metodolgy involved a survey with student from various universities in Surabaya with a descriptive approach technique. The results show that the use of AI-based online paraphrasing tools can significantlu reduce the time needed to complete assignments without reducing the quality of the content. This tools helps students to understand the material, develop writing skills, and avoid plagiarism. This research result is expected to encourage the use of digital technology in the learning process, which is expected to improve academic productivity. Thus, AI-based online paraphrasing tools can be part of a more modern and effective learning strategy.]]>
<![CDATA[Deteksi Tepi Sederhana Pada Citra Menggunakan Operator Sobel ]]>
<![CDATA[Supiyandi Supiyandi]]>;
<![CDATA[Trisatin Panggabean]]>;
<![CDATA[Nuzul Ramadhan]]>;
<![CDATA[Sri Ratna Dewi]]>;
<![CDATA[Salsabila Yusra]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.90
<![CDATA[implemented and evaluated the edge detection method using the Sobel Operator, which calculates the gradient of image intensity through two convoluted kernels for horizontal (Gx) and vertical directions. (Gy). The magnitudo gradient is obtained from the combination of both such directional gradients to represent the edge force on each pixel. The main steps include image pre-processing, the application of the Sobel kernel, the calculation of magnitudo gradients, and the filtering of results to extract significant edges. The results show that the Sobel Operator is effective in highlighting intensity differences that indicate the boundary of the object, although it is sensitive to noise and less accurate for fine edges. Despite its limitations, this method is simple to implement and useful as an initial step in image processing applications such as segmentation, pattern identification, and object shape analysis.]]>
<![CDATA[Simulasi Monte Carlo Dalam Prediksi Penjualan Pempers Makuku ]]>
<![CDATA[Nurul Mudhofar]]>;
<![CDATA[Soffiana Agustin]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.103
<![CDATA[Predicting sales is an important aspect in sales development. Sales prediction simulation is an estimated calculation of the level of product sales in a certain period. Sales of pempers tend to fluctuate due to the choice of many brands available, resulting in sales having a little difficulty in estimating sales of MAKUKU diaper products at Greens Mart stores. This research aims to predict sales Pempers products. This research uses several stages of identifying problems, determining research objectives, collecting data, data collected or obtained from interviews with salespeople, managing data using Monte Carlo stages, implementing/testing data and testing results to see the accuracy of the method used. The analysis results show that Comfit M and Comfit L have almost the same level of accuracy, namely Comfit M is around 90.63% and sales of Comfit L are 90.48%. These values provide an indication of the level of accuracy of the sales predictions made.]]>
<![CDATA[Perancangan Sistem Pelaporan Incident Hack Di Kominfo Lombok Tengah Menggunakan Agile Pendekatan Scrum ]]>
<![CDATA[Gunawan Efendi]]>;
<![CDATA[Lalu Mutawalli]]>;
<![CDATA[Jihadul Akbar]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.104
<![CDATA[The Scrum method is a methodology included in agile software development. Scrum is considered to be able to produce good quality software according to user wishes, can be used in large and small projects, and is easy to adopt changes. The scrum activity stages include product backlog, sprint backlog, daily scrum, sprint review, and sprint retrospective. Roles in Scrum include product owner, scrum master, and development team. Scrum has structured and iterative stages, so that if the product in the first sprint is not sufficient to meet needs, then in the next sprint a system can be developed that is in accordance with user evaluation. The results obtained from Designing a Hack Incident Reporting System at Kominfo Central Lombok Using the Agile Scrum Approach were proven to be able to overcome changes in requirements during the system development phase, producing products that met the wishes of users because they received repeated reviews.]]>
<![CDATA[Pengujian Usabilitas Pada Penggunaan Platform Scratch ]]>
<![CDATA[Zakia Access Asmaul Khusna]]>;
<![CDATA[Yovi Litanianda]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.107
<![CDATA[This research tests the usability of the platform on new students of Informatics Engineering. Usability of is measured through three main variables: effectiveness, efficiency, and user satisfaction. Data was collected through pre-test and post-test involving 20 respondents using questionnaires and practical tasks. 20 respondents using questionnaires and practical tasks. The results of the study showed that the effectiveness and efficiency of the Scratch platform increased significantly from the pre-test to the post-test, reaching a level of effectiveness and efficiency, showing that the time required to complete programming tasks is reduced once users are familiar with the platform. User satisfaction also increased, with the majority of respondents feeling more comfortable and interested in using Scratch after testing. This research concludes that the Scratch platform is effective and efficient as a programming learning tool for new Informatics Engineering students.]]>
<![CDATA[Evaluasi User Experience EduSmart Menggunakan System Usability Scale (SUS) ]]>
<![CDATA[Amanda Zulfi Kurnia Tsani]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.113
<![CDATA[Utilizing the System Usability Scale (SUS) method, the goal of this study is to understand the challenges faced by eduSMart users. Edusmart is an online learning platform. A survey consisting of several questions is conducted using the SUS method to improve the quality of work, efficiency, and ease of use. This study indicates that the user's SUS score indicates the use of tinggi. In the end, the platform needs to be improved to increase its capacity. The study's findings indicate how users should use the Edusmart platform and provide helpful advice for improving users' efficiency and enjoyment. The research findings can be used as a reference for future studies that assess the value of digital learning systems.]]>
<![CDATA[Penerapan K-Means Clustering Untuk Menentukan Jumlah Pengangguran Berdasarkan Umur : Studi Kasus Di Badan Statistik Provinsi DKI Jakarta 2020-2022 ]]>
<![CDATA[Andi Diah Kuswanto]]>;
<![CDATA[Azumardi Nabil Fadhila]]>;
<![CDATA[Paulus Tri Setiawan]]>;
<![CDATA[Muhammad Kevin Setiawan]]>;
<![CDATA[Dody Renal Syahputra]]>
<![CDATA[ Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/repeater.v2i3.116
<![CDATA[Unemployment is a persistent problem in the labor market, thus hampering economic development and national prosperity. Indonesia, including its capital Jakarta, continues to face significant levels of unemployment compared to neighboring countries. This research focuses on analyzing the structure of unemployment in Jakarta using K-Means Clustering to categorize unemployment data based on age groups (2020-2022) sourced from the Central Statistics Agency. Analysis carried out via RapidMiner revealed three clusters:-Cluster 0: Age 30-60 years and above, Cluster 1: Age 20-24 years, Cluster 2: Age 15-19 and 25-29 years. The findings show that the 20-24 year age group has the highest unemployment rate (399,167 people), while the 30-60 year and above age group shows the lowest unemployment rate (75,560 people). This clustering approach provides insight into the distribution of unemployment by different age demographics in Jakarta, highlighting areas where targeted interventions may be needed to effectively address this socio-economic challenge]]>
