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All Journal Journal of Dentistry Indonesia Majalah Kedokteran Gigi Indonesia BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Ilmiah Kesehatan Masyarakat : Media Komunikasi Komunitas Kesehatan Masyarakat Indonesian Journal of Dental Medicine Yarsi Dental Journal
Alias, Aspalilah
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Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Public Health Transportation

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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.
The Quality of Life Related to Oral Health Among The Elderly Based on Pathological Lesions in Soft Tissues Nurfianti, Nurfianti; Nurhadizah, Putri Ayu; Ronal, Ahmad; Audiawati, Audiawati; Riani, Siti Nur; Rokhani, Faezah; Alias, Aspalilah
Jurnal Ilmiah Kesehatan Masyarakat : Media Komunikasi Komunitas Kesehatan Masyarakat Vol 17 No 4 (2025): JIKM Vol 17, Issue 4, November 2025
Publisher : Public Health Undergraduate Program, Faculty of Health Science, Universitas Pembangunan Nasional Veteran Jakarta

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Abstract

Background: Oral health plays an important role in overall health and quality of life among the elderly. The presence of soft tissue lesions in the oral cavity, particularly in this vulnerable population, warrants attention due to its potential association with systemic health conditions and overall quality of life. Maintaining a high quality of life is crucial, as it is closely linked to health status, life satisfaction, and overall well-being. This study aimed to examine oral health–related quality of life among the elderly, with particular focus on the presence of pathological soft tissue lesions. Method: A cross-sectional study was conducted using a purposive sampling technique. Data collection included demographic information, administration of the Oral Health Impact Profile (OHIP-14) questionnaire, and comprehensive intraoral examinations to identify pathological lesions. The Mann–Whitney U test was used to compare quality-of-life scores between elderly individuals with and without pathological lesions. Results: Among the 94 subjects examined, 36 were found to have pathological lesions, while none of the 58 (p=0.024, p<0.05) showed a difference in the quality of life between elderly individuals with and without pathological lesions. Conclusion: There is a significant difference in oral health–related quality of life among the elderly, which is influenced by the presence of pathological soft tissue lesions.
Application of artificial intelligence for dental age estimation in children and adolescents: A review Kurniawan, Arofi; Chusida, An'nisaa; Rahmaputri, Annisa; Nurmalia, Salsabila; Prasetyo, Aulia Imani Sri; Akbar, Aeeshah Aswi; Maritza, Yasmina Putri; Rizky, Beta Novia; Marini, Maria Istiqomah; Alias, Aspalilah; Marya, Anand
Indonesian Journal of Dental Medicine Vol. 8 No. 2 (2025): Indonesian Journal of Dental Medicine
Publisher : Faculty of Dental Medicine Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/ijdm.v8i2.2025.90-93

Abstract

Background: Accurate dental age estimation is essential across multiple disciplines, including forensic identification, pediatric dentistry, and legal medicine. Conventional approaches, while extensively utilized, are constrained by observer subjectivity, population-dependent variation, and limited reproducibility. The emergence of artificial intelligence (AI) particularly through machine learning (ML) and deep learning (DL) technologies has introduced a transformative shift in age estimation, offering automated, data-driven alternatives that enhance precision, consistency, and efficiency. Purpose: This review aims to critically examine the current applications of AI in dental age estimation for children and adolescents. Review: An online literature search was conducted in the PubMed database using a structured set of keywords, complemented by manual searches through Google Scholar to ensure comprehensive coverage. Nine relevant studies were identified, encompassing a range of artificial intelligence (AI) approaches, including artificial neural networks (ANN), convolutional neural networks (CNN), support vector machines (SVM), and other machine learning (ML) algorithms. These models were applied to established dental age estimation methods such as those proposed by Demirjian, Willems, Cameriere, and Al-Qahtani. Overall, AI-based models demonstrated superior performance compared to traditional techniques, showing lower mean absolute error values and higher classification accuracy across various age categories. Notably, several models achieved accuracy levels exceeding 90%, highlighting the potential of AI to enhance precision and reliability in dental age estimation. Conclusion: Artificial intelligence demonstrates significant potential in improving the accuracy, efficiency, and reproducibility of dental age estimation in children and adolescents. While current findings are promising, further validation across diverse populations and standardized protocols is necessary before widespread forensic and clinical adoption.
Co-Authors A Samah, Azurah Adinda Rizkhi Nurpratama, Shafa Ahmad Ronal Akbar, Aeeshah Aswi Anandhiyah, Haura Destina Antoni Wibowo An’nisaa Chusida Arofi Kurniawan Audiawati Audiawati, Audiawati Baharin, Safura Anita Beta Novia Rizky Chusida, An'nisaa Diva, Annisa Tiara Maria Istiqomah Marini Maritza, Yasmina Putri Marya, Anand NURFIANTI NURFIANTI, NURFIANTI Nurhadizah, Putri Ayu Nurmalia, Salsabila Omar, Siti Hajar Prasetyo, Aulia Imani Sri Pribadi, Salma Nailah Pradnya Rahmaputri, Annisa Riani, Siti Nur Rojali, Rojali Rokhani, Faezah Ronny Eka Wicaksana, I Putu