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All Journal Jurnal Manajemen dan Agribisnis Jurnal Teknik Industri Autotech: Jurnal Pendidikan Teknik Otomotif Universitas Muhammadiyah Purworejo Media Gizi Mikro Indonesia ENGINEERING Elkom: Jurnal Elektronika dan Komputer JPBM (Jurnal Pendidikan Bisnis dan Manajemen) IJHCM (International Journal of Human Capital Management) Jurnal Pendidikan Ekonomi & Bisnis Majalah Ilmiah Biologi BIOSFERA: A Scientific Journal Psikodidaktika: Jurnal Ilmu Pendidikan, Psikologi, Bimbingan dan Konseling Jurnal Lentera Pendidikan Pusat Penelitian LPPM UM Metro Social, Humanities, and Educational Studies (SHEs): Conference Series Jurnal Teknologi Informasi dan Komunikasi Jurnal Perspektif MANAJEMEN Journal Equity of Law and Governance Jurnal Kolaboratif Sains Jurnal Pengabdian Kepada Masyarakat Abdi Putra Volksgeist: Jurnal Ilmu Hukum dan Konstitusi INFORMATIKA Journal of Innovation Research and Knowledge Jurnal Suara Pengabdian 45 ASEAN Journal of Empowering Community Jurnal Hukum, Politik dan Ilmu Sosial (JHPIS) JURNAL AKUNTANSI DAN BISNIS Jurnal Publikasi Ilmu Manajemen JURNAL ABDIMAS PLJ Seminar Nasional Teknologi dan Multidisiplin Ilmu Tadzkirah: Jurnal Pendidikan Dasar Mimbar Administrasi Jurnal Intelek Insan Cendikia PENG: Jurnal Ekonomi dan Manajemen Jurnal Ekonomi, Manajemen, Akuntansi Penelitian Gizi dan Makanan (The Journal of Nutrition and Food Research) Journal of Digital Business and Global Economy Sinergi : Jurnal Ilmiah Multidisiplin Jurnal Ilmiah Literasi Indonesia
Agus Wibowo
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Journal : MANAJEMEN

 1 
Enhancing Critical Thinking in Business Education through AI-Assisted Learning of Value-Based Pricing Fahyuda Rammadan; Agus Wibowo
MANAJEMEN Vol. 5 No. 1 (2025): MEI : MANAJEMEN (Jurnal Ilmiah Manajemen dan Kewirausahaan)
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/manajemen.v5i1.952

Abstract

The development of Artificial Intelligence (AI) has brought a significant impact in various fields, including pricing strategies. Value-Based Pricing as an approach that focuses on the perception of customer value is now increasingly optimized through the integration of AI technology. The study aims to explore how AI can support value-based decision-making through complex data processing and predictive analytics, as well as how critical thinking skills remain a key competency in interpreting results and establishing sustainable pricing strategies. This approach emphasizes the importance of synergy between technological sophistication and human cognition, in order to produce decisions that are not only efficient but also ethical and value-oriented in the long term. The results of this study show that the application of AI in Value-Based Pricing can improve the accuracy and speed of analysis, but still requires an active role of critical thinking in the context of interpretation and strategic decision-making.
Enhancing Fairness in HR Recruitment: A Hybrid AI-DSS Model vs. Traditional Methods Evaluated with DIR and EOD Metrics for Effective Recruitment Isna Eny Putri S; Agus Wibowo
MANAJEMEN Vol. 5 No. 1 (2025): MEI : MANAJEMEN (Jurnal Ilmiah Manajemen dan Kewirausahaan)
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/manajemen.v5i1.960

Abstract

The implementation of Artificial Intelligence-based Decision Support Systems (AI-DSS) in recruitment has significantly enhanced efficiency; however, concerns regarding algorithmic bias persist. Existing AI-DSS models primarily emphasize explicit data, often neglecting psychological and behavioral factors essential for fair recruitment. This study integrates Person-Job Fit and Person-Organization Fit theories into AI-DSS while employing adaptive learning techniques to mitigate bias. Using a mixed- methods approach with an explanatory sequential design, this research combines quantitative analysis (statistical comparisons of AI-DSS and traditional hiring methods, bias evaluation using fairness metrics) with qualitative insights (interviews with HR professionals and candidates). The findings indicate that AI-DSS improves selection efficiency and candidate performance yet remains susceptible to biases derived from historical data. Adaptive learning enhances fairness; however, ethical concerns about transparency and accountability persist. This research strengthens the AI recruitment debate by suggesting a comprehensive model that balances the operational efficiency, ethical needs, and fair practices. Explaining AI paradigms requires additional research to establish trust and flexibility for AI recruitment systems.
The Role of Social Media in Driving Community Innovation: A Mixed-Methods Study on Challenges and Opportunities in the Digital Age Jap Caroline Valencia; Agus Wibowo
MANAJEMEN Vol. 5 No. 1 (2025): MEI : MANAJEMEN (Jurnal Ilmiah Manajemen dan Kewirausahaan)
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/manajemen.v5i1.961

Abstract

Social media has increasingly become a driving force for community innovation in cyberspace. Platforms such as Facebook, WhatsApp, Instagram, and TikTok have empowered individuals and groups worldwide to collaborate, share ideas, and innovate collectively. However, despite these opportunities, social media also presents significant challenges, including misinformation, algorithmic bias, and issues surrounding trust and privacy. Utilizing a mixed- methods research approach, this study combines quantitative surveys and qualitative interviews to assess the impact of social media on community innovation. Data will be analyzed using descriptive statistics and thematic analysis to understand engagement, collaboration patterns, and the challenges faced by users. The study aims to contribute to existing research by providing insights into how social media platforms can be optimized for innovation and what strategies can be employed to overcome the digital divide and algorithmic biases. This study finds social media significantly enhances community innovation, with surveys indicating 95% faster collaboration, 100% idea generation efficiency, and 90% solution implementation post- adoption. Persistent challenges include misinformation (84% agreement), algorithmic bias limiting diversity (90%), and access gaps excluding marginalized groups (87%). Mixed- methods data reveal a paradox: platforms democratize innovation yet perpetuate inequities. Opportunities emerge in algorithmic transparency (80% agreement) and policy-driven digital inclusion (78%). Reforms prioritizing ethical governance, transparent AI, and inclusive infrastructure are critical to equitably harness social media’s potential as a global innovation catalyst.
Strategi Pemasaran Produk berbasis AI Analisis Efektifitas dan Hambatan dengan Mix method Khana Amelia; Agus Wibowo
MANAJEMEN Vol. 5 No. 2 (2025): Oktober : MANAJEMEN (Jurnal Ilmiah Manajemen dan Kewirausahaan)
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/manajemen.v5i2.1020

Abstract

In the era of digital transformation, the implementation of Artificial Intelligence (AI) in product marketing strategies has become an essential need for companies to understand consumer behavior, personalize campaigns, and improve operational efficiency. Although AI offers a competitive advantage, there are still challenges in adopting this technology, such as limited competence, high costs, and data privacy issues. This study aims to analyze the effectiveness of AI utilization in product marketing strategies and to explore the obstacles encountered through a concurrent mixed-method approach. Quantitative data were collected through Likert-scale questionnaires distributed to 150 respondents from various business sectors, while qualitative data were obtained from semi-structured interviews with 15 business practitioners who use AI. The research findings show that 82% of respondents acknowledged an increase in marketing effectiveness through AI, with an average effectiveness score of 4.2 out of 5. Content personalization (77%) and predictive analytics (70%) were identified as dominant factors that enhance customer engagement and marketing decision-making. However, 35% of respondents pointed out high initial investment costs as the main obstacle. The qualitative findings reinforce that AI provides benefits in promotional personalization, customer service automation, and data analysis accuracy. Nevertheless, its adoption remains hindered by limitations in human resources, high development costs, data privacy issues, and suboptimal internal system integration. This study concludes that AI has significant potential to enhance product marketing effectiveness; however, its successful implementation greatly depends on the company’s internal readiness and compliance with existing regulations.
Co-Authors A. Farid Abdul Syarif Achmad Ali Chafid Ade Aprilia Sasi Lestari Adi Suryo Ramadhan Adine Setya Wardhani ADITYA PRATAMA Agus Widodo Ahmad Farid Ahmad Rouf Amirin Amna Anggraeni Endah Kusumaningrum Annisa Sativa Aribandi Bambang wido kristanto Bangun Muljo Sukojo Budi Johan Budi Santoso Catur Wijayanti Cicik Harfana Cusanto Aji Aji Dian Ikha Pramayanti Dian Ratnasari Dicky Iranto Edi Pranoto Efrat Tegris Eka Ahadiyat Suryana Eko Hadisiswanto Endah K, Anggraeni Endang Swastuti Ernani Budi Prihatmi Fahyuda Rammadan Fitra Dila Lestari Galuh Juniarto Gulo, Sabina Berlina Gunawan . Hadi Pranoto Hadi Wibowo Hamzah Mardiansyah Imron Rosadi Ina Kusrini Indah Eko Cahyani Indra Fahrizal Ira Mariyah Ulfah Irfan Santosa Irfan Santoso irsan hadi Ismi Setianingsih Isna Eny Putri S Jap Caroline Valencia Jefrie Ardian Pratama Joni Laksito Jumail Karuniana Dianta Arfiando Sebayang Kastubi Khana Amelia Khoirunni’mah Kudang B. Seminar Kunarto Kurnia Kurnia Turrahmi Lagiyono . Lawrence Adi Supriyono M. Agus Shidiq M. Riyanto Marita Nurharjanti Markus Suryo U Markus Suryo Utomo Markus Suryoutomo Marsofiyati Marsofiyati Mashari Moh. Ade Purwanto Moh. Yusuf Abadi Mohamad Samsudin Mohammad Abousaidi Muhammad Agus Shidiq Muhammad Turmudzi Mustaqim , Mustaqim . Mustaqim mr Nabilla Ekariyana Mursita Nafisah Nuraini Narto Narto Ninik Umi Hartanti Nirma Hellyatul Auwalia Nur Asiyatul Janah Nur Tulus Ujianto Nurul Atieka Oscar, Oscar Haris Palupi Dyah Ayuni Prawiro Anggianto Purwana E.S., Dedi Rahmad Purwanto W Restian Khafi Nurhendi Retno Mawarini Sukmariningsih Rika Ampuh Hadiguna Rizki Fajarudin Rizki Prasetyo Tulodo Rossa Azwa Damayanti Rosyidah Jayanti Vijaya RR Widyorini Indrasti W Rr. Widyorini Indriasti W Sadah, Khozinatus Saepul Bahri Sandya Gilang Samudra Shofiyatul Hidayah Siti Mariam Siti Mariyam Siti Rohimah Sri Jumini Sri Mulyani Sri Nuryani Wahyuningrum Sudarinah Sudarinah Suparno Suryati Kumorowulan Susbiyantoro, Susbiyantoro Suswanto . Suyono Suyono Tofik Hidayat Untung Hartoni Viona Galanita Windi Puji Ariani Yasin , Yudi Widodo Yusuf Ibrahim Arowosaiye Zaenal Supriyadi Zulfah .