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Gen Z Students at State Senior High School 3 Rembang Learn Financial Literacy and Invest Early Roro Ayu Deby Citra Putri; Nita Afifah; Dian Anita Sari
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v6i1.7321

Abstract

The study purpose was to improve financial literacy among Generation Z students at SMA Negeri 3 Rembang, who generally possess limited knowledge regarding personal financial management and capital market investment. This community service program was motivated by national survey data indicating that Indonesia’s financial literacy rate remains relatively low, at only 38.03%, highlighting the urgent need for early financial education interventions. The program aimed to enhance students’ understanding, awareness, and basic competencies in managing finances and recognizing investment opportunities in the capital market. Materials and methods. The program was implemented using an educational and participatory approach through a series of structured activities, including Financial Literacy Counseling, Capital Market Investment Counseling, and a Capital Market School. The main activity was conducted in the form of a seminar-based training on November 7, 2023, involving 31 participants who were members of the student council (OSIS). The materials were delivered by competent speakers with expertise in finance and capital markets. Supporting methods included interactive discussions, visual learning media, and documentation through video recordings. Results. The program was successfully implemented as planned, resulting in the completion of financial literacy education, investment counseling, and Capital Market School activities. The findings indicate an improvement in students’ knowledge and understanding of financial management and capital market investment concepts. In addition, program documentation was disseminated through a YouTube video, and intellectual property rights (HKI) in the form of posters and activity videos are currently in the publication process. Conclusions. The community service program effectively increased financial literacy among participating students and demonstrated the importance of early financial education for Generation Z. Although some outputs are still in progress, the program showed positive educational impacts. It is recommended that future implementations involve a larger number of participants to broaden the program’s reach and maximize its long-term benefits.
PERBANDINGAN MODEL ALTMAN Z-SCORE, SPRINGATE DAN ZMIJEWSKI DALAM MEMPREDIKSI KEBANGKRUTAN INDUSTRI TEKSTIL DI BEI Nita Afifah; Damayanti Damayanti
Jurnal Pendidikan Ekonomi (JURKAMI) Vol 11, No 1 (2026): JURKAMI
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jpe.v11i1.5918

Abstract

The Textile and Textile Products (TPT) industry is one of the strategic sectors in the Indonesian economy. However, in recant years it has faced considerable pressure due to the COVID-19 pandemic, global economis slowdown, and increasing import competition. These conditions have led to a decline in finanicial performance and an increased risk of bankruptcy among textile companies. Therefore, reliable bankruptcy prediction result among the Altman Z-Score, Springate S-Score dan Zmijewski X-Score models, as  well as to determine the most accurate model in predicting bankruptcy of textile industry companies listed on the Indonesia Stock Exchange during the 2020 – 2024 period. The research sample was selected using a purposive sampling method, resulting in 15 textile companies as research samples. Hypothesis testing in this study was conducted using the Kruskal-Wallis test. The Result indicate that there are significant differences among the Altman Z-Score, Springate S-Score dan Zmijewski X-Score models in predicting bankruptcy. Furthermore, the Zmijweski model is found to be the most accurate in predicting bankruptcy in the textile industry, with an accuracy rate of 70,67%. This study is limited to the use of three bankruptcy prediction models.