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Pengaruh Pengelolaan Sarana Prasarana dan Pemahaman Teori Menjahit Terhadap Kualitas Pembelajaran Praktikum pada Jurusan Tata Busana di SMK Negeri 1 Sangatta Utara Sulistiani Sulistiani; Eko Nursalim; Muh Ibnu Faruk Fauzi
Lokawati : Jurnal Penelitian Manajemen dan Inovasi Riset Vol. 3 No. 4 (2025): July : Jurnal Penelitian Manajemen dan Inovasi Riset
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/lokawati.v3i4.1834

Abstract

This study aims to determine the extent of the influence of infrastructure management and understanding of sewing theory on the quality of practicum learning in the Fashion Department at SMK Negeri 1 Sangatta Utara. This study uses a quantitative approach with data collection methods through questionnaires, observation, and documentation. The research sample amounted to 107 students from a total population of 143 students in classes X, XI, and XII. The results of multiple linear regression analysis show that the management of infrastructure facilities has an influence of 16.26%, while the understanding of sewing theory has a greater influence, namely 71.53% on the quality of practicum learning. Simultaneously, the two variables contributed 87.9%, while 12.1% was influenced by other factors not studied. This finding confirms that the understanding of sewing theory has a more dominant influence than the management of infrastructure facilities in improving the quality of practicum learning in the Cosmetology department at the SMK.
Artificial Intelligence in Financial Forecasting : Enhancing Accuracy and Strategic Planning in Financial Management Sulistiani Sulistiani; Adiba Fuad Syamlan; Bustanul Ulum
Brilliant International Journal Of Management And Tourism Vol. 5 No. 2 (2025): June : Brilliant International Journal Of Management And Tourism
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/bijmt.v5i2.4455

Abstract

This study explores the implementation of Artificial Intelligence (AI) technologies in financial forecasting, aiming to improve prediction accuracy and enhance strategic financial decision-making. Traditional forecasting methods, such as ARIMA and linear regression, often fall short in modeling complex, nonlinear financial data, especially in volatile markets. In response, this research investigates the comparative performance of machine learning (ML), deep learning (DL), and hybrid AI-big data models. A qualitative exploratory approach was adopted, involving a systematic literature review and semi-structured interviews with financial practitioners and experts. The analysis revealed that hybrid models integrating Random Forest with big data analytics achieved the highest predictive accuracy (93.2%) and operational adaptability. LSTM models also demonstrated strong performance in handling time-series data but were limited by their lack of interpretability. Compared to traditional models, AI-based approaches significantly reduced prediction errors and offered real-time responsiveness, aligning with the dynamic needs of financial environments. The findings support the hypothesis that AI technologies can bridge the gap between accurate forecasting and strategic financial planning. However, challenges such as high computational requirements and low model transparency persist. Therefore, the study concludes that while AI models present a transformative potential for financial forecasting, successful implementation requires balancing model performance with organizational capabilities and regulatory considerations. These insights provide valuable guidance for financial managers and policymakers seeking to adopt AI-driven forecasting systems in increasingly complex and data-rich financial landscapes.
Co-Authors , Dasrol Abdul Choliq Adiba Fuad Syamlan Bustanul Ulum Eko Nursalim FITRIA FAJAR PRIASTUTI Hafidz Taqiyuddin Hanifah Nuryani Lioe Ismail K Usman mamay humaeroh Muh Ibnu Faruk Fauzi Nanda Sabbaha Nur Kasfillah Neny Mariyani NURINA WAKHIDATUL MUNAWAROH Ola Alifiyanti Zahra Purnama Padmono Citroreksoko Pratiwi, Cesa Septiana Resti Sofia Zahara Sri Handayani Sulfa Potiua Syafriana, Vilya Tatik Khusniati Tatik Khusniati Trisanti Anindyawati Yati Sudaryati Soeka Zulfikar Jayakusuma