Claim Missing Document
Check
Articles

Management of educators and educational staff Maftuhah Maftuhah; Amanta Annajma Khaularahma; Yovie Shafa Aulia Maymalaputri; Nazwa Aulia; Taufiqurrahman Taufiqurrahman
JURNAL PENDIDIKAN IPS Vol. 15 No. 3 (2025): JURNAL PENDIDIKAN IPS
Publisher : STKIP Taman Siswa Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37630/jpi.v15i3.3304

Abstract

Educator and education personnel management is a key component in improving the quality of education, involving systematic resource management from planning to supervision. This process influences the quality of learning, work motivation, and student achievement. This study aims to examine the concept, urgency, service areas, and processes of educator and education personnel management using qualitative literature study methods. The results indicate that professional management, including adaptive and continuous training, and attention to the psychological and professional dimensions of educators, is crucial in facing the challenges of the digital era.
Leveraging the RFM Model for Customer Segmentation in a Software-as-a-Service (SaaS) Business Using Python Andy Hermawan; Nila Rusiardi Jayanti; Aji Saputra; Army Putera Parta; Muhammad Abizar Algiffary Thahir; Taufiqurrahman Taufiqurrahman
Maeswara : Jurnal Riset Ilmu Manajemen dan Kewirausahaan Vol. 2 No. 5 (2024): OKTOBER : Maeswara : Jurnal Riset Ilmu Manajemen dan Kewirausahaan
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/maeswara.v2i5.1283

Abstract

Customer segmentation plays a pivotal role in driving marketing strategies and improving customer retention across various industries. This study explores the application of the RFM (Recency, Frequency, Monetary) model for customer segmentation in a Software-as-a-Service (SaaS) business, using Python for efficient data processing and analysis. By analyzing one year of customer purchase data, we segmented customers into key groups such as "Champions," "Loyal Customers," and "At Risk." The results highlight that targeted discount strategies significantly affect profitability, especially for high-value customer segments. Furthermore, the research builds upon existing methodologies, demonstrating how Python-based implementations streamline RFM analysis and allow for scalable solutions in business contexts, as illustrated in prior works by Hermawan et al. (2024). This study offers actionable recommendations, including tailored discounting, loyalty programs, and personalized engagement strategies, to enhance customer retention and business profitability. The findings underscore the importance of data-driven marketing approaches for customer segmentation and engagement, reinforcing the relevance of the RFM model in modern business environments.