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All Journal Journal Of Human And Education (JAHE) Dinamika Jurnal Ilmiah Ekonomika & Sains Journal of Economics and Public Health Jurnal Ilmiah Sistem Informasi
Qosidah, Nanik
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Audit Judgmen? Kompleksitas Tugas dan Tekanan Ketaatan Auditor Kantor Akuntan Publik di Semarang Sudarman, Sudarman; Wahyuningsih, Endang Dwi; Qosidah, Nanik
Jurnal Ilmiah Ekonomika & Sains Vol 1 No 1 (2020): JIESA: Jurnal Ilmiah Ekonomika & Sains: Mei 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) - Institut Teknologi dan Bisnis (ITB) Semarang

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Abstract

Penelitian bertujuan untuk menguji kompleksitas tugas dan tekanan ketaatan terhadap audit judgment. Desain penelitian menggunakan penelitian deskriptif eksploratif, dimana hasil penelitian digunakan untuk mengungkap kejadian-kejadian yang terjadi atau fenomena penelitian di objek penelitian. Sumber data menggunakan data primer yaitu dari jawaban responden melalui kuesioner tertutup. Sampel penelitian yaitu akuntan yang bekerja di Kantor Akuntan Publik yang ada di Semarang dan berjumlah 147 responden. Teknik pengambilan sampel menggunakan purposive sampling. Hasil penelitian menjelaskan bahwa kompleksitas tugas berkontribusi meningkatkan audit judgment dan tekanan ketaatan juga berkontribusi untuk meningkatkan audit judgment. Hal ini membuktikan jika kompleksitas tugas merupakan peran untuk meningkatkan audit. Tekanan ketaatan juga mempunyai peran meningkatkan audit judgment.
Keahlian dan Tekanan Ketaatan terhadap Audit Judgment pada Auditor Akuntan Publik di Semarang Wahyuningsih, Endang Dwi; Krisnawati, Hani; Qosidah, Nanik; Aniqotunnafiah, Aniqotunnafiah
Jurnal Ilmiah Ekonomika & Sains Vol 1 No 1 (2020): JIESA: Jurnal Ilmiah Ekonomika & Sains: Mei 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) - Institut Teknologi dan Bisnis (ITB) Semarang

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Tujuan dari penelitian yaitu menganalisis keahlian dan tekanan ketaatan terhadap audit judgment. Desain penelitian ini menggunakan penelitian ekploratif dengan menggunakan data primer dan data skunder. Sampel penelitian yaitu akuntan yang bekerja di Kantor Akuntan Publik di Semarang yang berjumlah 147 responden. Hasil penelitian menjelaskan bahwa keahlian meningkatkan audit judgment. Tekanan ketaatan memberikan kontribusi peningkatan audit judgment secara siginifikan. Hal ini membuktikan bahwa akuntan lebih dipercaya oleh klien karena pengalaman, selain itu tekanan ketaatan memiliki peran untuk meningkatkan secara keseluruhan.
Integrity Moderates the Relationship between Work Experience and Tax Inspector Performance at the Intermediate Tax Service Office Within the Regional Office of the Directorate General of Taxes of Central Java I Qosidah, Nanik; Husnurrosyidah, Husnurrosyidah
Journal of Economics and Public Health Vol 1 No 3 (2022): Journal of Economics and Public Health: September 2022
Publisher : Global Health Science Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/jeph.v1i3.1337

Abstract

The purpose of the study is toanalyze the effect of work experience on the performance of tax inspectors. Analyzing the integrity of moderating work experience to the performance of tax inspectors. The research design used Multiple Regression Analysis (MRA). The research sample was a tax inspector at the Associate Tax Service Office in the Regional Office of the Directorate General of Taxes of Central Jaw I, which totaled 60 respondents. The results of the study explained that work experience contributes to improving the performance of tax inspectors, integrity strengthens the relationship between work experience and tax inspector performance.
Pelatihan Teknik Pembuatan Konten Menarik dan Informatif Untuk Media Sosial Bagi Penggiat Literasi Digital Desa Gladagsari, Boyolali Dewi, Maya Utami; Nugroho, Aris Sarwo; Kholifah, Siti; Siswanto, Siswanto; Sumaryanto, Sumaryanto; Fitrianto, Yuli; Qosidah, Nanik; Nurmana, Ayyub Hamdanu Budi; Supriadi, Candra; Imaliya, Tri
Journal Of Human And Education (JAHE) Vol. 5 No. 1 (2025): Journal of Human And Education (JAHE)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v5i1.2131

Abstract

In this increasingly advanced digital era, social media has become the leading platform for many individuals and organizations to convey messages and information to a broad audience. The training activity on interesting and informative content creation techniques for social media for digital literacy activists in Gladagsari Village, Boyolali, aims to equip participants with the knowledge and skills needed to create content that not only attracts attention but also provides high informative value and relevance. Good content is not only able to attract the attention of the audience but is also able to convey messages clearly and increase interaction and engagement. This training was attended by 15 participants and was held in Gondang Village, Ampel District, Boyolali Regency. The training uses theoretical and practical delivery techniques. The training material focuses on creating interesting and innovative content for social media platforms with copywriting techniques. The results of the training showed satisfactory results with an increase in participants' ability to create content on social media with a value of 78%, which is included in the good category.
BUILDING RESILIENCE THROUGH AI: PREDICTIVE ANALYTICS FOR SUPPLY CHAIN RISK MANAGEMENT IN THE POST-COVID GLOBAL MARKET Henny, Henny; Qosidah, Nanik; Wardi, Agustinus
Dinamika: Jurnal Manajemen Sosial Ekonomi Vol. 5 No. 1 (2025): DINAMIKA : Jurnal Manajemen Sosial Ekonomi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/c44y6a86

Abstract

The COVID-19 pandemic has exposed fundamental vulnerabilities in global supply chain systems, such as over-reliance on single suppliers and a lack of operational visibility. This has highlighted the urgent need for a new approach to risk management—one that leverages smart technologies. Artificial Intelligence (AI) has emerged as a promising solution, thanks to its capabilities in predictive analytics and adaptive, data-driven decision-making in real time. This study aims to develop an AI-based predictive system framework to enhance the resilience of global supply chains in the face of post-pandemic disruptions. Using the Design Science Research (DSR) methodology, the research designs and evaluates a system that integrates algorithms such as LSTM, Random Forest, Natural Language Processing (NLP), and Reinforcement Learning. It also applies a federated learning approach to ensure data privacy among supply chain partners. The study analyzes over 12,000 data entries from diverse sources, including IoT devices, weather data, demand trends, and social media. The system's effectiveness is evaluated through a combination of quantitative methods (PLS-SEM analysis on 103 respondents) and qualitative methods (interviews with 12 industry executives). The findings show that AI-driven predictive analytics significantly improve supply chain resilience (β = 0.67; p < 0.001), with demand forecasting accuracy increasing by up to 40% and delivery times reduced by 30%. Conceptually, the study contributes by designing a resilient model that integrates real-time visibility, adaptability, and cross-organizational collaborative learning. Unlike traditional approaches focused solely on automation, this framework offers a more holistic solution, addressing key gaps in the literature. The implication is clear: AI is becoming a strategic asset in building sustainable, resilient supply chains amid ongoing global uncertainty.
Systematic Literature Review: Energy Metrics, Trade-Offs, and Best Practices in Green IT and Green Software Qosidah, Nanik
Jurnal Ilmiah Sistem Informasi Vol. 4 No. 1 (2025): Januari : Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/zezhdt51

Abstract

The rapid growth of information technology, including cloud computing, the Internet of Things, and artificial intelligence, is driving increased energy consumption and carbon emissions in the technology sector. A report by the International Energy Agency (IEA) projects that global data center electricity consumption will more than double, reaching approximately 945 TWh by 2030, or about 3% of global electricity consumption. A Deloitte study even estimates that data centers could contribute around 4% by 2030, primarily driven by the growing use of artificial intelligence. Beside physical infrastructure, software also significantly contributes to energy consumption, necessitating Green IT and Green Software approaches to reduce environmental impact. This research aims to identify and classify energy metrics used in the literature, analyze the trade-offs between energy consumption and system performance, and summarize relevant best practices for application in industrial settings. This research uses the Systematic Literature Review (SLR) method, referring to the Kitchenham protocol. The search was conducted on the IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, and arXiv databases for articles published between 2021 and 2025 that included empirical data or conceptual models related to the energy efficiency of information systems. From the screening process, a number of articles were obtained and analyzed thematically. The research results show that energy metrics vary from hardware-based measurements (power meter) to estimation models (GSMM, GSMP). A trade-off was also found between energy savings and performance, necessitating a multi-objective optimization approach. This research contributes by providing a framework for classifying energy metrics, visualizing measurement method trends, and offering methodological recommendations that can be integrated into industrial practice. The implications of this research are to support digital sustainability efforts while simultaneously reducing the organization's operational costs.
Co-Authors Aniqotunnafiah, Aniqotunnafiah Henny Henny, Henny Husnurrosyidah, Husnurrosyidah Imaliya, Tri Krisnawati, Hani Maya Utami Dewi, Maya Utami Nugroho, Aris Sarwo Nurmana, Ayyub Hamdanu Budi S Siswanto SITI KHOLIFAH Sudarman Sudarman Sumaryanto Sumaryanto, Sumaryanto Supriadi, Candra Wahyuningsih, Endang Dwi Wardi, Agustinus Yuli Fitrianto