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All Journal Jurnal Masharif al-Syariah: Jurnal Ekonomi dan Perbankan Syariah Jurnal Aplikasi Teknologi Pangan Jurnal Pengabdian Magister Pendidikan IPA Bulletin of Information Technology (BIT) International Journal of Education and Teaching Zone Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Semiotika-Q: Kajian Ilmu al-Quran dan Tafsir International Journal of Health, Engineering and Technology Jurnal Bima: Pusat Publikasi Ilmu Pendidikan Bahasa dan Sastra Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Sevaka: Hasil Kegiatan Layanan Masyarakat
Putri Ramadani
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Journal : International Journal of Health, Engineering and Technology

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Application of SVM to Speed Up and Accurate Nursing Decisions for Mentally Disordered Patients Santosa Pohan; Riyan Agus Faisal; Fitriyani Nasution; Putri Ramadani; Ade Irma Yanti Hasibuan
International Journal of Health Engineering and Technology Vol. 3 No. 4 (2024): IJHESS NOVEMBER 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v4i1.277

Abstract

This study aims to evaluate the application of the Support Vector Machine (SVM) algorithm in increasing the speed and accuracy of nursing decision making in patients with mental health disorders. Fast and accurate decision making is very important in the nursing context, especially in treating patients with complex mental disorders. In this research, patient medical record data is used to train an SVM model, which is then used to predict the severity of the patient's mental disorder, such as Mild, Moderate, or Severe. The model is trained using features such as the patient's age, gender, diagnosis, psychological test scores, and physical condition. The evaluation results show that the SVM model has 100% accuracy, which means the model succeeded in classifying the severity of the patient's mental disorder very accurately. In addition, implementing this model also reduces the time required for decision making, allowing nurses to provide faster and more precise decisions. These results indicate that SVM can be a very useful tool in supporting nursing decision making, increasing the efficiency and quality of care, and reducing diagnostic errors. This research provides important insights into the potential use of artificial intelligence algorithms in clinical decision support systems in the mental health field.
Implementation of Password Validation using a Combination of Letters, Numbers and Symbols in the New Student Registration Application Sentosa Pohan; Putri Ramadani; Riszki Fadillah; Yusril Iza Mahendra Hasibuan; Baginda Restu Al Ghazali
International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i1.282

Abstract

This research aims to evaluate the implementation of password validation using a combination of letters, numbers and symbols in new student registration applications in increasing the level of application security. This research method involves implementing a password validation system with strict criteria, as well as testing password strength using brute force attacks. The test results show that passwords that meet the criteria take time 150 seconds to be broken using brute force, while passwords that only use letters only take time 10 seconds. Surveys of users show that 70% feel comfortable with this validation system, though 40% find it difficult to create a valid password. As much 85% users consider this system to improve application security. This research suggests that new student registration applications adopt a strict password validation system to increase the protection of users' personal data, while providing solutions for users to create more secure passwords.complex but easy to remember. The implementation of this system is expected to strengthen application security and increase user confidence in the protection of their personal data.
Co-Authors Ade Irma Yanti Hasibuan Akmal Akmal Al Ramzy Awaludin Baginda Restu Al Ghazali Dikie Rezekia Dinda Fatimatuz Zahra Fatwa Aulia Fauziah Mawaddah Harefa Fitriyani Nasution Habibah, Fitriatul Hargono Hargono Helmawati Hery Sunandar Igha Devira Pristine Ika Ima Nissa Khistinah Haryani Lale Hidayatin Shani Lalu Maulana Kusumaningrat Lisa Dwi Afri Magistra Sayyidina Al Kautsar Meri Muliani Hasibuan Mhd.Furqan Mira Anggraini Muhammad Albadar Adren Muhammad Muayyadin Nazira Ananda Nazwa Khaerinnita Noer Abyor Handayani Nur Aisyah Pandia Nur Indah Nasution Nurhilallaily Parulian Sibuea Rabiatul Adawiyah Ridwan Sholeh Riszki Fadillah Riyan Agus Faisal Rohani Salwa Latipah Santosa Pohan Saprina Putri Utama Ritonga Sentosa Pohan Septa Viani Sri Muliani Sukiyat, Sukiyat Tiwi Widiastuti Tria Putri Andini Wahyu Wahono Yori Marwinda Yusril Iza Mahendra Hasibuan Zulfahri Salim