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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Informatics and Enginering Dedication
Tanzil, Surya Pratama
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Computer Science & IT Control & Systems Engineering Other

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Pembuatan Website Menggunakan Visual Studio Code di SMA Xaverius 3 Palembang Wilyanto, Nicholas; Firnando, Januar; Franko, Billy; Tanzil, Surya Pratama; Tan, Handy Christianto; Hartati, Ery
FORDICATE Vol 3 No 1 (2023): November 2023
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v3i1.5057

Abstract

Pemrograman web adalah cara yang bagus untuk meningkatkan keterampilan kreatif siswa, terutama dalam hal desain website dan tampilan visual. Pengajaran ini bertujuan untuk menarik minat siswa/i SMA Xaverius 3 mengenai pembelajaran web serta memberikan manfaat bagi siswa/i agar dapat membantu meningkatkan kreativitas dalam mengelola halaman website. Pada praktiknya, pengajaran pemrograman web yang kami lakukan di SMA Xaverius 3 melibatkan 28 siswa/i dengan memanfaatkan aplikasi Visual Studio Code dan notepad sebagai media pembelajaran dengan topik HTML dan website. Metode pengajaran yang digunakan pada dalam kegiatan ini meliputi: (1) Tahapan Persiapan, (2) Tahapan Pelaksanaan dan (3) Tahapan Evaluasi. Hasil kegiatan menunjukkan bahwa siswa/i bisa memanfaatkan tags-tags html yang diajarkan untuk membuat tampilan website sederhana yang menarik. Selain itu, persentase siswa-siswi yang menikmati pembelajaran dari hasil respons kuesioner terhadap 28 siswa-siswi SMA Xaverius 3 Palembang tersebut mencapai 89.29%.
Analisis Sentimen Pengguna Instagram terhadap Timnas Indonesia U-23 pada Piala AFC menggunakan Algoritma K-Nearest Neighbor (K-NN) dengan SMOTE Tanzil, Surya Pratama
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol. 12 No. 1 (2024): TELEKONTRAN vol 12 no 1 April 2024
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/telekontran.v12i1.12869

Abstract

The Indonesia U-23 National Team is Indonesia's national football team with players under the age of 23. The Indonesian public's sentiment towards the Indonesia U-23 National Team increased rapidly during the 2024 AFC Cup period. This trend can be observed on one of the social media platforms, Instagram. Instagram is widely used by the public today. By using Instagram, we can obtain various types of information shared by the public. Within this information, there is data that can be processed into sentiment analysis. Based on this premise, a study was conducted using the K-Nearest Neighbor (k-NN) method to analyze public sentiment towards user comments on Instagram. Data was collected using scraping techniques. After that, the data was cleansed and preprocessed. Then, the data was labeled and extracted using TF-IDF before being classified with K-Nearest Neighbor (k-NN). The dataset obtained from the scraping technique was imbalanced, which can affect the model's accuracy. Therefore, in this study will compared the performance of k-NN with SMOTE and k-NN without SMOTE. The experiments showed that the imbalanced data achieved only 50% accuracy for k = 3. After oversampling using SMOTE, the accuracy increased to 55% for k = 3.
Software Development for Swimmer Performance Prediction System Based on Physical Characteristics using XGBoost Tanzil, Surya Pratama; Tinaliah, Tinaliah; Widi, Anugerah
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.12176

Abstract

Swimmer performance assessment in Indonesia still largely depends on coaches’ intuition, which may lead to subjective decisions and inconsistencies in training program planning, particularly in environments where frequent changes in coaches and sports administrators occur. The lack of structured and data-driven performance assessment tools further limits the continuity and objectivity of athlete development. This study aims to develop a web-based system capable of predicting swimmers’ performance potential by estimating race times based on physical characteristics using the XGBoost model. The proposed system is designed to support coaches in identifying athlete performance potential in a more objective and data-driven manner. Model evaluation results indicate that the XGBoost model achieved an R² value of 0.9190, demonstrating a very high level of prediction accuracy, with an average prediction time of 7.036 seconds. Software testing results confirm that the system operates as intended and is able to present prediction outputs in the form of estimated swimming time, performance percentage, and performance classification into four categories: Very High, High, Medium, and Low. Furthermore, usability evaluation using the USE method yielded excellent results, with an average score of 88.16%.
Co-Authors Firnando, Januar Franko, Billy Hartati, Ery Tan, Handy Christianto Tinaliah, Tinaliah Widi, Anugerah Wilyanto, Nicholas