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All Journal Padjadjaran Journal of Dentistry JURNAL PAI: Jurnal Kajian Pendidikan Agama Islam
Putri, Rizkika
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Religion Biochemistry, Genetics & Molecular Biology Dentistry Education Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health Other

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Sumber Belajar Internet di Pesantren Putri, Rizkika
JURNAL PAI: Jurnal Kajian Pendidikan Agama Islam Vol 2 No 2 (2023)
Publisher : Prodi Pendidikan Agama Islam IAINU Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33507/pai.v2i2.1156

Abstract

This article explains how the internet is a learning resource in Islamic boarding schools. This article aims to explain the benefits and negative impacts of the internet as well as solutions for handling them in Islamic boarding schools. Islamic boarding schools have several criteria based on the number of students, based on facilities and infrastructure, and in terms of what is taught. The negative impacts of using the internet as a learning resource are explained in this article, namely; (1) the availability of access to pornographic sites which are feared to damage the morals of the students, (2) then there are entertainment facilities created by the internet, such as online games and social networking sites which can give the students a taste of addiction.
Performance analysis of DMF teeth detection using deep learning: A comparative study with clinical examination as quasi experimental study Novita, Rizki; Putri, Rizkika; Fitria, Maya; Oktiana, Maulisa; Elma, Yasmina; Rahayu, Handika; Janura, Subhan; Habibie, Hafidh
Padjadjaran Journal of Dentistry Vol 36, No 1 (2024): March 2024
Publisher : Faculty of Dentistry Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/pjd.vol36no1.52357

Abstract

ABSTRACTIntroduction: Decayed, missing, and filled teeth (DMF-T) are indicators used to assess the oral health status of an individual or a population. This examination is typically performed manually by dentists or dental therapists. In previous research, researchers have developed a deep learning model as a part of artificial intelligence that can detect DMF-T. Aim of this research was to analyze the comparison of the performance of deep learning with clinical examinations in DMF-T assessment. Methods: Experienced dentists conducted clinical examinations on 50 subjects who met the inclusion criteria. Oral clinical photos of the same patients were taken from various aspects, in total 250 images, and further analyzed using a deep learning model. The results of the clinical examination and deep learning were then statistically analyzed using an unpaired t-test to determine whether there were differences between groups. Results: The unpaired t-test analysis indicated that there was no significant difference between the result of DMF-T examination by dentist and by DL (P>0.05). Unpaired t-test of this research indicated no significant difference (P = 0.161). The unpaired t-test concluded that t Stat < t Critical two-tail, then who was accepted, which stated that there was no significant difference between the results of the DMF-T examination between two groups. Conclusion: The DL model demonstrates good clinical performance in detecting DMF-T.KeywordsDMF-T, clinical assessment, deep learning, caries detection
Co-Authors Elma, Yasmina Habibie, Hafidh Hargiani, Fransisca Xaveria Janura, Subhan Novita, Rizki Oktiana, Maulisa Rahayu, Handika