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All Journal Ensiklopedia Education Review Computer Science and Information Technologies
Arifin, Husnul
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Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media

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URGENSI TENTANG PERATURAN SURROGACY (SEWA RAHIM) DI INDONESIA Arifin, Husnul; Gultom, Elfrida Ratnawati
Ensiklopedia Education Review Vol 6, No 2 (2024): Volume 6 No 2 Agustus 2024
Publisher : Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33559/eer.v6i1.2574

Abstract

A wife who has experienced uterine cancer which resulted in her uterus being removed so that it is no longer possible to have genetic children from the ovum and sperm of a legitimate married couple, while children are one of the gifts that give happiness to married couples, through the In Vitro Fertilization (IVF) Program generally used by married couples who find it difficult to have children, namely the wife has difficulty getting pregnant so she cannot raise the fetus in her own womb, surrogacy has not yet been legalized by regulation, this research uses a legal approach and supporting books which is what this paper aims to do. provides a solution for married couples who do not have a uterus to have children through surrogacy.
Implementation of face recognition using Python Christanto, Febrian Wahyu; Arifin, Husnul; Dewi, Christine; Prasandy, Teguh
Computer Science and Information Technologies Vol 7, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v7i1.p1-9

Abstract

Artificial intelligence (AI)-based technology systems are developing rapidly. Along with technological development the number of criminal cases caused by facial forgery is also growing. Cases of theft and housebreaking with fake photos are a common problem in Semarang. In 2022–2023 the number of cases of theft and housebreaking reached 372,965 with a crime risk level of 137/100,000 people. To overcome this problem the facial recognition system used in the door security system uses digital image processing. This method works by imitating how nerve cells communicate with interconnected neurons, or more precisely, how artificial neural networks function in humans. As training data, image capture and facial recognition are carried out using a webcam and the Python programming language with the TensorFlow library. The image processing algorithm uses 400 facial images with an accuracy rate of 95%. However further development is needed to improve the efficiency and accuracy of the system to produce better results.
Co-Authors Christine Dewi Elfrida Ratnawati Febrian Wahyu Christanto Teguh Prasandy, Teguh