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Analysis of Forecasting Demand for Wheel Loader Unit Rental Using the Arima Method to Determine Safety Stock Inventory and Service Level at PT Petrokopindo Cipta Selaras Maghfur, Maula Aringga; Tranggono, Tranggono
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 7 No. 3 (2025): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v7i3.1368

Abstract

PT XYZ is a company engaged in the rental of heavy equipment such as excavators, forklifts, bulldozers, and Wheel Loaders. The problem faced is unpreparedness in dealing with fluctuations in demand, so there is often a backlog or excess inventory. This research aims to improve the accuracy of demand forecasting and determine safety stocks to anticipate these uncertainties. The research was conducted using historical data on Wheel Loader rental requests from September to November 2024. The data was processed using the ARIMA (Autoregressive Integrated Moving Average) method through several stages, namely stationarity testing, identification of ACF and PACF, model estimation, parameter testing, white noise test, and selection of the best model. The resulting significant model was ARIMA (3,1,1), with a MAPE error value of 21% (79% accuracy), an increase of 9% compared to the previous method with an error of 30%. The results of the calculation of safety stock to deal with fluctuations in demand at various service levels show that the need for 2,688 units at the 90% level, increased to 3,444 units at the 95% level, and reached 3,900 units at the 97% level. This study shows that the ARIMA method is able to improve the accuracy of forecasting and provide a better basis for determining safety stock in managing fluctuations in heavy equipment rental demand.
Utilization of Big Data For PPE Detection Using Convolutional Neural Network And Yolov8 Bisri, Hasan; Maghfur, Maula Aringga; Rahadian, Yanuar Rafi
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13774

Abstract

Indonesia holds a strategic position in the global manufacturing sector, with a manufacturing output of USD 228.32 billion in 2021, ranking 10th worldwide. In 2023, it ranked 12th globally by manufacturing value added, according to the World Bank’s report. However, this growth is accompanied by 297,725 workplace accidents reported in Indonesia in 2022, marking a 27.03% increase from the previous year. This study aims to develop a Personal Protective Equipment (PPE) monitoring system using Big Data, employing Convolutional Neural Network (CNN) and You Only Look Once (YOLO) algorithms. The dataset consists of at least 1,000 images for each of four classes: Helmet, Vest, NoHelmet, and NoVest. Evaluation results show a mAP@50 of 83.1%, with the highest detection performance in Vest (0.90), followed by NoHelmet (0.88), Helmet (0.85), and NoVest (0.81). These findings demonstrate strong potential in supporting safety protocol compliance and reducing workplace accidents in high-risk industrial environments.   Keywords - Big Data, Convolutonal Neural Network, You Only Look Once
Transformasi Ekonomi Sirkular Berkelanjutan: Pemberdayaan Perempuan Desa Giripurno Batu Jawa Timur melalui Inovasi “Banagurt – Banana Yogurt” dari Kulit Pisang Islami, Mega Cattleya; Sari, Rizqi Novita; Issafira, Radissa Dzaky; Maghfur, Maula Aringga; Firmansyah, Aries; Astutik, Rossa Lina; Ristanti, Ira Galuti; rahmawati, Arum
Jurnal SOLMA Vol. 14 No. 3 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i3.20609

Abstract

Background: Ekonomi sirkular merupakan strategi penting dalam mendorong kemandirian ekonomi masyarakat secara berkelanjutan, terutama di daerah pedesaan. Giripurno Batu Jawa Timur memiliki potensi pemanfaatan limbah kulit pisang yang belum optimal untuk menghasilkan produk bernilai tambah. Kegiatan pengabdian ini memberdayakan kelompok perempuan melalui inovasi Yogurt berbahan kulit pisang, sekaligus meningkatkan keterampilan praktis dan pemahaman mereka terkait ekonomi sirkular. Metode: Pendekatan partisipatif melalui pendampingan, meliputi penyampaian materi, diskusi interaktif, dan praktik langsung pembuatan produk. Sebanyak 30 orang terlibat dalam kegiatan pengabdian ini. Evaluasi dilakukan melalui pre-test dan post-test. Hasil: Hasil pre-test menunjukkan 94,28%, yang menandakan sebagian besar peserta memiliki pengetahuan awal, namun terbatas pada penerapan praktis. Setelah kegiatan, post-test meningkat menjadi 95,71%, dengan peningkatan 1,43%, yang menggambarkan efektivitas proses pembelajaran. Kesimpulan: Inovasi Banagurt tidak hanya memperkuat kapasitas perempuan dalam mengolah limbah menjadi produk bernilai ekonomi, tetapi juga mendukung transformasi menuju ekonomi sirkular berkelanjutan dan membuka peluang usaha mandiri yang ramah lingkungan.