Article Per Year (5 Year)
p-Index From 2021 - 2026
4.441
P-Index
This Author published in this journals
All Journal Jurnal Pemikiran dan Pengembangan Sekolah Dasar (JP2SD) Jurnal Teknologi Informasi dan Ilmu Komputer Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Jurnal Akuntansi YUME : Journal of Management Atma Jaya Accounting Reseach (AJAR) Jurnal Akuntansi Barelang Widya Akuntansi dan Keuangan Jurnal Perseda : Jurnal Pendidikan Guru Sekolah Dasar Jurnal Buana Akuntansi Current : Jurnal Kajian Akuntansi dan Bisnis Terkini Paulus Journal of Accounting (PJA) Jurnal Ekonomi Bisnis, Manajemen dan Akuntansi (JEBMA) INVOICE : JURNAL ILMU AKUNTANSI Journal of Financial and Tax SITTAH: Journal of Primary Education Contemporary Journal on Business and Accounting Transforma: Jurnal Manajemen JUMBA Jurnal Manajemen, Bisnis, dan Akuntansi Jurnal Inovasi Akuntansi Journal of Community Empowerment Jurnal Ekualisasi Jurnal Ekonomi Bisnis, Manajemen dan Akuntansi Jurnal Balireso: Jurnal Pengabdian pada Masyarakat
Mardiana, Ana
Unknown Affiliation
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Social Sciences Other

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 34 Documents
Search

 1   2   3   4 
PENDAMPINGAN eSPT PPh 21 SESUAI UU No.7 (2021) PADA CV MAJU MAKMUR BERSAMA Holly, Anthony; Jao, Robert; Mardiana, Ana
Jurnal BALIRESO Vol 8, No 2 (2023)
Publisher : Lembaga Pengabdian kepada Masyarakat Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/balireso.v8i2.264

Abstract

CV Maju Makmur Bersama is a profit-oriented firm which holds a culinary Korean food franchisee. The employee of CV Maju Makmur Bersama is 20 persons who get various income. In line with the dynamic of tax, regulation changed over time. Following business conditions, CV Maju Makmur Bersama, as a taxpayer, needs to adjust its tax obligation activity, especially ini Income tax Article 21deduction. Law Number 7 of 2021, known as the Law of Harmonization of Tax Regulation, has changed some tax regulations, especially in Income Tax Article 21 in the progressive tax rate bracket stated in Income Tax Article 17, where before the new regulation had four brackets and changed to 5 brackets also changing in the first bracket interval from fifty million to sixty million rupiahs. This caused a firm must recount the tax deduction from employer to employees. Hence, the employees are not disappointed, and employers, as taxpayers, can do their obligation correctly according to current tax regulations. Therefore, servants accompany the firm partner in implementing tax regulation, especially implementing income tax article 21 as stated in law Number 7 of 2021.
Pengaruh Financial Leverage dan Operating Leverage terhadap Kinerja Keuangan Perusahaan Manufaktur di Bursa Efek Indonesia Holly, Anthony; Jao, Robert; Mardiana, Ana; Dayoh, Geraldy Frederick
Jurnal Inovasi Akuntansi (JIA) Vol. 3 No. 2 (2025)
Publisher : Program Studi Akuntansi Fakultas Ekonomi dan Bisnis Universitas Mahasaraswati Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36733/jia.v3i2.12457

Abstract

This research aims to investigate the effect of financial leverage and operating leverage on financial performance. The population used in this research is financial data from the manufacturing sector listed on the Indonesia Stock Exchange (BEI) with a research period of 2021-2023. This research uses secondary data. Sample selection was carried out using a purposive sampling method to obtain a total sample of 13 companies over 3 years. The data analysis method used is linear regression analysis.The research results show that financial leverage has a positive and significant effect on financial performance, operating leverage has a positive and significant effect on financial performance. The implication of this research is that for investors, the results of this research can contribute to investors as a source to see the development of company performance in the capital market and can be used as material for consideration in making investment decisions in the future. And for companies, the results of this research can be used as consideration in improving company performance to manage company reports better.
PENGARUH PENGHINDARAN PAJAK DAN RISIKO PAJAK TERHADAP BIAYA UTANG Holly, Anthony; Lukman; Jao, Robert; Mardiana, Ana; Kasim, Chelsea
Journal of Financial and Tax Vol. 6 No. 1 (2026): Journal Of Financial and Tax
Publisher : STIE Jambatan Bulan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52421/fintax.v6i1.671

Abstract

The purpose of this study is to analyze the effect of tax avoidance and tax risk on the cost of debt. This study is built with an agency theory approach. This study uses secondary data in the form of annual reports of manufacturing companies listed on the Indonesia Stock Exchange for the period 2022-2024. The number of samples is 108 company data for 3 years, which were selected using the purposive sampling method. The results of this study indicate that tax avoidance has a positive and significant effect on the cost of debt. However, tax risk has a positive but insignificant effect on the cost of debt.
Pengembangan Model IDS Berbasis Deep Reinforcement Learning untuk Prediksi dan Mitigasi Serangan Siber Dalam Network Traffic Analysis Martanto; Suarna, Nana; Kurnia Putri, Dede; Mardiana, Ana
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 3: Juni 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026133

Abstract

Intrusion Detection System (IDS) merupakan komponen krusial dalam pertahanan jaringan modern, berfungsi mendeteksi dan merespons ancaman siber secara cepat dan akurat. Penelitian ini menawarkan kontribusi baru melalui perancangan lingkungan Markov Decision Process (MDP) yang lebih realistis, integrasi reward shaping adaptif, serta evaluasi komprehensif multi-algoritma Deep Reinforcement Learning (DRL) yaitu Proximal Policy Optimization (PPO), Deep Q-Network (DQN), Advantage Actor-Critic (A2C) dan perbandingannya dengan model supervised learning mutakhir . Dataset CICIDS2017 dan UNSW-NB15 digunakan sebagai sumber data lalu lintas jaringan, mencakup berbagai jenis serangan dan lalu lintas normal. Lingkungan pelatihan dirancang khusus untuk memungkinkan agen DRL belajar melalui interaksi langsung dengan data, dengan reward function yang memandu agen untuk meningkatkan akurasi deteksi dan meminimalkan kesalahan. Metodologi penelitian meliputi perancangan arsitektur model DRL, proses pelatihan selama 200.000 time steps, serta evaluasi kinerja model berdasarkan metrik akurasi, presisi, recall, dan F1-score. Hasil evaluasi menunjukkan DQN mencapai akurasi tertinggi pada pendekatan DRL (89–92%), namun secara keseluruhan model supervised learning seperti Random Forest dan CNN masih melampaui DRL dengan akurasi 98–99%. Temuan ini mengonfirmasi bahwa DRL memiliki potensi kuat dalam adaptasi dinamis, tetapi masih memerlukan optimasi lebih lanjut untuk menyaingi metode supervised pada klasifikasi statis. Penelitian ini juga menghadirkan blueprint integrasi IDS–DRL dengan SOC dan firewall adaptif, yang memberikan landasan implementatif pada sistem keamanan nyata. Penelitian ini berkontribusi pada pengembangan IDS adaptif yang mampu melakukan deteksi dan mitigasi secara real-time dengan tingkat akurasi tinggi. Keterbatasan penelitian mencakup kebutuhan komputasi yang tinggi dan potensi ketidakstabilan pelatihan, yang membuka peluang untuk penelitian lanjutan dengan optimasi arsitektur dan integrasi teknik transfer learning.   Abstract An Intrusion Detection System (IDS) is a crucial component of modern network defense, detecting and responding to cyber threats quickly and accurately. This research proposes the development of a Deep Reinforcement Learning (DRL)-based IDS for cyberattack prediction and mitigation using three main algorithms, namely Proximal Policy Optimization (PPO), Deep Q-Network (DQN), and Advantage Actor-Critic (A2C). The CICIDS2017 dataset is used as a source of network traffic data, covering various types of attacks and normal traffic. The training environment is specifically designed to allow DRL agents to learn through direct interaction with the data, with a reward function that guides the agent to improve detection accuracy and minimize errors. The research methodology includes designing the DRL model architecture, training for 20,000 time steps, and evaluating model performance based on accuracy, precision, recall, and F1-score metrics. The experimental results show that DQN has the best performance with an accuracy of 92.39%, a precision of 91.04%, a recall of 92.39%, and an F1-score of 91.50%, followed by A2C and PPO. Confusion matrix analysis and performance visualization show that DQN excels in detecting majority and minority classes with a low number of false positives and false negatives. Theoretical discussions link the results of this study to the fundamental principles of DRL, where agents learn adaptive detection strategies to attack dynamics, and their relevance to real-world applications such as Security Operation Centers (SOCs) and adaptive firewalls. Comparisons with previous research confirm that the DRL approach can offer significant improvements over traditional IDS and supervised learning methods. This research contributes to the development of an adaptive IDS capable of real-time detection and mitigation with high accuracy. Limitations include high computational requirements and potential training instability, which opens up opportunities for further research with architecture optimization and the integration of transfer learning techniques.
Co-Authors Agung Putra Anthony Holly Atmakusuma, Cheryl Natasya Azali, Lia Bilal, Arpan Islami Bunga, Yulisna Daromes, Fransiskus. E. Dayoh, Geraldy Frederick Dera, Jingga Azaria Yasi dina, nur edi edi Fauzan . Fransiskus Eduardus Daromes Gunawan, Emylia Kusuma H.M Lubis, Patricia Hogianto, Marselinus Adry Holly, Anthony Ida Ida Suryani, Ida Ifriqia, Fartika Kampo, Kunradus Kasim, Chelsea Kresensia, Vince Kurnia Putri, Dede Kusuma, Wilson Limbok, Jeni Tiktania Laurensa Limbunan, Excel Lukman LUKMAN, LUKMAN Mario Oktavianus, Mario Martanto Mas’amah, Mas’amah Muzakki, Imron Nontji, Meifilia Nurin Rochayati Ottong, Ervina Patandianan, Tripentita Loto Patricia Rahayu, Rian Sri Robert Jao Salma Sunaiyah, Salma Sambur, Sindi Claudia Sar'i, Muhammad Sirajuddin Sirajuddin Siti Sanisah Sri Rejeki Suarna, Nana Suwandi Ng Tandiamal, Fritzline Geralda Tangke, Paulus Tjiang Y. Suryady, Ardi Tuwo, Lukman Yunus Abidin