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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) International Conference on Engineering and Technology Development (ICETD) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal ULTIMATICS METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Pengabdian Pada Masyarakat METHABDI Jurnal Ilmiah Teknologi dan Komputer (JITTER)
Sri Agustina Rumapea
Universitas Methodist Indonesia
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Physics Public Health

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Integrasi Algoritma YOLOv8 dan Streamlit untuk Visualisasi Real-Time dan Akurat dalam Penghitungan Kerumunan di Kawasan Stasiun Bekasi Prihandoko, Prihandoko; Rumapea, Sri Agustina; Pratama, Abdul Hanif
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp179-187

Abstract

Crowd management in public transportation areas has become a critical challenge with the rise of urban populations. This study develops a real-time web-based people detection and counting system by integrating the YOLOv8 algorithm with the Streamlit framework. A case study was conducted at the entrance of Bekasi Station. The model was developed using the AI Project Life Cycle approach, and the system was built following the Waterfall methodology. Data were obtained from video recordings, which were extracted into images, annotated, and processed into training and testing datasets. The YOLOv8 model was trained for 50 epochs, yielding strong performance with an mAP@0.5 of 91.7%, a maximum precision of 93.6%, and an F1-score of 87%. Tests on 15 images showed an average accuracy of 80.37% and an error rate of 19.63%. The model's performance declined on out-of-dataset images due to variations in lighting and extreme crowd density. The system was tested using black-box testing and demonstrated that all main features—image upload, object detection, visualization, and result download—functioned correctly. The system has been successfully deployed on Streamlit Cloud. These results indicate that the system offers a practical, lightweight, and responsive solution to support crowd monitoring in public areas. In future development phases, the system can be extended to support real-time video stream processing and integrated with an object tracking and classification module to accurately identify and differentiate the ingress and egress flow of individuals within a defined surveillance area.
PENRAPAN FUZZY TIME SERIES UNTUK PREDIKSI PRODUKSI IKAN TAMBAK DI SUMATERA UTARA Samuel Bakkara; Sri Agustina Rumapea; Edward Rajagukguk
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 11 No. 1 (2025): Volume 11 Nomor 1 Tahun 2025
Publisher : Universitas Methodist Indonesia

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Abstract

Fish is one of the most potential animal food products in Indonesia. Over the years, the majority of animal food consumption in Indonesia has been contributed by fish products. The increasing growth rate in North Sumatra is balanced by the food potential that can support the region's food security. Based on data from the fisheries sector potential in North Sumatra, pond fish farming in the province of North Sumatra covers an area of 20,000 hectares, spread across various districts/cities. The pond fish cultivated include catfish, catfish, tilapia, carp, snapper, milkfish, grouper. Given the potential of the pond aquaculture sector and the increasing awareness of the population in North Sumatra to consume fish as a source of nutrition, this research aims to predict pond fish production in North Sumatra. The prediction of pond fish production in North Sumatra is conducted to address the challenges of fluctuating pond fish production, uncertainty in supply and demand using the fuzzy time series method. The results of the study using the Fuzzy Time Series method in forecasting pond fish production in North Sumatra obtained forecast accuracy for catfish of 11.702%, for catfish of 10.359%, for tilapia of 21.636%, for carp of 15.788%, for snapper of 11.487%, for milkfish of 12.87%, for grouper of 12.263%, and for shrimp of 14.814%.).
Co-Authors Aritonang, Mendarissan Darwis Robinson Manalu Edward Rajagukguk Edward Rajagukguk Fati Gratianus Nafiri Larosa Fawwaz, Muhamad Faishal Gea, Asaziduhu Hasibuan, Doli Humuntal Rumapea Humuntal Rumapea Jhoni Maslan, Jhoni Kridanto Surendro Lumbanraja, Posma Mufria J. Purba Nettina Samosir Pratama, Abdul Hanif Prihandoko Prihandoko Purba, Nova Ferawati Rajagukguk, Edward Rumapea, Yolanda Y. P. Samosir, Nettina Samuel Bakkara Sarkis, Indra M. Silalahi, Arina Prima