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PELUANG DAN TANTANGAN UMKM DI MASA PANDEMI COVID-19 Nurhidayah, Fitriyah; Mutira, Putri; Yanti, Yanti; Purnamasari, Ratih; Meutia, Meutia; Uzliawati, Lia; Ismail, Tubagus; Ramdhani, Dadan; Abu Hanifah, Imam; Bastian, Elvin; Yazid, Helmi; Sholikhan Yulianto, Agus
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2022): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v5i2.695-698

Abstract

Pandemi Covid-19 telah berlangsung lebih dari setahun dan masih belum menunjukkan tanda-tanda akan segera berakhir. Dampaknya sangat luas dan mempengaruhi berbagai sektor, termasuk UKM. Para pelaku usaha tersebut secara langsung mengalami penurunan omzet bahkan menutup usahanya. Sebagai upaya untuk mengurangi atau mengatasi dampak pandemi di sektor UKM, kampus bisa menjadi motor penggerak. Universitas Sultan Ageng Tirtayasa melalui kegiatan Pengabdian kepada Masyarakat tidak ketinggalan juga berkontribusi, namun dengan mempertimbangkan situasi pandemi dan pembatasan kegiatan masyarakat secara langsung dengan jangkauan yang luas dan untuk memutus penyebaran Covid-19 maka digunakan strategi webinar online, yaitu peluang dan tantangan yang dihadapi oleh UKM di Indonesia. di tengah pandemi yang memberikan solusi terbaik.
Pemberdayaan Masyarakat Melalui Teknologi Pengolahan Ikan Asin Ramah Lingkungan Berbasis Greenhouse Nurhidayah, Fitriyah; Silalahi, Ronald Maraden P.; Setiawan, Agustinus Agus; Mantofani, Rizal
Journal Pemberdayaan Masyarakat Indonesia Vol 7 No 2 (2025): Jurnal Pemberdayaan Masyarakat Indonesia (JPMI) - In Progress
Publisher : Pusat Pengabdian kepada Masyarakat (PPKM) Universitas Prasetiya Mulya

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Abstract

Sumberjaya Village is a coastal community known as a traditional salted-fish production center, supported by abundant marine resources such as anchovy, grouper, tuna, snapper, and shrimp. Despite its potential, the drying process still relies heavily on conventional sun drying, making production vulnerable to weather conditions. During the rainy season, production frequently halts, product quality declines, and community income drops significantly. Through the BIMA Community Service Grant Program, the implementing team introduced an innovative Solar-Powered Greenhouse Dryer to address these challenges. This technology enables year-round drying in a hygienic, efficient, and environmentally friendly manner, producing cleaner and longer-lasting salted fish with higher market value. In addition to technological intervention, the program also provided training in business management, basic financial recording, digital marketing, and product legality assistance, including PIRT, NIB, and halal labeling. This integrated approach strengthened production capacity, enhanced community skills, and reinforced local institutional resilience. Overall, the synergy between appropriate technology and community capacity building has transformed Sumberjaya Village into a model of modern green-technology-based salted-fish processing, serving as a best-practice example of sustainable coastal economic empowerment in Indonesia.
Cash Flow Prediction System of PT Gudang Garam Using ERP-Integrated LSTM Novandi, Muhammad Ananta Arya; Nurhaida, Ida; Sofia, Irma Paramita; Nurhidayah, Fitriyah
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1235

Abstract

Enterprise Resource Planning (ERP) applications such as Odoo generally do not have predictive analytics capabilities for time series data and are limited to recording historical financial data. The limitations of ERP systems make companies dependent on traditional statistical models such as ARIMA, which often fail to capture complex non-linear patterns in financial data. However, the ability to accurately predict cash flow is crucial for strategic financial management in companies. This study aims to develop and evaluate a predictive model using a Long Short-Term Memory (LSTM) approach that is accurate and integrated into Odoo ERP. The research method includes designing a microservices architecture with FastAPI as a bridge between Odoo ERP, the predictive model, and prediction graph visualization. The LSTM model is evaluated by comparing it with the ARIMA model using 3,740 Daily cash flow data, with evaluation metrics MAE, MAPE, R2. System testing will use Black Box Testing and White Box Testing. The research results show that LSTM significantly outperforms the ARIMA model with an R2 evaluation of 0.8801 and an accuracy of 96.62%. The system testing results also yielded positive outcomes as the integration architecture runs stably and functionally. This research contributes by providing an Odoo ERP system that has predictive analysis capabilities with interactive graphical visualizations through Grafana, which helps companies make decisions effectively.