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Pengaruh Work From Home Terhadap Kinerja Karyawan Di Batam Kelvyn Kelvyn; Ellwan Edy Wei; Christopher Khomali; Hosse Fernando; Veri Hartanto
Sains: Jurnal Manajemen dan Bisnis Vol 13, No 2 (2021)
Publisher : FEB Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35448/jmb.v13i2.11282

Abstract

This study aims to obtain empirical evidence about the effect of work from home on employees job performance taken from the respondents. This analysis using independent variables WFH (work from home), work environment, job satisfaction, and work motivation. The dependent variable is job performance. Samples in this study were the college students who ever or currently working with working from home system in Batam city. This study used a sample method of Stratified Disproportionate Random Sampling with total sample of 150 respondents. This is a quantitative study that distributes data and questionnaires. Data analysis in this study was analyzed using regression using SPSS software. The three supporting factors, work environment, job satisfaction, and job motivation affect the job performance in Batam city. This study proves that work motivation and job satisfaction have positive influence on job performance. From the result, we hope this research can be useful as knowledge and consideration for government or company whether need to continue the implementation of work from home system or not.
TRAVEL ITINERARY RECOMMENDER SYSTEM USING MACHINE LEARNING ANALYSIS AND WEB APPLICATION DEVELOPMENT: A CASE OF BATAM CITY REGION Hosse Fernando; Syaeful Anas Aklani
JURNAL ILMIAH BETRIK Vol. 14 No. 01 APRIL (2023): JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : P3M Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/betrik.v14i01.12

Abstract

Batam City is an island with a complete and diverse point of destination (POI). Searching for information is common when someone is making a travel itinerary. With the help of technology, planning a trip should be fast and easy. In this study, the authors will build a web application-based recommender system with the help of machine learning. This study uses the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development method and then the TAM Model (Technology Acceptance Model) to analyze the effectiveness. The results of system testing show a range of scores with the lowest value 0.509 and the highest value 0.572. This score indicates the degree of correlation between the test and the underlying construct it is designed to measure. A score of 0.509 indicates a weak correlation between the test and constructs, while a score of 0.572 indicates a stronger correlation. Score above 0.5 Thus, the authors hope that this research can be used as a reference or knowledge for future readers or researchers.