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All Journal Jurnal Ekonomi Manajemen Sistem Informasi Indonesian Journal of Social Work Supremasi Hukum
Aji Pangestu, Ilham
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Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Social Sciences

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PROBLEMATIKA PENEGAKAN INSIDER TRADING DALAM PRAKTIK PASAR MODAL DI INDONESIA Aji Pangestu, Ilham; Thorik, Achmad; Yulviani, Dian; Rizqi Fadhlillah, Muhammad
SUPREMASI HUKUM Vol. 20 No. 02 (2024): Supremasi Hukum
Publisher : Fakultas Hukum Universitas Islam Syekh Yusuf

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Abstract

This research aims to identify and analyze the problems of insider trading in capital market practices in Indonesia. This research is normative legal research. Legal materials consist of primary and secondary legal materials obtained through literature study. The approach used includes a statutory regulatory approach. Based on the results of the discussion, it is known that first, Law Number 8 of 1995 concerning Capital Markets (UUPM) still has several weaknesses. Article 95 does not explain who is meant as an employee of the issuer. Apart from that, UUPM has a legal loophole to reach insider trading which is based on misuse of information to carry out transactions. UUPM only regulates insider trading that occurs as a result of violations of obligations. Second, the law enforcement process for insider trading violators in Indonesia is still considered very weak. Third, POJK Disgorgement is one of the government's efforts to deal with insider trading. These efforts include examination, investigation, evidence, dispute resolution, and imposition of sanctions. Researchers provide suggestions including, first, strengthening the role of OJK in terms of supervision. Second, the formation of a special unit consisting of several institutions to handle and resolve insider trading practices so that they are effective and efficient. Third, increasing understanding and education related to POJK Disgorgement in the community. Keywords: Problems; Insider Trading; Capital Market    
Industrial Expansion: Sebagai Komitmen G20 Dalam Mengentaskan Kemiskinan di Negara Berkembang Aji Pangestu, Ilham; Sofia Latif, Inas; Nurul Fauzyah, Rizgita; Yulviani, Dian
Indonesian Journal of Social Work Vol 7 No 1 (2023): August 2023
Publisher : Politeknik Kesejahteraan Sosial Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31595/ijsw.v7i1.731

Abstract

Poverty is one of the most common problems in every country. The achievement of the Millennium Development Goals (MDGs) regarding the eradication of poverty is indeed indicated to have made good progress. Nevertheless, poverty alleviation remains one of the core agendas for the implementation of the Sustainable Development Goals (SDGs). As a form of contribution to the SDGs, the G20 is expected to have strategies related to poverty alleviation. This study aims to examine and discuss the concept of joint industrial expansion as a solution to the G20 in poverty alleviation in developing countries. The method used in this study is a literature review with conceptual review techniques and a qualitative approach. The results showed that the concept of joint industrial expansion is a concept where developed countries and developing countries that are members of the G20 work together to expand industries that previously existed or have been running in developed countries to be applied in developing countries while still making adjustments to the potential of member countries. It can also be done by building a new industry by looking at the potential of the place where the industry will be built. Therefore, all G20 member countries and all relevant parties must work together in the implementation of joint industrial expansion, so that the results obtained are appropriate and can reduce poverty in developing countries.
Implementasi Algoritma Convolutional Neural Network (CNN) Dalam Mendeteksi Berita Hoaks Pada Media Social Aji Pangestu, Ilham; Saprudin, Saprudin
Jurnal Ekonomi Manajemen Sistem Informasi Vol. 7 No. 2 (2025): Jurnal Ekonomi Manajemen Sistem Informasi (November-Desember 2025)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jemsi.v7i2.6993

Abstract

Penyebaran berita palsu (hoaks) di media sosial semakin meningkat dan berdampak negatif terhadap masyarakat, mulai dari menimbulkan kebingungan hingga mengganggu stabilitas sosial. Penelitian ini bertujuan untuk membangun sistem deteksi berita hoaks berbasis Convolutional Neural Network (CNN) dengan menggunakan data komentar dari platform X (Twitter). Data yang terkumpul berjumlah 5.534 komentar, yang setelah tahap preprocessing menghasilkan 4.117 komentar . Proses pelabelan menunjukkan bahwa mayoritas data termasuk kategori hoaks (88,05%). Data kemudian dibagi menjadi data latih dan uji untuk pengembangan model CNN. Hasil evaluasi menunjukkan performa dengan akurasi 88,2%, precision 91,8%, recall 95,2%, serta F1-score 93,4%. Selain itu, model ini berhasil diimplementasikan ke dalam aplikasi web berbasis Gradio. Penelitian ini membuktikan bahwa CNN efektif dalam mengklasifikasi berita hoaks berbasis teks dan dapat digunakan untuk meningkatkan keakuratan identifikasi dalam berita hoaks.
Co-Authors Inas Sofia Latif Nurul Fauzyah, Rizgita Rizqi Fadhlillah, Muhammad Saprudin Saprudin, Saprudin Thorik, Achmad Yulviani, Dian