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All Journal Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Seminar Nasional Teknologi Informasi Komunikasi dan Industri Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOISIE (Journal Of Information Systems And Informatics Engineering) Journal of Applied Engineering and Technological Science (JAETS) International Journal of Electrical, Energy and Power System Engineering (IJEEPSE) Unri Conference Series: Community Engagement Seandanan: Jurnal Pengabdian pada Masyarakat Journal of Applied Business and Technology
Adiya, M. Hasmil
Institut Bisnis Dan Teknologi Pelita Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Convolutional Neural Network Model for Sex Determination Using Femur Bones Nasien, Dewi; Adiya, M. Hasmil; Afrianty, Iis; Farkhan, Mochammad; Butar-Butar, Rio Juan Hendri
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1711

Abstract

Forensic anthropology is the critical discipline that applies physical anthropology in forensic education. One valuable application is the identification of the biological profile. However, in the aftermath of significant disasters, the identification of human skeletons becomes challenging due to their incompleteness and difficulty determining sex. Researchers have explored alternative indicators to address this issue, including using the femur bone as a reliable sex identifier. The development of artificial intelligence has created a new field called deep learning that has excelled in various applications, including sex determination using the femur bone. In this study, we employ the Convolutional Neural Network (CNN) method to identify the sex of human skeleton shards. A CNN model was trained on 91 CT-scan results of femur bones collected from Universiti Teknologi Malaysia, comprising 50 female and 41 male patients. The data pre-processing involves cropping, and the dataset is divided into training and validation subsets with varying percentages (60:4, 70:30, and 80:20). The constructed CNN architecture exhibits exceptional accuracy, achieving 100% accuracy in both training and validation data. Moreover, the precision, recall, and F1 score attained a perfect score of 1, validating the model's precise predictions. The results of this research demonstrate excellent accuracy, confirming the reliability of the developed model for sex determination. These findings demonstrate that using deep learning for sex determination is a novel and promising approach. The high accuracy of the CNN model provides a valuable tool for sex determination in challenging scenarios. This could have important implications for forensic investigations and help identify victims of disasters and other crimes.
Software Agent Simulation Design on the Efficiency of Food Delivery Ismail, Shahrinaz; Mostafa, Salama A; Baharum, Zirawani; Erianda, Aldo; Jaber, Mustafa Musa; Jubair, Mohammed Ahmed; Adiya, M. Hasmil
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2648

Abstract

Food delivery services have gained popularity since the emergence of online food delivery. Since the recent pandemic, the demand for service has increased tremendously. Due to several factors that affect how much time additional riders spend on the road; food delivery companies have no control over the location or timing of the delivery riders. There is a need to study and understand the food delivery riders' efficiency to estimate the service system's capacity. The study can ensure that the capacity is sufficient based on the number of orders, which usually depends on the number of potential customers within a territory and the time each rider takes to deliver the orders successfully. This study is an opportunity to focus on the efficiency of the riders since there is not much work at the operational level of the food delivery structure. This study takes up the opportunity to design a software agent simulation on the efficiency of riders' operations in food service due to the lack of simulation to predict this perspective, which could be extended to efficiency prediction. The results presented in this paper are based on the system design phase using the Tropos methodology. At movement in the simulation, the graph of the efficiency is calculated. Upon crossing the threshold, it is considered that the rider agents have achieved the efficiency rate required for decision-making. The simulation's primary operations depend on frontline remotely mobile workers like food delivery riders. It can benefit relevant organizations in decision-making during strategic capacity planning.
Co-Authors ahmad kamal, ahmad Ahmad Mulyadi Aldo Erianda, Aldo Alyauma Hajjah Anggara, Devi Willeam Angriawan, Sherkhing Baharum, Zirawani Butar-Butar, Rio Juan Hendri Dahliyusmanto, Dahliyusmanto Deny Jollyta Desnelita, Yenny Devi Willieam Anggara Dewi Nasien Erlin Fajri Adrianto Farkhan, Mochammad Feri Candra Gustientiedina Helly Aroza Siregar Ihsan, M. Nurul Iis Afrianty Ismail, Shahrinaz Jaber, Mustafa Musa Johan Johan Jubair, Mohammed Ahmed M Noval Dwi Pratama Marlim, Yulvia Nora Masyhuri Hamidi, Masyhuri Mostafa, Salama A Nadira Nurul Atika Rahmadhani, Ummi Sri Rahmadian Yuliendi, Rangga Rianda, Gilang Rida Rahim Roni Sanjaya Samah, Azurah A. Siddik, M. Sirait, Andrio Pratama ST, M.A.B, Okto Fenta Riandi Sukabul, Ahmad Suroyo Suroyo Suroyo Suroyo Wicaksono, Mahfuzan Hadi Wilda Susanti Willy Andrio Harefa Yacob, Azliza Yulianti, Deni Yusnita Rahayu