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All Journal E-JOURNAL MANAJEMEN FE UNTAD PRISMA FISIKA Insect (Informatics and Security) : Jurnal Teknik Informatika Chemistry Indonesian Journal of Chemical Research Dalton : Jurnal Pendidikan Kimia dan Ilmu Kimia ELT-Lectura Jurnal Entomologi Indonesia EDUMATIC: Jurnal Pendidikan Informatika JOURNAL OF SPORT EDUCATION (JOPE) Ekspose: Jurnal Penelitian Hukum dan Pendidikan Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Sporta Saintika Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Kesehatan Tambusai Abdimas: Papua Journal Of Community Service Community Education Engagement Journal INSPIREE: Indonesian Sport Innovation Review Munaddhomah: Jurnal Manajemen Pendidikan Islam Journal Peqguruang: Conference Series TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Jurnal Berita Kesehatan Jurnal Pendidikan, Sains dan Teknologi Journal of Social Commerce Indonesian Research Journal on Education Innovative: Journal Of Social Science Research Science and Education Journal Integrated Sport Journal JOI Journal of Business Economics and Management JIO: Jurnal Inovasi Olahraga Journal Development Manecos Catha : Jurnal Penelitian Kreatif dan Inovatif
REZKI, REZKI
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Vo2 Max Klub Sepakbola Garuda Muda Kecamatan Kuok Rezki, Rezki; Zulkifli Darwis; Sesi Melati
Journal Of Sport Education (JOPE) Vol. 2 No. 2 (2020): July
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/p1jf3p49

Abstract

Penelitian ini bertujuan untuk mengetahui Tingkat Vo2 Max pemain Garuda Muda FC Kuok, apakah sudah tegolong sangat baik, baik, kurang ataupun kurang sekali. Penelitian ini bersifat deskriptif, populasi penelitian ini berjumlah 12 orang pemain Garuda Muda FC Kuok. Tata cara pengambilan sampel yakni dengan cara purposive sampling yaitu penentuan sampel dengan pertimbangan atau kriteria-kriteria tertentu. Instrument penelitian menggunakan Daya tahan (VO2max) diukur dengan Bleep test (Multistage Fitness Test). Berdasarkan hasil tes Vo2 max yang dilakukan, diperoleh skor maksimum = 43,6 dan skor minimum = 29,1 disamping itu diperoleh nilai mean (rata-rata) = 36,23, median = 36,05, standar deviasi = 5,01,. Dengan demikian data berdistribusi normal, karena selisih antara nilai mean (rata-rata) dengan nilai median tidak lebih dari satu standar deviasi. Berdasarkan hasil penelitian tentang Tingkat Kemampuan Vo2max Pemain Garuda muda FC Kuok dari 12 orang sampel dapat disimpulkan berada pada kategori cukup.
Machine Learning Approaches for Export Trend Classification: Evidence from Leading Commodities in Indonesia Muslimah, Virasanty; Rezki, Rezki; Jabar, Wildan Abdul
Jurnal Pendidikan Informatika (EDUMATIC) Vol 10 No 1 (2026): Edumatic: Jurnal Pendidikan Informatika (IN PRESS)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v10i1.32949

Abstract

Sorong City holds a strategic position in the export economy of Papua Barat Daya; however, its export performance remains volatile due to global price fluctuations, logistical constraints, and shifts in international demand. To address these challenges, this study applies machine learning-based classification to analyze and predict export trend dynamics of Sorong’s leading commodities. Specifically, the study compares the performance of Naïve Bayes and Random Forest classifiers within a quantitative experimental framework. The dataset comprises 874 export records (2023–2025), including HS Codes, export values, destination countries, exporters, and export types. The methodological workflow encompasses data preprocessing, trend labeling, normalization, label encoding, class balancing using SMOTE, and model evaluation via 80:20 train-test split and 10-fold cross-validation. Performance metrics include accuracy, precision, recall, F1-score, and ROC-AUC. Experimental results reveal that Random Forest outperforms Naïve Bayes, achieving 74% accuracy compared to 57%, and more effectively captures nonlinear feature relationships. Despite a reduction in ROC-AUC during cross-validation, Random Forest demonstrates greater robustness in export trend prediction. Overall, the findings highlight the potential of machine learning to enhance regional trade forecasting, inform evidence-based policy formulation, and strengthen data-driven export management in emerging regional economies.
Co-Authors Abdillah Al-Zikri, Muhammad Abiyyu Jikaladha Imka, Abiyyu Jikaladha Imka Aceng Haetami, Aceng Ahmad, Arimuliani Ahmadi, Maswan Ainun K.D.P, Nofryanti Akbar Tukan, Ramdya Aldi, Aldi Alfajri, Wili Alfarizi, M.Abel Anastasia, Elva Andres, Faula Anjas Alpata, Anjas Alpata Anugrah, Fezyana Delsa Aoliya, Nur Aprianti, Lisa Aras, Suhardi ARDIANSYAH ARDIANSYAH Arfandi, Muh. Alif Ariansyaha, Sirka Arjuna, Arjuna Awaluddin, A. Fajar Awaluddin, A. Fajar Awaluddin Barangkau, Barangkau Bayu Saputra Bintoro Siswo Nugroho Darni Darni Daud Yusuf Dedi Zega Dewi Astria Faroek Dodi, Dodi Dupri, Dupri Dwi Putra, Handra Elvy Rahmi Ermin Ermin Exmal, Pridho Arya Fadilla, Shaikah Fadliansyah, Fadliansyah Faridah, Alfiyyah fauzi, islami Fitri, Sabina Hadi Purnomo, Yuda Hadi Purnomo Hardiandy, Riko Hardiandy Hasan, Masrah Henjilito, Raffly Herman Hidayat, Herman Herman, Mimi Hilmy Muhammad Hasan, Hilmy Muhammad Hasan Hoirul, Hoirul Ichwan, Saiful Irwang, Irwang Islami, Vebi Jabar, Wildan Abdul Jatra, Rices Jesajas, David Reinhard Kabir, Md Shahariar Khulaifiyah, Khulaifiyah La Jupriadi Fakhri La Jupriadi Fakhri Lesman, Hendy Lucy Chairoel M Agung Al Fatah, M Agung Al Fatah Mahendra, Zulki Iza Mahesa, Diefki Mallisa, Bita Maulana, Iqmal Meldo, Devri Morales, Indra Gunawan Muhammad Azilla Yandre Muhammad Firdaus Muhammad Hasyim, Muhammad Muhammad Ikhsan MUHAMMAD YUSUF Musta, Rustam Najihah, Najihah Nopri Pratama, Iqbal Nugraha, Boyke Dian Nur Miswar Nurdjan, Nirwana Nurhasanah Nurhasanah Putri, Nur Annisa Rahma Wati Reksi Setiawan Renold , Renold Basar Nadeak Ridwan RIKA RAFFIUDIN Riskianti, Arvina Windah Rizky, Miftahur sembara Sesi Melati Sigit Nugroho Siti Latifa Wulandari Soekarta, Rendra Sofyan, Abib Sri Wulandari Sudi, Agustinus Sukuredo, Sukuredo Sunarko Sunarko Surahmanto Surya Adiputra, Surya Virasanty Muslimah Wadinka, Akbar Dani Wingky, Alkahdafi Yulianti, Mimi Zahratul habibah, Zahratul habibah Zhen Li Zulkifli Zulkifli Darwis