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Pasaribu, Roben S.
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Estimation of Time of Death through Observation of Microbiota Changes in the Oral Cavity Oktaviana, Fahriza R.; Gultom, Ferry P.; Pasaribu, Roben S.; Auerkari, Elza I.
e-GiGi Vol. 13 No. 1 (2025): e-GiGi
Publisher : Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35790/eg.v13i1.54461

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Abstract: Various methods for estimating post-mortem (PMI) have been investigated such as rigor mortis, livor mortis, molecular, chemical, and forensic entomology (insect) methods. However, these methods have weaknesses, therefore researchers are looking for more accurate methods in determining the time of death of a person. Molecular methods are unreliable due to the degradation of DNA, RNA, and proteins in corpses over time. In different parts of the body, the amount of diversity of microbes will be different. The oral cavity is the most abundant microbial area among other parts of the body due to its continuous exposure to the respiratory and digestive systems. This area has great potential in estimating time intervals of death because of its ease of access and the types of microbiomes that predominate at any given time. Therefore, this narrative review was conducted to describe studies that used oral microbiota communities to estimate post-mortem intervals. Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes are the dominant microbial types found in corpses. Firmicutes became one of the dominant bacterial phyla in the early stages of decomposition. Actinobacteria were found to decrease as PMI increased. Studies have shown that the oral microbiome has excellent potential as a parameter to determine the post-mortem interval. However, further research is needed with more complex environmental conditions such as different humidity and temperature. In addition, further research requires more samples of human remains to obtain more valid results. Keywords: oral microbiome; post-mortem interval; human identification; forensic odontology
Artificial Intelligence–Driven Innovations in Forensic Odontology for Human Identification: A Narrative Review Pasaribu, Roben S.; Muliawati, Dian; Yunus, Aditia D.
e-GiGi Vol. 14 No. 2 (2026): e-GiGi
Publisher : Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35790/eg.v14i2.65713

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Abstract: Forensic odontology is a branch of forensic science that plays a role in identification, including age and sex estimation. The identification results acted as valid evidence based on the science of forensic dentistry, which is used in the judicial process. Traditional methods of identification have the disadvantage of subjectivity on the part of the examiner. The analysis results can be biased, leading to incorrect conclusions. The rapid development of technology has impacted the field of forensic odontology. This review aimed to evaluate the potential and applications of AI in forensic odontology. Artificial intelligence (AI) is a computer-based system designed using principles of human intelligence. The application of artificial intelligence to assist forensic experts is growing and being explored increasingly. Artificial intelligence in forensic odontology plays a role in gender determination, age estimation, lip print analysis, toothmark analysis, personal identification, and facial reconstruction. The AI-based identification process is expected to eliminate the researcher's subjectivity and improve the accuracy of the results. In conclusion, artificial intelligence (AI) has significantly influenced forensic odontology by supporting key forensic tasks, including age estimation, sex determination, cheiloscopy analysis, and facial reconstruction. Keywords: forensic odontology; artificial intelligence; identification process; application