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All Journal Komunikator Wikrama Parahita : Jurnal Pengabdian Masyarakat Tuturlogi: Journal of Southeast Asian Communication AKSIOMA : Jurnal Sains Ekonomi dan Edukasi
Argyanti, Talitha
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Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Strengthening Public Relations Practitioners' Capacity to Address Artificial Intelligence Challenges Wulandari, Maulina Pia; Wachid, Ivan Bimantoro; Argyanti, Talitha; Sasela, Mirel Imelda; Zuhri, Mochamad Fernanda Abuzar; Jukiabtari, Serly Novita; Taqi, Naila
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 9 No. 1 (2025): May 2025
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v9i1.9417

Abstract

The emergence of digital tools like artificial intelligence (AI) presents unique challenges to public relations practices, making it crucial for practitioners to understand these dynamics and strengthen their competencies for the digital transformation era. A Community Service Team conducted a "Workshop on Enhancing the Capacity of Public Relations Practitioners in Facing the Challenges and Threats of Artificial Intelligence (AI) in Digital Public Relations Practices" in Room 7.2, Building C, FISIP, Universitas Brawijaya, on Tuesday, August 20, 2024. This community service activity falls under problem-based, experiential, and real-world project-based learning methods, specifically Problem-Based Learning, in the form of training/workshops. Its primary objective is enhancing theoretical knowledge and strengthening foundational skills in utilizing AI to formulate effective digital PR strategies. The workshop underscores the critical need for PR professionals to enhance their digital literacy, particularly in AI, to remain competitive in an increasingly digital and data-driven environment.
Blind Buying Intention of Local Perfumes: An Indonesian Consumer Perspective Argyanti, Talitha; Hussein, Ananda Sabil; Oktaviani, Fitri Hariana
Tuturlogi: Journal of Southeast Asian Communication Vol 6, No 2 (2025): Tuturlogi: Journal of Southeast Asian Communication
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.tuturlogi.2025.006.02.2

Abstract

Perfume was one of the most sold products online in Indonesia and was predicted to continue growing each year. However, Indonesian consumers still tended to choose perfumes from long-established local and international brands available in offline stores. As a result, emerging local perfume brands that primarily focused on online sales faced great challenges in winning the competition. As a sensorial-based product with a high level of uncertainty, perfume was difficult to evaluate in online purchases since consumers could not try it beforehand. Using the Uncertainty Reduction Theory construct, this study examined how product descriptions, online reviews, and interactions with the seller influenced the blind buying intention of local perfumes online in Indonesia. This study used an explanatory quantitative approach with a survey method. A total of 306 respondents who had previously purchased local perfume online without trying it first were selected through purposive sampling. The results of multiple linear regression analysis indicated that product descriptions, online reviews, and interactions with the seller affected the intention to blind buy local perfumes online. 
Analisis Pemodelan Regresi Linear dengan Sebaran Distribusi Gamma: Hubungan antara Pendidikan, Kesehatan, dan Ekonomi Terhadap Indeks Pembangunan Manusia Nisa', Khoirun; Argyanti, Talitha
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 1 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/gspza867

Abstract

The Human Development Index (HDI) is a crucial indicator reflecting the quality of life in a region through three main dimensions: education, health, and economy. This study aims to analyze the relationship between education, health, and economic variables and HDI using linear regression modeling with a gamma distribution. The data used include Mean Years of Schooling (MYS), Life Expectancy (LE), and Poverty Rate (PR) as independent variables, with HDI as the dependent variable. The analysis evaluates the influence of each independent variable, including multicollinearity testing using Tolerance and Variance Inflation Factor (VIF) values. The results show that MYS and LE have a significant positive effect on HDI, while PR does not exhibit a significant impact. The regression model with a gamma distribution demonstrates good performance in capturing the relationship between the variables. This study provides an empirical basis for formulating more effective development policies to improve the quality of life.
Analisis Korelasi Variabel dan Pemodelan Regresi Non-linear Ketenagakerjaan Terhadap PDRB Provinsi Indonesia Tahun 2021 dengan GLM dan INLA Argyanti, Talitha
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 2 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/aksioma.v2i2.893

Abstract

Economic growth is a key indicator in assessing the welfare of a region, with Gross Regional Domestic Product (GRDP) serving as one of its primary measures. This study aims to analyze the influence of various factors on GRDP in 35 provinces of Indonesia using Generalized Linear Models (GLM) and Integrated Nested Laplace Approximation (INLA) approaches. The analyzed variables include Open Unemployment Rate (OUR), Crime Rate (CR), Poverty Rate (PR), Population (POP), and Human Development Index (HDI). The data were obtained from Indonesia's Central Bureau of Statistics (BPS) for 2021. GLM was selected to capture nonlinear relationships with Gamma distribution and log link function, while INLA was utilized to estimate model parameters using a Bayesian approach, accounting for spatial data structures. This study provides a foundation for policymakers to design more effective and data-driven economic development strategies.
Pemodelan Spasial: Analisis Pengaruh Indikator Sosio-Ekonomi terhadap Pesebaran Industri Kecil dan Mikro di Indonesia Harits, Jiyaad Muhamad; Argyanti, Talitha; Sianipar, Alexcandro Hibertus
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 2 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/aksioma.v2i2.917

Abstract

This study examines the influence of socio-economic indicators on the distribution of small and micro industries (SMI) in Indonesia using spatial modelling. The research employs a Bayesian approach with the Integrated Nested Laplace Approximation (INLA) method to analyse spatial dependencies and heterogeneity across regions. Data were obtained from the Central Bureau of Statistics (BPS), focusing on variables such as Gross Domestic Product (GDP), unemployment rate, Human Development Index (HDI), and poverty rate. The results indicate that HDI has a significant positive impact on the distribution of SMI, suggesting that improvements in education, health, and living standards foster the growth of small and micro enterprises. Spatial analysis reveals regional variations in SMI potential, with Yogyakarta, Gorontalo, and Maluku showing the highest relative potential. Conversely, regions like Papua and West Papua face significant challenges due to infrastructure and socio-economic limitations. The findings provide valuable insights for policymakers to design targeted interventions to support SMI development in different regions.
Online Blind Buying of Local Perfume: Reducing Uncertainty through Digital Cues Argyanti, Talitha; Ananda Sabil Hussein; Fitri Hariana Oktaviani
Komunikator Vol. 17 No. 2 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jkm.v17i2.27086

Abstract

Local perfumes have increasingly entered Indonesia’s e-commerce market, yet competition remains dominated by long-established local and global brands available in physical stores. New brands that rely mainly on online distribution face a significant challenge because perfumes are sensorial products that cannot be directly experienced prior to purchase, resulting in high product uncertainty. Drawing on Uncertainty Reduction Theory, this research investigates how marketplace and social media as digital platforms through product descriptions, online reviews, and interactions with the seller shape consumers’ intention to blind buy local perfumes online, while also examining the mediating role of perceived product uncertainty. A quantitative explanatory design was employed, using an online survey of 306 consumers with prior blind buying experience of local perfumes through PLS-SEM. The findings reveal that product descriptions and perceived product uncertainty significantly drive blind buying intention, whereas online reviews and interactions with the seller do not exert a direct effect. All three information cues significantly influence perceived product uncertainty, and mediation analysis indicates that seller interactions indirectly enhance blind buying intention via reduced perceived product uncertainty. These results extend the application of Uncertainty Reduction Theory by highlighting the mediating role of perceived product uncertainty in the context of online perfume purchases.  
Co-Authors Ananda Sabil Hussein Fitri Hariana Oktaviani Harits, Jiyaad Muhamad Jukiabtari, Serly Novita Maulina Pia Wulandari Nisa', Khoirun Oktaviani, Fitri Hariana Sasela, Mirel Imelda Sianipar, Alexcandro Hibertus Taqi, Naila Wachid, Ivan Bimantoro Zuhri, Mochamad Fernanda Abuzar