Meli Siagawati
Politeknik Lembaga Pendidikan Dan Pengembangan Profesi Indonesia, Bandung, Indonesia

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Identification of HR management best practices in marketing tourism production and services: scientific proof of progress in tourism destinations in several provinces in Indonesia Faqih Nabhan; B.M.A.S. Anaconda Bangkara; Sri Sugiarti; Laros Tuhuteru; Meli Siagawati
Enrichment : Journal of Management Vol. 13 No. 1 (2023): April: Management Science And Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/enrichment.v13i1.1211

Abstract

Finding best practices in human resource management, especially in advancing global tourism, both services and goods, is an exciting topic, mainly when much scientific evidence has been investigated in various advanced provinces in the tourism industry. To obtain valid data to support this research question, we collect several publications which are scientific evidence in the field and analyze them using a phenomenological approach which includes, among others, in-depth data coding systems, in-depth evaluation, and data synthesis and interpretation to obtain valid findings to answer the research problem. We electronically scoured many literary data sources for our data. Next, we made a descriptive qualitative report, in which we looked at various points of view with findings including that the key to tourism success, as in several provinces in Indonesia, lies in the skills and excellence of government and private human resources in managing tourism to make their province the best tourist destination. Those are some reviews from various studies that are scientific evidence to answer this study question. Hopefully useful for further studies.
UNDERSTANDING AI-DRIVEN INFLUENCER MARKETING Adi Mursalin; Yuli Purbaningsih; Surya Fadjar Boediman; Meli Siagawati; Rainier Hendrik Sitaniapessy
INTERNATIONAL JOURNAL OF HUMANITIES, SOCIAL SCIENCES AND BUSINESS (INJOSS) Vol. 2 No. 3 (2023): SEPTEMBER
Publisher : ADISAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/injoss.v2i3.90

Abstract

AI-driven influencer marketing has emerged as a transformative approach in the digital advertising landscape. This research aimed to explore the efficiency and effectiveness of AI integration in influencer marketing campaigns, comparing it to traditional methods. By employing a mixed-methods approach, including qualitative interviews and quantitative data analysis, the study investigated the impact of AI on influencer selection, campaign performance, and ethical considerations. The findings revealed that AI-driven influencer selection processes significantly outperformed manual methods' accuracy and efficiency. AI algorithms effectively matched influencers with target audiences, increasing engagement rates and brand visibility. The real-time analytics provided by AI tools enabled marketers to make data-driven decisions and optimize campaign strategies on-the-fly. Moreover, AI-optimized influencer campaigns consistently surpassed traditional campaigns in metrics such as reach, impressions, and ROI. The data-backed approach of AI led to more targeted and relevant campaigns, resonating better with the audience and yielding tangible results for businesses. However, ethical considerations regarding algorithmic biases were identified as crucial aspects of AI-driven influencer marketing. Transparent practices and ongoing audits of AI algorithms were emphasized to mitigate biases and ensure ethical influencer selections. Looking ahead, the future of AI for influencer marketing appears promising. Advancements in AI algorithms will lead to even more accurate influencer matches and sophisticated audience insights, fostering hyper-personalized campaigns. By embracing AI technologies responsibly, businesses can connect with their target audiences more effectively and stay ahead in the dynamic realm of digital advertising.