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Gonial angle and mandibular ramus height in Surabaya population: comparison and correlation analysis in panoramic radiograph Chusida, An'nisaa; Kurniawan, Arofi; Rizky, Beta Novia; Pribadi, Salma Nailah Pradnya; Diva, Annisa Tiara; Anandhiyah, Haura Destina; Alias, Aspalilah
Majalah Kedokteran Gigi Indonesia Vol 10, No 2 (2024): August
Publisher : Faculty of Dentistry, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/majkedgiind.98837

Abstract

One of the crucial steps of identifying an individual is to determine their sex. The mandible, which is the largest and strongest bone in the human face, is a useful tool due to its significant sexual dimorphism. Two features that are recognized for their high sexual dimorphism are the gonial angle and mandibular ramus height. Several studies have shown different results when using both measures to estimate sex, factors that are thought to influence morphological differences include age, population, sex, and physical activity. The objective of this study was to analyze the differences in gonial angle and mandibular ramus height between sexes using panoramic radiography. Additionally, it aimed to analyze the correlation between these measurements and sex. The measurements of the gonial angle and mandibular ramus height were conducted using ImageJ software. Initially, the specific anatomical landmarks were identified, and the software’s measurement tools were then employed to accurately assess the height and angle based on these selected points. The sample consisted of secondary data obtained from 70 panoramic radiographs of patients aged 20–45 years at the Dental and Oral Teaching Hospital (RSGMP) of Universitas Airlangga, Surabaya. Data analysis was conducted using the independent t-test and Pearson correlation. There was a significant difference in the mandibular ramus height between sexes, with males having a greater height (p < 0.05). It was also discovered that, despite the fact that males exhibited a smaller gonial angle compared to females, this difference was not statistically significant (p = 0.29). Furthermore, a significant correlation was observed between mandibular ramus height and sex (r = 0.498); however, there was no significant correlation between gonial angle and sex (r = -0.128). The study reveals a significant difference in mandibular ramus height between males and females, with males exhibiting greater height. This parameter shows a strong correlation with sex, making it a reliable indicator for sex determination. Conversely, the gonial angle is not suitable for this purpose.
Impact of Smoking on Oral Mucosa: A Case Report Nurfianti, Nurfianti; Adinda Rizkhi Nurpratama, Shafa; Audiawati; Ronal, Ahmad; Rokhani, Faezah; Alias, Aspalilah
YARSI Dental Journal Vol. 2 No. 1 (2024): YARSI DENTAL JOURNAL
Publisher : Lembaga Penelitian Universitas YARSI

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Abstract

Introduction: The discoloration of the oral mucosa is influenced by the presence and degree of dilation of the subepithelial corium blood vessels and the amount of melanin pigment. Changes in the oral mucosa of smokers encompass various significant pathological conditions, including smoker’s melanosis and hyposalivation. Case Report: A 27-year-old male presented to the dental hospital with complaints of black discoloration on the lower jaw gingiva, persisting for the past two years. He exhibited widespread black spots on both the upper and lower jaws without pain. The patient also reported dry lips. He had a smoking history of seven years, with a consumption of 10 cigarettes per day. Examination revealed pigmented lesions, and the patient's stimulated salivary flow rate was 0.7 ml/min. Discussion: The oral cavity is a primary gateway for toxic substances from cigarettes, while saliva is the main biological fluid exposed to cigarette smoke, which contains various toxic compounds responsible for structural and functional changes in saliva. Exposure to cigarette smoke can lead to reduced salivary flow rate (hyposalivation), changes in salivary components that may result in malignancies, and changes in the color characteristics of the oral mucosa, such as the appearance of pigmented lesions known as smoker’s melanosis. Management of hyposalivation in patients includes providing education to improve hydration and encouraging smoking cessation. Conclusion: Smoking affects the condition of an individual's oral cavity, impacting both saliva and the oral mucosa. It is crucial for dentists to educate patients about the use of tobacco and its effects on oral health.
Students’ Experience, Self-Confidence, and Perception Toward Endodontic Learning: National Survey Among Malaysian Dental Schools Omar, Siti Hajar; Alias, Aspalilah; Baharin, Safura Anita
Journal of Dentistry Indonesia Vol. 30, No. 1
Publisher : UI Scholars Hub

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Abstract

Objective: This study aimed to evaluate the first endodontic case experiences, self-confidence levels, and perceptions toward endodontic learning of final-year undergraduate students. Methods: An online questionnaire was emailed to 270 final-year dental students at 10 Malaysian dental schools. The questionnaire consists of 29 questions on students’ experience, self-confidence, and perception toward endodontic learning. Results: The response rate was 74.4%. The most frequently treated case was tooth diagnosed as nonvital associated with periapical periodontitis. Most of the students perceived working length determination as the most difficult stage and reported having low confidence in locating canal orifices in multirooted teeth and achieving satisfactory obturation. Overall, the students were satisfied with the endodontic knowledge taught by their respective faculties. Conclusion: Endodontic teaching in Malaysian dental schools was perceived as satisfactory by most dental students. Although endodontic treatment is perceived as difficult, students demonstrated high confidence in carrying out this treatment. However, they had limited ability in treating the complex root canal system.
CLASSIFICATION OF SKELETAL MALOCCLUSION USING CONVENTIONAL NEURAL NETWORK (CNN) WITH VISION ATTENTION Ronny Eka Wicaksana, I Putu; Wibowo, Antoni; Rojali, Rojali; A Samah, Azurah; Alias, Aspalilah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2709-2726

Abstract

Skeletal malocclusion, a common orthodontic condition, affects jaw function and dental health. It is often caused by genetic factors, abnormal growth, bad habits, or trauma. Conventional diagnostic models often fail to generalize across diverse datasets, leading to overfitting and poor test performance. This study aimed to improve diagnostic accuracy by incorporating Vision Attention mechanisms into a custom Convolutional Neural Network (CNN), enabling the model to focus on critical regions in X-ray images. A total of 491 radiographic images depicting facial skeletal structures with various malocclusion types (Classes 1, 2, and 3) were used in this study. A custom CNN was developed and evaluated both with and without attention mechanisms—specifically, Scaled Dot Product Attention and Multihead Attention—to assess their impact on classification performance. The baseline CNN without attention achieved an accuracy of 0.68. With Scaled Dot Product Attention, accuracy improved to 0.72, while Multihead Attention achieved the highest accuracy of 0.76. Evaluation using weighted average precision, recall, and F1-score showed that attention mechanisms significantly enhanced the model’s ability to differentiate between malocclusion classes. Notably, the Multihead Attention model yielded the best performance, reducing misclassification errors and improving generalization. Confusion matrix analysis revealed that it had the lowest classification errors, especially in distinguishing between Class 0 and Class 1. These results suggest that incorporating attention mechanisms, particularly Multihead Attention, enhances CNN performance by improving feature extraction and classification accuracy. Future research should explore more diverse datasets and implement advanced augmentation techniques to improve clinical reliability.