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All Journal Surya Informatika Indonesian Journal of Islamic Psychology International Conference on Social Science
Fajri Fauzan Azhari
Universitas Islam Indonesia
Computer Science & IT Social Sciences

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Perbandingan Kinerja Algoritma Machine Learning Dalam Prediksi Kesehatan Mental Dan Burnout Mahasiswa Jose Julian Hidayat; Fajri Fauzan Azhari; Tsania Manzilatul Husna; Aulia Nufaila Fahmayani; Novant Nanda Pradana; Cindy Setyowati
Jurnal Surya Informatika Vol. 16 No. 1 (2026): Jurnal Surya Informatika, Vol 16. No. 1, Mei 2026
Publisher : Universitas Muhammadiyah Pekajangan Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48144/suryainformatika.v16i1.2420

Abstract

Penelitian ini bertujuan untuk membandingkan kinerja beberapa algoritma machine learning dalam memprediksi tingkat kesehatan mental dan burnout mahasiswa, yang diklasifikasikan ke dalam tiga kategori, yaitu Low, Medium, dan High. Algoritma yang diuji meliputi Decision Tree, Logistic Regression, Naive Bayes, Support Vector Machine (SVM), dan Random Forest. Evaluasi dilakukan menggunakan metrik Accuracy, Precision, Recall, dan F1-Score pada dataset berjumlah 200.000 data. Hasil penelitian menunjukkan bahwa Logistic Regression memiliki performa terbaik secara keseluruhan dengan nilai akurasi sebesar 0,8720 dan F1-Score sebesar 0,8677, diikuti oleh Random Forest dengan akurasi 0,8708. Decision Tree dan SVM juga menunjukkan performa yang kompetitif dengan akurasi masing-masing sebesar 0,8646 dan 0,8684, sementara Naive Bayes memiliki performa terendah dengan akurasi 0,8503. Namun demikian, seluruh model mengalami kesulitan dalam memprediksi kelas High, yang ditunjukkan oleh nilai recall yang relatif rendah, terutama pada SVM yang gagal mendeteksi kelas tersebut. Hal ini mengindikasikan adanya ketidakseimbangan data yang signifikan, di mana kelas Low mendominasi dataset. Secara keseluruhan, Logistic Regression dan Random Forest dapat direkomendasikan sebagai model terbaik untuk prediksi kesehatan mental mahasiswa dalam studi ini. Namun, diperlukan strategi penanganan data tidak seimbang, seperti resampling atau cost-sensitive learning, untuk meningkatkan performa prediksi pada kelas minoritas, khususnya kategori High.
Forgiveness Predicting Prosocial Behavior In Sundanese Emerging Adults Fajri Fauzan Azhari; Meida Bella Hanjaswari; Amelia Callista Athoillah; Muhamad Farhan Naufal; Fuad Nashori
IJIP : Indonesian Journal of Islamic Psychology Vol. 8 No. 2 (2026)
Publisher : Da'wa Faculty of Islamic State University Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18326/ijip.v8i2.6918

Abstract

Prosocial behavior plays an important role in maintaining social harmony, particularly in collectivistic cultures such as the Sundanese population. One psychological factor associated with prosocial behavior is forgiveness. This study aims to examine the relationship between forgiveness and prosocial behavior among emerging adults of Sundanese ethnicity. A quantitative correlational design was employed involving 250 participants. Forgiveness was measured using the Forgiveness Scale developed by Nashori, while prosocial behavior was assessed using the Prosocial Behavior Scale by Sefianmi et al. Data were analyzed using Pearson’s product-moment correlation. The results indicated a positive but weak and statistically significant relationship between forgiveness and prosocial behavior (r = 0.196, p = 0.002). These findings suggest that higher levels of forgiveness are associated with higher levels of prosocial behavior. Additionally, forgiveness contributed only 3.86% to the variance in prosocial behavior, indicating that other factors may play a more substantial role in shaping prosocial behavior.
Islamic Spirituality and Subjective Well-Being among Generation Z Fajri Fauzan Azhari; Nailah Dhiya Ulhaq; Ghina Ilma Alia; Arsyaddhia Edra Rustam; Nita Trimulyaningsih
Proceedings of the 1st International Conference on Social Science (ICSS) Vol. 4 No. 1 (2025): Proceedings of the 6th International Conference on Social Science (ICSS)
Publisher : Green Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/icss.v4i1.279

Abstract

Generation Z faces significant psychological and emotional challenges that affect their subjective well-being. In the digital age, constant social media exposure and online comparison contribute to lower subjective well being. Research in Indonesia shows that spirituality plays an important role in improving subjective well-being. The purpose of this study is to examine the relationship between Islamic spirituality and subjective well-being. A quantitative correlational approach was conducted on Muslim Gen Z who are in the age range of emerging adults (n = 171, 64 males and 107 females, aged 18-25 years). This study used the Islamic spirituality scale, which refers to Swinton's theory, and the Subjective well-being scale, which was measured using two measuring instruments, namely the Satisfaction With Life Scale (SWLS) and the Positive Affect Negative Affect Scale (PANAS). Pearson correlation analysis showed that there is a highly significant positive correlation between Islamic spirituality and subjective well-being (r = 0.530, p < 0.001), with the meaning aspect in the Islamic spirituality variable providing the largest positive contribution to respondents' subjective well-being, which is 30.5%. Then there are differences in the level of subjective well-being when viewed from gender where men have a higher level of subjective well-being than women. Islamic spirituality can be applied in the form of therapy, counseling or guidance and counseling to improve subjective well-being in Gen Z, especially in facing difficult times and existential crises.
Co-Authors Amelia Callista Athoillah Arsyaddhia Edra Rustam Aulia Nufaila Fahmayani Cindy Setyowati Fuad Nashori Ghina Ilma Alia Jose Julian Hidayat Meida Bella Hanjaswari Muhamad Farhan Naufal Nailah Dhiya Ulhaq Nita Trimulyaningsih Novant Nanda Pradana Tsania Manzilatul Husna