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All Journal UNP Journal of Statistics and Data Science Jurnal Penelitian Pendidikan Indonesia
Siti Nurhaliza
Universitas Negeri Padang
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences Other

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Improvement of performance through learning motivation on accuracy of forehand service in badminton among students Siti Nurhaliza; Ridho Bahtra; Tjung Hauw Sin; Ahmad Chaeroni
JPPI (Jurnal Penelitian Pendidikan Indonesia) Vol. 11 No. 4 (2025): JPPI (Jurnal Penelitian Pendidikan Indonesia)
Publisher : Indonesian Institute for Counseling, Education and Theraphy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/020256901

Abstract

This study aims to examine the direct and indirect effects of arm muscle strength, eye-hand coordination, and learning motivation on forehand service accuracy in badminton among junior high school students. A quantitative approach with path analysis was used. The sample consisted of 49 male students selected through random sampling. Data were collected using a push-up test for arm muscle strength, a tennis ball throw-and-catch test for eye-hand coordination, a 50-item Likert-scale questionnaire for learning motivation, and a modified forehand service accuracy test. The findings revealed that arm muscle strength (0.393), eye-hand coordination (0.337), and learning motivation (0.278) had significant direct effects on forehand service accuracy. Additionally, arm muscle strength and eye-hand coordination showed indirect effects through learning motivation, contributing 5.2% and 3.7%, respectively. Both physical and psychological factors significantly influence forehand service accuracy. Integrating physical training and motivational strategies is essential to enhance badminton performance.
Analisis Sentimen Penggunaan Aplikasi YouTube Menggunakan Metode Naïve Bayes Triana Putri; Siti Nurhaliza; Dodi Vionanda
UNP Journal of Statistics and Data Science Vol. 3 No. 1 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss1/343

Abstract

This study aims to analyze user sentiment towards the YouTube application using the Naive Bayes method. With the rapid growth of YouTube users worldwide, understanding user preferences and experiences is crucial. Sentiment analysis, a process of processing or extracting textual data to obtain information by categorizing positive or negative sentiment The Naive Bayes algorithm, a statistical approach commonly used in natural language processing and sentiment analysis, was applied due to its simplicity and efficiency. The research involved data collection through web scraping, followed by preprocessing steps such as cleaning, case folding, tokenization, stopword removal, and stemming. Feature selection was performed using TF-IDF (Term Frequency-Inverse Document Frequency) to assign weights to words based on their importance. The Naive Bayes classifier was then trained on the preprocessed data, and its performance was evaluated using accuracy, precision, recall, and F1-score metrics. The results showed an accuracy of 82%, precision of 83%, recall of 98%, and an F1-score of 89%, indicating the effectiveness of the Naive Bayes method in sentiment analysis for the YouTube application. This study provides valuable insights into user sentiment towards YouTube, enabling developers and content creators to enhance user experiences and marketing strategies.
Penerapan Model Log Linear Tiga Dimensi dalam Analisis Faktor Risiko Riwayat Sakit Maag Wita Resfi Ananta Wita; Eujenniatul Jannah; Siti Nurhaliza; Yenni Kurniawati; Syafriandi Syafriandi
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss4/433

Abstract

Gastritis, or commonly known as an ulcer, is an inflammatory condition caused by excess stomach acid that irritates the stomach lining. This disease is one of the most common in Indonesia and often disrupts daily activities, especially among students who face academic pressure, stress, and irregular diet. Based on Indonesia’s Health Profile Data, gastritis ranks sixth for inpatients with 330,580 cases, 60.86% of which occur in women, and seventh for outpatients with 201,083 cases, of which 77.74% occur in women. This study aims to examine the relationship between gastritis and demographic factors using a three-dimensional log-linear model. The method analyzes interactions between categorical variables to identify the best explanatory model. Results indicate that the most appropriate model involves the interaction between place of residence, gender, and history of stomach ulcers, showing that these factors collectively influence gastritis incidence. In conclusion, gastritis is not only related to physical health but also lifestyle and demographic factors. This study underlines the importance for students to manage stress, maintain healthy eating habits, and adopt preventive measures. The urgency of this research lies in raising awareness that untreated gastritis may reduce productivity and lead to more serious health problems.
Co-Authors Bahtra, Ridho Chaeroni, Ahmad Dodi Vionanda Eujenniatul Jannah Syafriandi Syafriandi Tjung Hauw Sin, Tjung Hauw Triana Putri Wita Resfi Ananta Wita