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All Journal Jurnal Kesehatan Masyarakat (JKM) CENDEKIA UTAMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING NURSING UPDATE JURNAL ILMIAH ILMU KEPERAWATAN Jurnal Pengabdian Masyarakat Indonesia Sewagati: Jurnal Pengabdian Masyarakat Indonesia Jurnal Ilmu Pendidikan dan Sains Islam Interdisipliner Ranah Research : Journal of Multidisciplinary Research and Development Journal of Informatics and Computing Jurnal Ilmu Kedokteran dan Kesehatan Indonesia ABDIKOM Prosiding SeNTIK STI&K Jurnal Ilmu Kedokteran dan Kesehatan Indonesia
Robieth Sohiburoyyan
Politeknik Negeri Indramayu
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Klasifikasi Stroke Pada Citra Ct Otak Menggunakan Transfer Learning Efficientnet-B0 Rendi, Rendi; Himawan, Salamet Nur; Sohiburoyyan, Robieth; Wati, Vera
Prosiding Seminar SeNTIK Vol. 9 No. 1 (2025): Prosiding SeNTIK 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini mengusulkan model klasifikasi stroke berbasis citra CT otak menggunakan metode transfer learning dengan arsitektur EfficientNet-B0. Hasil menunjukkan akurasi 96,83%, menandakan performa klasifikasi yang sangat baik dan berpotensi membantu radiolog dalam diagnosis cepat dan akurat.
Sistem Prediksi Risiko Penyakit Jantung Menggunakan Metode Logistic Regression Berbasis Optimasi Data Robieth Sohiburoyyan; Devan Herdiansyah Nugroho; Salamet Nur Himawan; Vera Wati; Rosena Shintabella
Jurnal Ilmu Pendidikan dan Sains Islam Interdisipliner Vol. 5 No. 3 Agustus 2026: Jurnal Ilmu Pendidikan dan Sains Islam Interdisipliner
Publisher : Yayasan Azhar Amanaa Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59944/jipsi.v5i3.1702

Abstract

Penyakit jantung masih menjadi penyebab kematian yang signifikan diberbagai negara. Kondisi tersebut menunjukkan pentingnya suatu sistem pendukung keputusan yang dapat membantu tenaga medis dalam mendeteksi risiko penyakit jantung sejak dini secara cepat dan akurat. Penelitian ini berfokus pada pengembangan sistem berbasis machine learning untuk memprediksi risiko penyakit jantung melalui penerapan teknik penyeimbangan data, pemilihan fitur, serta optimalisasi model. Dengan pembagian dataset menjadi 80% data pelatihan serta 20% data pengujian dengan metode train test split. Pendekatan supervised learning digunakan dengan membandingkan enam algoritma klasifikasi, yaitu K-Nearest Neighbors (KNN), Decision Tree, Random Forest, Support Vector Machine (SVM), Naive Bayes, dan Logistic Regression. Ketidakseimbangan distribusi data ditangani menggunakan Synthetic Minority Over-sampling Technique (SMOTE), sedangkan penentuan fitur yang relevan dilakukan melalui Embedded Methods dengan Random Forest. Selanjutnya, GridSearchCV digunakan untuk menentukan konfigurasi hyperparameter terbaik. Kinerja setiap model dianalisis berdasarkan accuracy, precision, recall, F1-score, dan ROC-AUC. Berdasarkan hasil pengujian dengan dua hasil klasifikasi berupa berisiko dan tidak berisiko, Logistic Regression sebelum proses hyperparameter tuning menghasilkan performa paling baik, dengan accuracy sebesar 82,06%, precision 85,45%, recall 84,68%, F1-score 85,06%, serta ROC-AUC 87,26%. Performa dari Model terbaik tersebut selanjutnya diintegrasikan ke dalam aplikasi berbasis web dan mobile sebagai sarana pendukung untuk melakukan identifikasi dini terhadap risiko penyakit jantung.
HUBUNGAN ANTARA EFIKASI DIRI DAN RESILIENSI DENGAN PRESTASI AKADEMIK MAHASISWA SEMESTER 2 POLITEKNIK NEGERI INDRAMAYU Robieth Sohiburoyyan; Nafisah Itsna Hasni
Jurnal Ilmu Kedokteran dan Kesehatan Indonesia Vol. 3 No. 1 (2023): Maret : Jurnal Ilmu Kedokteran dan Kesehatan Indonesia
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jikki.v3i1.1149

Abstract

In the implementation of education, each university has learning outcomes that must be achieved by students graduating from the institution. To find out the predetermined learning outcomes have been achieved or not, measurable indicators are needed. One of the indicators used to measure the quality of university graduates is the achievement index achieved by students. In academic settings, many studies show that there is a positive relationship between self-efficacy and academic achievement. In addition, student academic achievement is also influenced by another aspect, namely resilience. Therefore, this research was conducted with the aim of knowing the relationship between the level of self-efficacy and resilience with academic achievement in 2nd semester students of Politeknik Negeri Indramayu. The method used in this research is a quantitative method. The sampling technique in this study was random sampling technique, with a total sample of 213 students. The results of data analysis showed that the significance score obtained was below 0.05. This means that there is a relationship between self-efficacy and resilience with academic achievement in 2nd semester students of Politeknik Negeri Indramayu. The higher the self-efficacy and resilience, the higher the academic achievement achieved. Conversely, the lower the level of self-efficacy and resilience, the lower the academic achievement.
Co-Authors Alfiyah Nur Baeti Andre Wibowo Arifin Nurhidayah Devan Herdiansyah Nugroho Dimas Arya Ramadhan Setiawan Farkhan Farkhan Hasim Asyari Himawan, Salamet Nur Iryanto Iryanto Iryanto Iryanto lutfi wahyuni, Melani Moh. Yani Mohammad Yani NAFISAH ITSNA HASNI Nur Budi Nugraha Puspitaningrum, Ike Putri, Sukma Diani Rendi Rendi, Rendi Rosena Shintabella Salamet Nur Himawan Salamet Nur Himawan Supriatun, Evi Suryatna, Sally Yustinawati Vera Wati Wati, Vera