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All Journal Prosiding Semnastek Jurnal Ilmiah FIFO Jurnal ULTIMA InfoSys TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri Jurnal E-Komtek Indonesian Journal of Electrical Engineering and Computer Science JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal of Authentic Research
Herman Bedi Agtriadi, Herman Bedi
Institut Teknologi PLN
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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CT-Scan Image Segmentation of Liver Cancer Using the Active Contour Method Nurazizah Nurazizah; Dwina Kuswardani; Herman Bedi Agtriadi
Jurnal E-Komtek Vol 10 No 1 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v10i1.3273

Abstract

Liver cancer is one of the most common types of cancer both in Indonesia and throughout the world. The increase in liver cancer cases is thought to be related to the increase in hepatitis B and C virus infections. According to statistical data from Globocan, in 2022 there will be 866,000 cases of liver cancer recorded worldwide, with 758,000 deaths due to this disease. To overcome this challenge, image processing plays an important role in improving image quality and performing segmentation to separate objects based on certain characteristics. In this research, the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Contrast Stretching methods are used to improve image quality, while the Active Contour method is applied for image segmentation. Validation of segmentation results was carried out using Receiver Operating Characteristic (ROC) calculations. Testing was conducted on 21 CT-scan images of liver cancer, yielding an accuracy of 97.16%, a sensitivity of 75.69%, and a specificity of 98.85%. This research was conducted using the MATLAB application (R2015a). These findings demonstrate the effectiveness of the methods used in supporting the diagnosis and treatment of liver cancer
Implementation of The K-Nearest Neighbors (KNN) Algorithm in The Process of Student Graduation Prediction (Case Study of The Bachelor of Informatics Engineering Program, PLN Institute of Technology, Jakarta) Andi Abd. Jalil. L; Herman Bedi Agtriadi; Meilia Nur Indah; Rakhmadi Ifansyah Putra
Jurnal E-Komtek Vol 10 No 1 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v10i1.3299

Abstract

Student graduation is one of the key indicators in a university’s Internal Quality Assurance System (SPMI). Based on data from the Bachelor of Informatics Engineering program, out of 305 students from the 2016 cohort, 227 graduated on time and 78 graduated late. This study aims to predict student graduation using the K-Nearest Neighbors (KNN) algorithm. The research stages include data collection and division for training and testing, parameter determination with K=3, and distance calculation between data points. The results show that the KNN model with parameter K=3 achieved an accuracy rate of 90% in predicting student graduation. This demonstrates that the KNN method is effective in predicting student graduation outcomes.
Co-Authors Abdurrasyid Abdurrasyid, Abdurrasyid Afandi, Adam Afif Dwi Kurniawan Afifah Nurlita Octaviasari Andi Abd. Jalil. L Angga Saputra Chaerudin, Muhammad Farhan Darma Rusjdi David Gabriel Sembiring Dewi Arianti Wulandari Dimas Arditya Pinandhito Dina Aulia Djunaidi, Karina Duliades Mirsal Dwina Kuswardani Efy Yosrita Febryansyah Hans Arieyantho, Febry Haris, Abdul Hendra Jatnika Indrianto Indrianto Indrianto Kusnandar, Adam Ramdani Linda Alifiana luqman Luqman, Luqman M Habibi Max Teja Ajie Meilia Nur Indah Meilia Nur Indah Susanti Meilia Nur Indah Susanti, Meilia Nur Melania Erika Andolo Mochamad Farid Rifai Muhammad Nur Khanib Nurazizah Nurazizah Ocha Nia Martcya Situmorang Octaviasari, Afifah Nurlita Purwanto, Yudhi Rahmad Evan Rakhmadi Ifansyah Putra Rizqia Cahyaningtyas Susanti, Meilia Wijayanti , Anis Yessy Fitriani Zakiya Viantika Sihabudin4 Zakiyah Misfazilah