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All Journal Jurnal Kedokteran Gigi Universitas Padjadjaran Padjadjaran Journal of Dentistry JOIV : International Journal on Informatics Visualization Jurnal Pengabdian Masyarakat The Indonesian Journal of Computer Science
Arya Brahmanta, Arya
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Medicine & Pharmacology Public Health Social Sciences Other

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Potensi Stichopus hermanii dan Hyperbaric Oxygen Therapy untuk Mempercepat Perawatan Ortodonti Sandana, I Ketut Ika; Velisia, Jessica; Yunior, Alexander; Brahmanta, Arya; Prameswari, Noengki
Jurnal Kedokteran Gigi Universitas Padjadjaran Vol 29, No 3 (2017): Desember
Publisher : Fakultas Kedokteran Gigi Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.055 KB) | DOI: 10.24198/jkg.v29i3.15951

Abstract

Pendahuluan: Perawatan ortodonti memerlukan inovasi untuk mempercepat waktu perawatan. Perawatan ortodonti menyebabkan adanya daerah tekanan dan tarikan yang dipengaruhi oleh ekspresi RANK pada daerah tekanan, yang merangsang osteoklas dan ekspresi OPG pada daerah tarikan yang merangsang osteoblast. Stichopus hermanii dikenal mempunyai efek pada proses penyembuhan sedangkan Hiperbarik Oksigen Therapy (HBOT) memberikan efek remodeling. Tujuan studi literatur ini bertujuan untuk mengungkapkan mekanisme potensi gel Stichopus hermanii dan HBOT dalam mempercepat proses pergerakan gigi saat perawatan ortodonti, sehingga dapat menjadi alternatif terapi selain terapi pemberian low-level laser, dan corticotomy surgery. Telaah Pustaka: Resorpsi terjadi akibat tekanan piranti ortodonti. Inovasi untuk mempercepat perawatan ortodonti, dilakukan pada daerah tekanan dan tarikan. Pemberian Stichopus hermanii secara lokal dapat meningkatkan level OPG yang berfungsi menghambat ikatan antara RANKL dan RANK, sehingga menghambat aktivasi osteoklas dan mengaktivasi aposisi tulang. Terapi HBOT menstimulasi ekspresi RANK pada daerah tekanan membantu mempercepat proses resorpsi serta OPG. Kombinasi Stichopus hermanii dan HBOT menyebabkan pergerakan gigi meningkat melalui proses remodelling yang lebih cepat karena aktivasi aposisi tulang melalui OPG yang menghambat ikatan RANK-RANKL. Simpulan: Inovasi kombinasi terapi Stichopus hermanii dan HBOT dapat meningkatkan pergerakan gigi ortodonti melalui aktivasi OPG dan ROS.Introduction: Orthodontic treatment requires innovation to accelerate the treatment time. Orthodontic treatment is resulting in the occurrence of the tension and traction regions affected by the RANK expression in the traction region, which stimulates the osteoclast and OPG expression in the traction thus stimulate the osteoblasts. Stichopus hermanii is known to affect the healing process, while Hyperbaric Oxygen Therapy (HBOT) provides the remodelling effects. The purpose of this literature study was aimed to reveal the potential mechanisms of Stichopus hermanii gel and HBOT in accelerating the process of the teeth movement during orthodontic treatment to made it as alternative adjunctive therapy besides the low-level laser therapy and corticotomy surgery. Literature Review: Resorption was occurred due to the pressure of orthodontic devices. Innovations in accelerating the orthodontic treatment were performed in the tension and traction region. Administration of Stichopus hermanii locally may increase the OPG levels that inhibit the bond between RANKL and RANK, thus inhibiting the osteoclast activation and activated the bone resorption. HBOT therapy stimulated the RANK expression in the tension region to accelerate the resorption and OPG process. The combination of Stichopus hermanii and HBOT caused an increasing teeth movement through faster remodelling process due to the bone apposition activation through OPG that inhibits the RANK-RANKL bonding. Conclusion: Therapy innovation through the combination of Stichopus hermanii and HBOT was able to improve the orthodontic teeth movement through the activation of OPG and ROS.
Deep Learning Models for Dental Conditions Classification Using Intraoral Images Makarim, Ahmad Fauzi; Karlita, Tita; Sigit, Riyanto; Bayu Dewantara, Bima Sena; Brahmanta, Arya
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.1914

Abstract

This paper presents the digitalization of dentistry medical records to support the dentist in the patient examination process. A dentist uses manual input to fill out the evaluation form by drawing and labeling each patient’s tooth condition based on their observations. Consequently, it takes too long to finish only one examination. For time efficiency, using AI-based digitalization technology can be a promising solution. To address the problem, we made and compared several classification models to recognize human dental conditions to help doctors analyze patient teeth. We apply the YOLOv5, MobileNet V2, and IONet (proposed CNN model) as deep learning models to recognize the five common human dental conditions: normal, filling, caries, gangrene radix, and impaction. We tested the ability of YOLO classification as an object detection model and compared it with classification models. We used a dataset of 3.708 intraoral dental images generated by various augmentation methods from 1.767 original images. We collected and annotated the dataset with the help of dentists. Furthermore, the dataset is divided into three parts: 90% of the total dataset is used as training and validation data, then divided again into 80% training data and 20% validation data. 10% of the total dataset will be used as testing data to compare classification performance. Based on our experiments, YOLOv5, as an object detection model, can classify dental conditions in humans better than the classification model. YOLOv5 produces an 82% accuracy testing value and performs better than the classification model. MobileNet V2 and IONet only get 80% and 70% testing accuracy. Although statistically, there is not much of a difference between the test accuracy values for YOLOv5 and MobileNet v2, the speed in classifying dental objects using YOLOv5 is more efficient, considering that YOLOv5 is an object detection model. There are still challenges with the deep learning technique used in this research, but these can be addressed in further development. A more complex model and the enlargement of more data, ensuring it is varied and balanced, can be used to address the limitations. 
Usability testing of “smart odontogram” application based on user’s experience Brahmanta, Arya; Maharani, Aulia Dwi; Dewantara, Bima Sena Bayu; Sigit, Riyanto; Sukaridhoto, Sritrusta; Fadhillah, Excel Daris
Padjadjaran Journal of Dentistry Vol 34, No 2 (2022): July
Publisher : Faculty of Dentistry Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/pjd.vol34no2.36566

Abstract

ABSTRACTIntroduction: Collecting dental data for odontogram in medical records is done chiefly conventionally and causes a lot of human errors. Disadvantages of the conventional method can be overcome by developing a server-based system to store medical information equipped with embedded artificial intelligence (AI), which can identify the patient’s dental condition using an intra-oral camera with the help of Deep Learning algorithms. It is essential to evaluate the usability of this application to adapt to user needs. This study aimed to know the user’s experience in using this application and also provide information for improvements of the application. Methods: This is quantitative descriptive research with 15 users (dentists) as the respondent. The questionnaire was used to measure the user’s experience using this application. The user’s experiences measured are effectivity, efficiency, and satisfaction.  Results: The highest scores of respondents on the three variables are extremely efficient, effective, and satisfied (9 people). The lowest score is slightly efficient and neutral on the efficiency and effectiveness variables (0 people). In the satisfaction variable, the lowest score is slightly satisfied (0 people). Conclusions: The Usability Testing of the “Smart Odontogram” Application based on User’s Experience showed a good result in 3 variables: effectiveness, efficiency, and satisfactionKeywords: smart Odontogram; medical record; application; usability testing; user’s experience
Deteksi Kondisi Gigi Manusia pada Citra Intraoral Menggunakan YOLOv5 Makarim, Ahmad Fauzi; Karlita, Tita; Sigit, Riyanto; Dewantara, Bima Sena Bayu; Brahmanta, Arya
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3355

Abstract

Proses identifikasi dan pencatatan rekam medis pada praktik kedokteran gigi masih dilakukan secara manual. Akibatnya, proses tersebut memakan waktu yang cukup lama. Pada penelitian ini metode deteksi objek dimanfaatkan untuk membantu dokter melakukan identifikasi pada gigi pasien. YOLOv5 dipilih untuk dilatihkan pada dataset citra intraoral dengan lima kelas kondisi gigi (normal, karies, tumpatan, sisa akar, dan impaksi). Dataset yang digunakan berjumlah 1.767 data citra intraoral yang diambil dan dilabeli oleh dokter gigi. Dataset dibagi menjadi tiga bagian, 10% digunakan untuk data testing dan 90% digunakan untuk data training dan validation. Dilakukan komparasi performa berdasarkan nilai metrik evaluasi terhadap tiga jenis model YOLOv5 (S, M, L). Dari hasil pelatihan, YOLOv5 M sebagai model terbaik mendapatkan nilai mAP sebesar 84%, dan 82% nilai akurasi testing. Penelitian ini telah memenuhi tujuan utama untuk membangun sebuah model deep learning yang robust untuk mendeteksi dan mengklasifikasi beberapa kondisi gigi pada manusia.
PENGABDIAN MASYARAKAT PEMBERIAN EDUKASI KESEHATAN GIGI DAN MULUT PADA SISWA SD HANG TUAH 1 SURABAYA Soesilo, Diana; Brahmanta, Arya; Ramadhi, Cakrawartyha; Hermanto, Eddy; Khoironi, Emy; Wijaya, Yongki Hadinata; Fitriani, Yufita; Syahdinda, Meralda Rossy
BESIRU : Jurnal Pengabdian Masyarakat Vol. 2 No. 6 (2025): BESIRU : Jurnal Pengabdian Masyarakat, Juni 2025
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/besiru.v2i6.1411

Abstract

Latar belakang.  Karies gigi termasuk penyakit infeksi kronis yang biasanya terjadi akibat bakteri kariogenik yang menempel pada gigi yang akan memetabolisme gula sehingga menghasilkan asam, yang seiring dengan waktu akan mendemineralisasi struktur gigi. Anak-anak usia sekolah sangat menyukai makanan dan minuman manis dengan kandungan glukosa tinggi, dan sering kali kurang memahami teknik menyikat gigi yang benar, serta jarang memeriksakan gigi mereka ke fasilitas kesehatan. Metode pelaksanaan. Siswa akan diberikan soal pre test dan post test untuk mengetahui pengetahuannya terhadap kesehatan gigi dan rongga mulut sebelum dan setelah diberikan edukasi dan dilakukan pemeriksaan kondisi rongga mulut siswa oleh  dokter gigi RSGMP Nala Husada. Hasil dan pembahasan. Hasil pre tes dan post tes menunjukkan terdapat 1 orang dari 85 orang siswa yang mengikuti tes memperoleh skor SEMPURNA. Pada kategori NAIK persentasenya adalah 76% yang artinya terdapat 64 orang. Kategori hasil TETAP terdapat 17% berarti terdapat 14 orang yang skornya TETAP. Terdapat 6 orang atau sekitar 8% dari siswa yang nilai post test-nya lebih buruk daripada nilai pre test sehingga termasuk dalam kategori TURUN.Kesimpulan Pemberian edukasi tentang kesehatan gigi dan rongga mulut siswa SD Hang Tuah I memberikan hasil yang baik karena persentase terbesar adalah terdapat peningkatan pengetahuan siswa SD Hang Tuah I tentang kesehatan rongga mulut.
The changes of fibroblast and periodontal ligament characteristics in orthodontic tooth movement with adjuvant HBOT and propolis: A study in Guinea pigs Prayogo, Rosiana Dewi; Sandy, Bunga Novita; Sujarwo, Hendy; Fitri, Karimatul; Brahmanta, Arya; Rahardjo, Pambudi; Handayani, Budi
Padjadjaran Journal of Dentistry Vol 32, No 1 (2020): March 2020
Publisher : Faculty of Dentistry Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/pjd.vol32no1.19848

Abstract

Introduction: Periodontal ligament plays an essential role in preventing relapse after orthodontic treatment. Hyperbaric Oxygen Therapy (HBOT) and propolis gel can increase the amount of fibroblast in the tension area during orthodontic treatment, thus affecting the periodontal ligament. This research was aimed to analyse the difference of the width of the periodontal ligament and amount of fibroblast in the tension area with the administration of propolis gel and HBOT in an attempt to prevent orthodontic relapse. Methods: Forty-two male guinea pigs were randomly divided into 7 groups of treatments― the untreated group (I – negative group), group with rubber separator (II – positive group), 3% propolis gel treatment group (III), 5% propolis gel treatment group (IV), the HBOT treatment group (V), combination of 3% propolis gel and HBOT treatment group, and combination of 5% propolis gel and HBOT treatment group. The upper left central incisor was extracted distally using a 14-days separator rubber in the positive group and the treatment group; then the separator rubber was removed for 2 days to conduct the relapse process. The data were analysed by LSD statistical test. Results: The result of the combination of HBOT and propolis gel treatment showed significant differences among all groups (p<0.05) in the width of the periodontal ligament (1.03), and the number of fibroblasts was 95.67 in the tension site. Conclusions: The combination of HBOT and propolis gel affect the width of periodontal ligament and the number of fibroblasts in the area of the orthodontic relapse.
Co-Authors Alief, Febryan Aulia Dwi Maharani Bima Sena Bayu Dewantara Diana Soesilo, Diana Dirmadana, Robbi Akbar Eddy Hermanto Fadhillah, Excel Daris Fitri, Karimatul Handayani, Budi Handayani, Budi Jonathan, Ivan Nicholas Khoironi, Emy Makarim, Ahmad Fauzi Mediani, Ghina Sucilia Noengki Prameswari Pambudi Rahardjo Prayogo, Rosiana Dewi Ramadhi, Cakrawartyha Riyanto Sigit, Riyanto Sandana, I Ketut Ika Sandana, I Ketut Ika Sandy, Bunga Novita Sujarwo, Hendy Syahdinda, Meralda Rossy Tita Karlita Velisia, Jessica Yasin, Jessica Jenuary Yongki Hadinata Wijaya Yufita Fitriani Yunior, Alexander