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AI-Powered HR: Ethical and Strategic Analysis of Artificial Intelligence Implementation in Recruitment Process in Indonesia Zidnal Falah; Fajar Syaifurrochman; Saeful Anwar; Riska Anggraeni
Journal of Village Development Innovation Vol. 2 No. 1 (2025): Journal of Village Development Innovation
Publisher : Journal of Village Development Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jvdi.v2i1.11

Abstract

The development of artificial intelligence (AI) in the human resources (HR) sector, particularly in recruitment, is accelerating, including in Indonesia. The implementation of AI in the recruitment process offers great potential in terms of efficiency and reduction of human bias, but also raises ethical and strategic challenges. Therefore, it is important to understand how AI is applied in recruitment and its impact on the selection process and company decisions. This study aims to analyze the implementation of AI in the recruitment process in Indonesia, identify the ethical challenges that arise, and provide strategic recommendations for the effective and fair use of this technology. This study used a descriptive mixed-methods approach, which included in-depth interviews with HR managers and relevant staff as well as a survey of employees who have gone through AI-based recruitment. The data obtained was analyzed using thematic analysis techniques for qualitative data and descriptive statistics for quantitative data. The results show that although AI improves the efficiency of the recruitment process, many companies in Indonesia still face challenges related to the transparency of AI decisions and potential bias. Most companies use AI only in the early stages of selection, with the final decision still involving humans. The application of AI in recruitment in Indonesia can improve efficiency, but companies must pay more attention to ethics and transparency to ensure that this technology is used fairly. A hybrid approach that combines technology with human evaluation may be the best solution.
Analyzing Pricing Strategy in Competitive E-Commerce Ecosystem Like Tokopedia and Shopee Riska Anggraeni; Nur Saebah; Dina Nurul Fathiya
Journal of Strategic Marketing and Applied Economics Vol. 1 No. 2 (2025): Journal of Strategic Marketing and Applied Economics
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jsmae.v1i2.9

Abstract

The rapid growth of e- commerce in Indonesia has created a highly competitive business environment, with Tokopedia and Shopee becoming the two dominant platforms. Price competition has become a key strategy to attract price- and promotion-sensitive digital consumers. However, the pricing dynamics between these two platforms have not been comprehensively studied, particularly in the context of long-term strategies and their impact on customer loyalty. This study aims to analyze the pricing strategies implemented by Tokopedia and Shopee in their efforts to maintain and increase their market share. The research method used was a descriptive qualitative approach with a case study technique. Data were collected through in-depth interviews with active business owners on both platforms, analysis of price promotion content from 2023 to 2024, and observation of secondary data from e- commerce industry reports . The results show that both platforms rely on deep discount strategies, shipping subsidies, and automatic price adjustment algorithms to maintain competitiveness. Shopee tends to be more aggressive in loyalty programs and price campaigns, while Tokopedia places greater emphasis on financial services integration as an added value. Dynamic pricing strategies have proven effective in increasing short-term transactions, but present sustainability challenges for small businesses. This research contributes to the understanding of digital marketing strategies and offers practical implications for MSMEs and policy makers in designing fair e- commerce regulations.