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All Journal Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Syntax Transformation
Waluyo, Adhi
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Humanities Computer Science & IT Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Imposition of Criminal Sanctions Against Perpetrators of Prostitution in Indonesia Waluyo, Adhi; Sobandi, Sobandi; Suandika, I Nyoman
Jurnal Syntax Transformation Vol 6 No 4 (2025): Jurnal Syntax Transformation
Publisher : CV. Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jst.v6i4.1068

Abstract

Prostitution in Indonesia continues to be a complex and contentious issue, involving not only pimps and sex workers but also service users who remain largely unregulated by existing laws. This research examines the gaps in Indonesia’s legal framework, particularly the absence of provisions criminalizing prostitution service users. The study aims to explore how Indonesian law addresses the criminalization of all parties involved in prostitution, focusing on service users and the enforcement of criminal sanctions. Using a normative legal research methodology, this study reviews existing laws such as Law No. 44 of 2008 on Pornography, Law No. 19 of 2016 on Electronic Information and Transactions, and the Criminal Code (KUHP). It applies legal analysis through the legislative approach and legal concept approach, identifying significant gaps in applying criminal sanctions to users of prostitution services. The findings highlight that while pimps and service providers are criminalized, service users remain largely exempt from legal accountability. The study proposes that service users can be prosecuted through adultery complaints as stipulated in Article 284 of the Criminal Code. These findings suggest the urgent need for legal reforms to address this gap, ensuring a more comprehensive legal approach to prostitution regulation.
Penerapan Deep Learning untuk Klasifikasi Buah Menggunakan Algoritma Convolutional Neural Network (CNN) Noris, Shandi; Waluyo, Adhi
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 1 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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Abstract

The fruit is the part of the plant that is embedded in the soil so that it grows large, fleshy and has a lot of water content. There are about 295,383 species of seed plants that can produce fruit. By utilizing artificial intelligence, especially deep learning, it will make it easier to classify fruit. In this study, researchers used the Convolutional Neural Network (CNN) algorithm with the MobileNetV1 architecture to produce a fruit classification model. The data used is the fruit dataset from the Kaggle platform, namely the fruit 360 dataset. The data consists of 10 types of fruit (Avocado, Apple, Orange, Lemon, Lime, Mango, Pineapple, Banana, Watermelon and Strawberry) with 4729 training images and 1586 image testing image with a size of 100×100 pixels which has been converted to a size of 224×224 pixels. The stages of this research started with preparing fruit image datasets, preprocessing datasets, namely resizing images, modeling the Convolutional Neural Network (CNN) architecture using the MobileNetV1 architecture. The results of this study can classify fruit into 10 classes into a model and labels, producing a fruit classification model with 100% accuracy in model testing of training data and 100% accuracy in model testing of data testing.
Co-Authors Noris, Shandi Sobandi, Sobandi Suandika, I Nyoman