Maria Zefanya Sampe
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Predictive Analysis of Employee Loyalty: A Comparative Study Using Logistic Regression Model and Artificial Neural Network Sampe, Maria Zefanya; Ariawan, Eko; Ariawan, I Wayan
Journal of the Indonesian Mathematical Society Volume 25 Number 3 (November 2019)
Publisher : IndoMS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jims.25.3.825.325-335

Abstract

Employee turnover is a common issue in any company. A high turnover phenomenon becomes a big problem that will certainly affect the performance of the company. Therefore, measuring employee turnover can be helpful to employers to improve employee retention rates and give them a head start on turnover. A study to analyze for employee loyalty has been carried out by using Logistic Regression (LR) and Artificial Neural Networks (ANN) model. Response variables such as satisfaction level, number of projects, average monthly working hours, employment period, working accident, promotion in the last 5 years, department, and salary level are used to model the employee turnover. Parameters such as accuracy, precision, sensitivity, Kolmogorov-Smirnov statistic, and Mean Squared Error (MSE) are used to compare both models.
EKSPLORASI PENGALAMAN TERHADAP RISIKO BERWISATA PADA KONSUMEN WISATA PEREMPUAN DI INDONESIA Peni Zulandari Suroto; Maria Zefanya Sampe; Made Handijaya Dewantara
Journal of Tourism Destination and Attraction Vol 8 No 2 (2020): Journal of Tourism Destination and Attraction
Publisher : Fakultas Pariwisata Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/tourism.v8i2.1649

Abstract

This study aims to explore the experiences of Indonesian female tour consumers regarding risks they face when traveling domestically. Data was collected through focus group discussions (FGD), to nine female tour consumer informants who traveled in Indonesia. Qualitative data were analyzed descriptively. The opposite grouping of keywords is done by creating a code and make narration. The results showed that there were four motivations for traveling, and two of them were related to risk. Female tour consumers want to explore new destinations, have high sense of curiosity, are interested in enjoying natural, cultural, and culinary richness. Forms of risk experienced by female tour consumers include natural conditions, geography, racial discrimination, verbal harassment, and physical injury. Female tour consumers anticipate risks by looking at various references, for making decisions, travel partners, and seeing publications from trusted sources. Although index and risk management have not been standardized in Indonesia, due to a travel ban in a cultural context, Indonesian female tour consumers tend to take risks to travel and repeat it several times. Behind the risk, they get important things such as unbeatable views, new experiences and knowledge, excitement, satisfying curiosity, and enjoyment of local wisdom. The findings on Indonesian female tour consumers are important input for tourism destination stakeholders.