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All Journal International Journal of Advances in Intelligent Informatics SPRINTER: Jurnal Ilmu Olahraga
Junaidi Budi Prihanto
Universitas Negeri Surabaya
Computer Science & IT Physics Other

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Pengaruh Active Learning Method terhadap Peningkatan Kebugaran Jasmani Siswa Ekstrakurikuler Karate Gholiyah Puteri Virgie; Afifan Yulfadinata; Junaidi Budi Prihanto
SPRINTER: Jurnal Ilmu Olahraga Vol. 7 No. 1 (2026): SPRINTER: Jurnal Ilmu Olahraga
Publisher : MAN Insan Cendekia Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46838/spr.v7i1.955

Abstract

This study aims to explore the impact of Active Learning methods on improving the physical fitness of students participating in karate extracurricular activities at MTSN 3 Sidoarjo. This study applies a quantitative approach with a quasi-experimental design using the One Group PreTest- PostTest model. A total of 26 students who actively participated in karate extracurricular activities were used as research samples. The instrument used was the Multistage Fitness Test to measure VO2Max as an indicator of cardiorespiratory fitness. Data analysis using the Wilcoxon test was performed because the Pre-Test data was not normally distributed. The results of this study showed a significant increase in VO2Max values, where the pre-test median of 27.95 increased to 36.00 in the post-test. The Wilcoxon test produced a p-value < 0.05, indicating a significant difference between before and after the treatment. These findings indicate that the Active Learning method is able to increase student engagement in exercises so that they do not feel bored, thereby having a positive effect on improving physical fitness. Thus, the Active Learning method can be used as an effective alternative in teaching extracurricular sports activities, especially karate.
Korelasi Tingkat Status Gizi terhadap Tingkat Kebugaran Kardiorespirasi pada Peserta Didik SMP Negeri Surabaya Tsarwah Mahdiyyah; Junaidi Budi Prihanto
SPRINTER: Jurnal Ilmu Olahraga Vol. 7 No. 1 (2026): SPRINTER: Jurnal Ilmu Olahraga
Publisher : MAN Insan Cendekia Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46838/spr.v7i1.961

Abstract

Cardiorespiratory fitness is one of the main components of physical fitness that is important for the body, using Vo2Max as a measurement tool. Cardiorespiratory fitness is influenced by several things such as physical activity, age, and BMI. Nutritional status is used to anticipate excess or deficiency of nutritional status, this is certainly interrelated with cardiorespiratory fitness. This study aims to determine the relationship between nutritional status levels and cardiorespiratory fitness levels in class VIII at SMP Negeri 34 Surabaya. This study uses a quantitative approach with a correlational research design. The population and sample used are students of SMP Negeri 34 Surabaya with a population of 793, which then uses purposive sampling as a data collection technique with a sample size of 85 respondents. The instrument to assess fitness is the PACER test, while the measuring tool for nutritional status is BMI/U. Hypothesis testing uses the Spearman's Rank Order correlation test. The results of implementing the majority of students have a very low level of fitness in cardiorespiratory fitness (82.4%). While the level of nutritional status shows that the majority of nutrition (62.4%) is good. The results of the study, when analyzed using BMI and inverse, indicated a relationship of -0.340 (P-value 0.001), but when using fitness and nutritional status, there was no significance.
K-means optimization with bat algorithm for predicting diabetes and hypertension risk in athletes’ comparison with machine learning A&#039;yunin Sofro; Danang Ariyanto; Junaidi Budi Prihanto; Dimas Avian Maulana; Riska Wahyu Romadhonia; Asri Maharani; Affi Oktaviarina; Ibnu Febry Kurniawan; Khusnia Nurul Khikmah; Muhammad Mahdy Al Akbar
International Journal of Advances in Intelligent Informatics Vol 11, No 4 (2025): November 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i4.1816

Abstract

This research aims to develop an analytical approach to classification statistics. The proposed approach combines machine learning with optimization. Considering the urgency of research related to exploring the best methods to apply to sports data. This study proposes a novel framework that combines the k-means clustering results with the bat algorithm to optimize performance prediction for athletes in Indonesia. The proposed method aims to explore the data by comparing the classification performance of random forests, extremely randomized trees, and support vector machines. We conducted a case study using primary data from 200 respondents at Surabaya State University and the East Java National Sports Committee. The accuracy results in this study indicate that, based on the performance evaluation metric, the best approach is random forest clustering using k-means with bat algorithm optimization, achieving 81.25% accuracy, compared with other machine learning approaches. This research contributes to the field of classification statistics by introducing a novel hybrid framework that integrates machine learning, clustering, and optimization techniques to improve predictive accuracy, particularly in sports analytics. Beyond sports science, the proposed approach can be adapted to other domains that require robust performance prediction and decision support, such as health analytics, educational assessment, and human resource selection.
Co-Authors A&#039;yunin Sofro Affi Oktaviarina Afifan Yulfadinata Asri Maharani Danang Ariyanto Gholiyah Puteri Virgie Ibnu Febry Kurniawan Khusnia Nurul Khikmah Maulana, Dimas Avian Muhammad Mahdy Al Akbar Riska Wahyu Romadhonia Tsarwah Mahdiyyah