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Deteksi Dini Gangguan Kejiwaan dan Peningkatan Kesehatan Mental Remaja melalui Fun Games: Early Detection of Mental Disorders and Enhancement of Adolescent Mental Health through Fun Games Wibowo, Sapto; Priambodo, Anung; Prihanto, Junaidi Budi; Indriarsa, Nanang; Dinata, Vega Candra; Ristanto, Kolektus Oky
ABSYARA: Jurnal Pengabdian Pada Masayarakat Vol 5 No 1 (2024): ABSYARA: Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/ab.v5i1.25135

Abstract

Early detection of mental disorders is crucial for preventing serious impacts on adolescent mental health. Fun games are used as an engaging and acceptable solution for adolescents to identify behavioral and emotional changes, raise mental health awareness, facilitate open dialogues, and reduce the stigma associated with mental disorders. This study aims to train PJOK teachers in Banyuwangi Regency to detect early signs of mental disorders and improve adolescent mental health through fun games. The program was conducted on October 6, 2023, at SMAN 1 Glagah Banyuwangi with 45 participants. The training included mental health identification using instruments adapted from the Mental Health Inventory (MHI) and group dynamics activities from Psychodynamic Play Therapy (PPT). Participant satisfaction surveys showed that 100% were very satisfied with the training, with an average rating above 4.6 on a scale of 1-5. Participants indicated that the training positively impacted their understanding of student mental health and the benefits for PJOK teaching. Post-training, 100% of participants rated the delivery method as excellent. The study concluded that the community service activity successfully enhanced PJOK teachers' understanding of adolescent mental health and underscored the importance of early detection and fun games as therapeutic tools. Future activities should involve teachers from all subjects to maximize mental health awareness and adapt to the dynamic conditions of students' mental health
Pengaruh Entrepreneurship Self-efficacy dan Entrepreneurship Leadership terhadap Work Readiness Siswa Konsentrasi Keahlian DKV SMKN 1 Lamongan: The Influence of Entrepreneurship Self-efficacy and Entrepreneurship Leadership on Work Readiness of Students of DKV Expertise Concentration at SMKN 1 Lamongan Fatihah, Nur'run; Sudarwanto, Tri; Prihanto, Junaidi Budi
Edu Cendikia: Jurnal Ilmiah Kependidikan Vol. 5 No. 01 (2025): Research Articles, April 2025
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/educendikia.v5i01.5653

Abstract

Self-efficacy plays an important role in determining their readiness to enter the competitive world of work. This study is expected to provide a clear picture of the relationship between the three variables and their impact on the work readiness of DKV students. This study uses a quantitative method with data collection through questionnaires distributed to students. The study results from the number of respondents were 100 (The number of respondents is 100). • Prob> F: 0.4597 (insignificant because p> 0.05). This shows that overall, the independent variables (self-efficacy and Et) of students of DKV expertise concentration of SMKN 1 Lamongan do not have a significant effect on the dependent variable (work readiness) Regress WorkReadiness Entrepreneurship Self Efficacy Entrepreneurship Leadership Every 1 unit increase in self-efficacy increases Work Readiness by 0.1051 points. However, this effect is not significant (p = 0.250 > 0.05) • Entrepreneurship Leadership (X2): o increases Entrepreneurship Readiness by 0.0665 points, but this effect is significant (p = 0.561 > 0.05). • Constant (_cons): o Coefficient: 4.2097 If all v. Overall, the regression model is not significant (Prob > F = 0.4597), which means that Entrepreneurship Self-efficacy and Entrepreneurship Leadership do not significantly affect Work Readiness. 2. The three independent variables have a minor influence on the dependent variable but are insignificant at the 98% confidence level (p > 0.05). 3. This model has a very low predictive ability (R-squared = 44%), so many other factors may significantly influence Work Readiness.
Hubungan Penggunaan Gadget terhadap Motivasi Belajar Siswa Kelas VII SMP Negeri 6 Surabaya Syah, Ardi Romadhon; Prihanto, Junaidi Budi
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.30024

Abstract

Perkembangan teknologi digital telah membawa perubahan positif dan negative yang signifikan dalam dunia pendidikan, salah satunya melalui penggunaan gadget di kalangan siswa. Motivasi belajar merupakan salah satu aspek penting yang menentukan keberhasilan proses pendidikan. Tujuan penelitian untuk mengetahui hubungan antara penggunaan gadget terhadap motivasi belajar siswa VII SMP Negeri 6 Surabaya. Metode yang digunakan pendekatan kuantitatif dengan jenis korelasional. Populasi seluruh siswa kelas VII dengan subjek 369 siswa. instrumen pengumpulan data berupa angket penggunaan gadget dan motivasi belajar. Teknik analisis data penelitian ini menggunakan analisis statistik deskriptif, uji normalitas dan korelasi spearman. Berdasarkan hasil analisis data, diperoleh nilai koefisien korelasi Spearman sebesar r = 0,507 dengan tingkat signifikansi p = 0,001. (p < 0.05) terdapat hubungan signifikan antara penggunaan gadget dengan motivasi belajar siswa kelas VII di SMP Negeri 6 Surabaya. Besar hubungan penggunaan gadget terhadap motivasi belajar siswa kelas VII di SMP Negeri 6 Surabaya cukup kuat (r=0.507).
Hubungan Kadar Hemoglobin, Eating Behaviour, dan Tingkat Kebugaran terhadap Hasil Asesmen Sumatif Pjok Siswa Unggulan Hidayati, Ika Emirulliah; Wahjuni, Endang Sri; Prihanto, Junaidi Budi
Jurnal Keolahragaan Vol 11, No 2 (2025): Jurnal Keolahragaan
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jkor.v11i2.20488

Abstract

Hasil belajar siswa merupakan salah satu tolak ukur fundamental dari keberhasilan proses belajar mengajar. Hasil belajar siswa di Kurikulum Merdeka diukur melalui asesmen setiap akhir capaian pembelajaran dan akhir tujuan pembelajaran. Selain proses belajar mengajar, terdapat beberapa faktor yang mempengaruhi hasil belajar siswa. Faktor-faktor tersebut diantaranya status zat besi siswa yang baik, konsumsi nutrisi dalam tubuh siswa yang seimbang, dan tubuh siswa yang bugar. Tujuan penelitian ini untuk mengetahui adanya seberapa besar kontribusi kadar hemoglobin, eating behaviour, dan tingkat kebugaran terhadap hasil asesmen sumatif PJOK siswa unggulan di Madrasah. Metode penelitian yang digunakan adalah kuantitatif dengan jenis korelasional. Sampel penelitian berjumlah 58 siswa dengan rentang usia 13-15 tahun. Teknik pengambilan sampel yang digunakan adalah teknik purposive sampling dengan 4 parameter. Analisis data yang digunakan adalah uji korelasi Spearman dikarenakan jenis data pada dua variabel berbeda. Hasil penelitian menunjukkan bahwa terdapat hubungan yang signifikan secara parsial antara kadar hemoglobin (p= 0.0036), eating behaviour (p=0.013), dan tingkat kebugaran (p=0.008) terhadap hasil asesmen sumatif PJOK siswa unggulan (p<0.05).
From Visual To Understanding: Analysis Of The Effect Of Canva Learning Media On Phbs Motivation Hasanah Aprilia, Niswatin; Prihanto, Junaidi Budi; Ridwan, Mochamad
Jurnal Pendidikan Jasmani (JPJ) Vol 6 No 1 (2025): Jurnal Pendidikan Jasmani (JPJ)
Publisher : Sekolah Tinggi Olahraga dan Kesehatan Bina Guna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55081/jpj.v6i1.4023

Abstract

Low learning motivation in understanding Clean and Healthy Living Behavior (PHBS) material is still problematic at the elementary school level. Lack of student awareness of healthy behaviors such as washing hands and choosing nutritious foods indicates the need for innovation in learning strategies. This study aims to analyze the effect of Canva-based video media on student learning motivation on the PHBS topic. The study used a quantitative method with a one-group pretest-posttest quasi-experimental design. The research subjects consisted of 19 fourth-grade students at SD Negeri 2 Pule. The research instrument was a motivation questionnaire given before and after treatment. The results of the hypothesis test showed a significance value of 0.000 <0.05, it can be concluded that there was a significant effect after being given treatment with the use of Canva videos on increasing learning motivation. Therefore, Canva media can be used as an alternative technology-based learning that is effective in increasing motivation, especially in PHBS material.
LOGISTIC AND PROBIT REGRESSION MODELING TO PREDICT THE OPPORTUNITIES OF DIABETES IN PROSPECTIVE ATHLETES Ariyanto, Danang; Sofro, A'yunin; Hanifah, A’idah Nur; Prihanto, Junaidi Budi; Maulana, Dimas Avian; Romadhonia, Riska Wahyu
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1391-1402

Abstract

Diabetes is among the most prevalent chronic diseases globally, posing significant health risks to individuals. The identification of individuals at risk of developing these conditions is of paramount importance, particularly in high-stress and physically demanding activities such as athletic training. To find out the chances of a prospective athlete suffering from diabetes or not, models for binary data can be used, including logistic regression and probit models. The data used is primary data from prospective athletes in East Java, including prospective athletes from the State University of Surabaya and East Java Koni Athletes. This study aimed to develop an early prediction model for diabetes in prospective athletic candidates using a bivariate logistic and probit regression approach while considering the influence of socio-demographic and anthropometric factors. To selecting the best model between logistic regression and probit regression using Akaike’s Information Criterion (AIC) value, the smaller the AIC value gets means that the model is closer to the actual value or being the best model. Logistic regression has a smaller AIC value (129,85) than probit regression, this means that the logistic model is the best model. In this paper, an attempt is made to explore the use of logistic and probit regression to determine the factors which significantly influence the diabetes disease and we got that the logistic model as the best model because it has a smaller AIC value than the probit model. Based on the result of analysis and discussion, it can be concluded that there are two factors called mother’s job and finance which are influenced to the response variable, diabetes disease at significance level of 5%.
Enhanced diabetes and hypertension prediction using bat-optimized k-means and comparative machine learning models Sofro, A'yunin; Ariyanto, Danang; Prihanto, Junaidi Budi; Maulana, Dimas Avian; Romadhonia, Riska Wahyu; Maharani, Asri; Oktaviarina, Affi; Kurniawan, Ibnu Febry; Khikmah, Khusnia Nurul; Al Akbar, Muhammad Mahdy
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 in classification statistics. The proposed approach is the use of machine learning combined with optimization effects. Considering the urgency of research related to exploring the best methods to apply to sports data. This study proposes a novel framework by combining the clustering results of random forest from the k-means method with the bat algorithm optimization to enhance performance prediction in the case of athlete prediction. The proposed method aims to explore data by comparing the quality of classification results in random forest machine learning, extremely randomized trees, and support vector classification methods. We conducted a case study on primary data with 200 respondents from Surabaya State University and the East Java National Sports Committee. The accuracy found in this study indicates that the best approach based on the performance evaluation metric of the proposed approach is the random forest clustering results from the k-means method with bat algorithm optimization, which provides the best accuracy value compared to other machine learning approaches at 81.25%. This research offers a novel machine-learning–optimization framework that significantly improves athlete performance prediction by integrating k-means clustering, random forest, and bat algorithm optimization. The approach provides higher accuracy than conventional classifiers, enabling more data-driven decision-making for talent identification and sports analytics in Indonesia.