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All Journal LEX CRIMEN JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Sinkron : Jurnal dan Penelitian Teknik Informatika
Widi Santoso
Unknown Affiliation
Computer Science & IT Law, Crime, Criminology & Criminal Justice Mathematics Other

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PERLINDUNGAN HUKUM TERHADAP ANAK DARI TINDAKAN KEKERASAN Santoso, Widi
LEX CRIMEN Vol 3, No 4 (2014): Lex Crimen
Publisher : LEX CRIMEN

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Abstract

Tujuan dilakukannya penelitian ini adalah untuk mengetahui bagaimanakah bentuk-bentuk kekerasan yang dapat dialami anak dan bagaimanakah perlindungan hukum terhadap anak dari tindakan kekerasan. Penelitian ini menggunakan metode penelitian yuridis normatif dan dapat disimpulkan, bahwa: 1. Bentuk-bentuk kekerasan yang terjadi terhadap anak adalah bentuk kekerasan fisik, kekerasan psikis/emosional dan kekerasan seksual, antara lain berupa: dicubit, didorong, digigit, dicekik, ditendang, disiram, ditempeleng disuruh push-up, disuruh lari, mengancam, diomeli, dicaci, diludahi, digunduli, diusir dipaksa bersihkan wc, dipaksa mencabut rumput, dirayu, dicolek, dipaksa onani, oral seks, diperkosa dan lain sebagainya.  2. Perlindungan hukum terhadap anak dari tindakan kekerasan diatur dalam UU Nomor 23 Tahun 2002 tentang Perlindungan Anak, UU Nomor 22 Tahun 2004 tentang Penghapusan Kekerasan Dalam Rumah Tangga dan KUHP melalui pasal-pasalnya yang mengatur tentang masalah persetubuhan, perbuatan cabul, menghilangkan jiwa anak dan penganiayaan. Kata kunci: Anak, Tindakan kekerasan
IMPLEMENTASI APLIKASI JUAL BELI MOBIL BEKAS DENGAN METODE ANALYTICAL HIERARCHY PROCESS DAN NAIVE BAYES Widi Santoso; Viny Christanti Mawardi; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (658.34 KB) | DOI: 10.24912/jiksi.v9i1.11597

Abstract

One area of life that is affected by the rapid development and advancement of technology is the automotive sector. Information technology bridges various groups who participate in automotive transaction activities. Therefore, the physical condition and performance of an automotive are determining factors for a buyer who wants to make a purchase.Not all types of automotive offered meet the buyers' standards, nor do they have a selling price in accordance with the quality described by the seller. The Analytical Hierarchy Process (AHP) method helps determine the type of automotive that suits the buyers' wishes and the Naïve Bayes method helps determine the selling price according to the quality of the automotive offered.The Analytical Hierarchy Process (AHP) method is a decision support model that describes a complex multi-factor or multi-criteria problem into a hierarchy, which in turn can organize complex problems into a more orderly and systematic manner. The Naïve Bayes method is a classification using probability and statistical methods that predict future opportunities based on past experiences. Naïve Bayes calculates a set of probabilities by adding up the frequency and value combinations from the given dataset. Based on the comparison of the calculation results with the tests carried out, the AHP method obtains an accuracy rate of 100% in displaying the criteria for cars being sold. Meanwhile, the Naïve Bayes method obtains an accuracy rate of 100% in determining whether a dealer is interested in buying a car or not.
Integration of Artificial Intelligence in Facial Recognition Systems for Software Security Santoso, Widi; Safitri, Rahayu; Samidi, Samidi
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 2 (2024): Article Research Volume 8 Issue 2, April 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.13612

Abstract

Facial recognition technology, a cornerstone in modern software security, has seen significant advancements through the integration of Artificial Intelligence (AI). This research focuses on enhancing facial recognition systems by incorporating sophisticated machine learning algorithms and deep neural networks. By doing so, the goal is to increase the accuracy and reliability of these systems in security applications. The study uses a variety of facial datasets to train AI models that are adept at extracting facial features and recognizing patterns. These models are subjected to rigorous testing to evaluate their performance in terms of identification accuracy, processing speed, and adaptability to different environmental conditions. One of the key challenges addressed in the research is the system's vulnerability to errors and potential misuse. Ethical considerations and privacy concerns are at the forefront of the study. The research highlights the importance of designing AI-based facial recognition systems that respect user privacy and are resistant to biases, thus fostering trust and acceptance among users. The results of the study show a marked improvement in system performance, demonstrating enhanced recognition accuracy and speed, while maintaining robustness across different conditions. By offering practical recommendations for the development of secure, ethical, and privacy-aware facial recognition systems, this research contributes valuable insights into the integration of AI in software security. It underscores the importance of continuous innovation and ethical responsibility in the deployment of facial recognition technologies, shaping the future landscape of technological security measures
Co-Authors Safitri, Rahayu Samidi Samidi TRI SUTRISNO Viny Christanti M