Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal J-Innovation Jurnal Pariwisata, Bisnis Digital dan Manajemen
Dama, Desi Masdin
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementasi Algoritma Apriori Dalam Analisa Penjualan Sparepart Motor Ihsan, Muhammad Ifan Rifani; Irmanti, Kanita Salsabila Dwi; Dama, Desi Masdin
Jurnal Pariwisata Bisnis Digital dan Manajemen Vol. 1 No. 1 (2022): Jurnal Pariwisata, Bisnis Digital dan Manajemen Periode Mei 2022
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1273.081 KB) | DOI: 10.33480/jasdim.v1i1.2999

Abstract

Abstract— In 2020, Indonesia's population is dominated by Gen Z (born 1997-2012) and Millennials (born 1981-1996). ). Gen Z accounts for 27.94% of the total population and millennials reach 25.87%. Most of these two generations are in the working age group, which could be an opportunity to accelerate economic growth. The government needs to encourage generations z and millennials to become entrepreneurs. The government calls on millennials to start a business. Technology development allows people to become entrepreneurs and self-employed. Changes in the usage of this technology will affect the human resource management of the. The gig economy enhances the flexibility and ability to hire skilled professionals from different parts of the world across time zones and geographic boundaries. This dynamics presents us with new challenges. Gig worker represents the balance between immediate working life and the need to increase income. Today's workers want flexibility in their work. The research method used is qualitative to primary data and secondary data. In addition, the data source was explained qualitatively. The survey results were performed by UBSI Jakarta Z- and 130 student repondents. The respondent has knowledge of entrepreneurship 60.8% and 39.2% of respondents can not understand. The type of work of GIG economy and generation z Gig era was awarded 47.7% itself, and then the work in society was determined by 28.4% free lancer. Reasons for choosing a job type show that 40% receive unlimited income, 25.4% are flexible, 26.2% of respondents are rewarded according to their job, and 8.5% choose others a job. Keywords: Entrepreneur, Gen Z, Millennials, GIG economy
Analisis Komparatif Metode Peningkatan Kualitas Citra Digital untuk Deteksi Area Tubercoluma pada Citra MRI Hidayat, Taopik; Dama, Desi Masdin; Irmanti, Kanita Salsabila Dwi
J-Innovation Vol. 13 No. 2 (2024): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v13i2.289

Abstract

Digital images are essential visual representations in medical analysis, particularly for detecting tuberculoma, a severe tuberculosis complication with high mortality. This study aims to enhance the quality of MRI T1 images for identifying specific tuberculoma areas by comparing four method segmentation, thresholding, negation, and embossed. The dataset comprises T1 MRI brain scans in top and bottom positions, followed by pre-processing stages to reduce noise using gaussian blurring, median blurring, and sharpening techniques. The pre-processing results indicate all methods retain image details effectively. Further analysis reveals the Embossed method produces the clearest images with high contrast, facilitating tuberculoma identification. The advantage of this method lies in its ability to highlight structural details through a three-dimensional effect. The findings conclude that the embossed method effectively improves the accuracy of tuberculoma detection, contributing significantly to advancing medical image analysis techniques. This research is expected to positively impact imaging-based disease diagnosis, particularly in brain tumor cases like tuberculoma.
Co-Authors Hidayat, Taopik Irmanti, Kanita Salsabila Dwi Muhammad Ifan Rifani Ihsan