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All Journal Jurnal Teknologi Informatika dan Komputer Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced
Harries Arizonia Ismail
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Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences Other

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PENGARUH KEPEMIMPINAN, KOMPENSASI, LINGKUNGAN KERJA DAN WORK-LIFE BALANCE TERHADAP KINERJA KARYAWAN (Studi Kasus Pada Karyawan PT. Kereta Api Indonesia (Persero) Daerah Operasi (DAOP) IV Semarang) Nuraningsih, Cahya Indah; Harries Arizonia Ismail
Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced Vol. 2 No. 3 (2024): Future Academia : The Journal of Multidisciplinary Research on Scientific and A
Publisher : Yayasan Sagita Akademia Maju

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61579/future.v2i3.180

Abstract

This research examines the impact of leadership, salary, work environment, and work-life balance on worker performance at PT. Indonesian Railways (Persero) Operational Area 4 Semarang. By using a quantitative approach and a questionnaire survey of 145 employee respondents, the research concluded that each variable had a significant effect on employee performance. All research measuring instruments were declared valid and reliable based on the results of validity and reliability tests. Multiple linear regression research shows that leadership, salary, working conditions, and work-life balance have a positive effect on employee performance. These findings provide important information for improving management strategies and human resource development in companies.
Pengaruh Kualitas Produk, Keterjangkauan Harga, Online Customer Rating Dan Digital Marketing Terhadap Minat Beli Produk Di Online Shop Shopee (Studi Kasus pada Masyarakat di Desa Bolo) Eva Prihatiningsih; Harries Arizonia Ismail
Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced Vol. 2 No. 4 (2024): Future Academia : The Journal of Multidisciplinary Research on Scientific and A
Publisher : Yayasan Sagita Akademia Maju

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61579/future.v2i4.308

Abstract

This study aims to examine the influence of product quality, price affordability, online customer ratings, and digital marketing on purchase intention for products on the Shopee online shopping platform. The research sample consisted of 100 Shopee users in Desa Bolo, Demak Regency, selected using the Slovin formula. Data were collected through questionnaires with a Likert scale. The findings revealed that product quality, price affordability, online customer ratings, and digital marketing positively and significantly influence purchase intention. Based on regression analysis, product quality (β = 0.504), price (β = 0.118), online customer ratings (β = 0.206), and digital marketing (β = 0.281) each significantly impact purchase intention. These findings provide insights for e-commerce companies to enhance these factors in their marketing strategies to attract consumer purchase intentions.
Analysis of Boarding House Payment Patterns Using Data Visualization Techniques to Identify Delay Factors Abid Sakti Pamungkas; Yohana Tri Widayati; Harries Arizonia Ismail
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2841

Abstract

In an increasingly competitive business environment, the ability of Micro, Small, and Medium Enterprises (MSMEs) to survive heavily depends on effective cash flow management. Boarding house businesses, as a form of MSMEs in the service sector, face crucial challenges due to late rental payments by tenants. Management practices that are often reactive and intuitive have proven less effective in identifying the root causes of such issues. This study aims to apply an analytical approach using data visualization techniques to analyze rental payment patterns at Kost Green, Semarang. The main objective is to discover significant temporal patterns and identify tenant profile factors that strongly correlate with late payment behavior. The methodology employed is exploratory data analysis with a quantitative and visual approach, using primary data in the form of historical rental payment transactions over a one-year period, covering attributes such as tenant status and room type. The analysis process begins with a data preprocessing stage, in which a key analytical feature, Days_Late, is engineered to measure the duration of delays. The analysis is conducted using the Python programming language supported by the Pandas, Matplotlib, and Seaborn libraries. The findings reveal the existence of high-risk tenant segments (students) and critical time periods (certain months of the year) when delays tend to increase. The outcome of this research is a visual analytical report that provides a strong foundation for Kost Green management to make data-driven decisions, design more proactive and segmented billing strategies, and ultimately improve payment discipline and maintain healthy business cash flow.
Analysis of Boarding House Payment Patterns Using Data Visualization Techniques to Identify Delay Factors Abid Sakti Pamungkas; Yohana Tri Widayati; Harries Arizonia Ismail
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2841

Abstract

In an increasingly competitive business environment, the ability of Micro, Small, and Medium Enterprises (MSMEs) to survive heavily depends on effective cash flow management. Boarding house businesses, as a form of MSMEs in the service sector, face crucial challenges due to late rental payments by tenants. Management practices that are often reactive and intuitive have proven less effective in identifying the root causes of such issues. This study aims to apply an analytical approach using data visualization techniques to analyze rental payment patterns at Kost Green, Semarang. The main objective is to discover significant temporal patterns and identify tenant profile factors that strongly correlate with late payment behavior. The methodology employed is exploratory data analysis with a quantitative and visual approach, using primary data in the form of historical rental payment transactions over a one-year period, covering attributes such as tenant status and room type. The analysis process begins with a data preprocessing stage, in which a key analytical feature, Days_Late, is engineered to measure the duration of delays. The analysis is conducted using the Python programming language supported by the Pandas, Matplotlib, and Seaborn libraries. The findings reveal the existence of high-risk tenant segments (students) and critical time periods (certain months of the year) when delays tend to increase. The outcome of this research is a visual analytical report that provides a strong foundation for Kost Green management to make data-driven decisions, design more proactive and segmented billing strategies, and ultimately improve payment discipline and maintain healthy business cash flow.
Co-Authors Abid Sakti Pamungkas Eva Prihatiningsih Nuraningsih, Cahya Indah Yohana Tri Widayati