Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Digitus : Journal of Computer Science Applications Babakti: Journal of Community Engangement
Corizon Sinar Arainy
STMIK Mercusuar
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Public Health Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Manajemen Sumber Daya Manusia dalam Upaya Meningkatkan UMKM di Desa Sukarame Saromah; Anjelis Ratu Wulan; Samroh; Muhammad Ikrar Yamin; Corizon Sinar Arainy; Ahmad Soderi; Juwari; Karno Diantoro; Abdurrohman; Anwar T Sitorus; Rinaldo
Babakti: Journal of Community Engangement Vol 2 No 2 (2025): October
Publisher : Fakultas Teknik, Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/babakti.v2i2.13079

Abstract

Manajemen sumber daya manusia (SDM) merupakan faktor penting dalam pengembangan Usaha Mikro, Kecil, dan Menengah (UMKM) karena kualitas SDM sangat menentukan daya saing dan keberlanjutan usaha. Berdasarkan hasil observasi di Desa Sukarame, Kabupaten Pandeglang, Provinsi Banten, ditemukan bahwa sebagian besar pelaku UMKM masih memiliki pemahaman yang terbatas mengenai manajemen SDM, termasuk perencanaan tenaga kerja, rekrutmen, pengelolaan kinerja, serta strategi pengembangan usaha. Kondisi ini menjadi latar belakang dilaksanakannya kegiatan pengabdian kepada masyarakat oleh tim dosen dan mahasiswa STMIK Mercusuar, yang bertujuan untuk meningkatkan pemahaman pelaku UMKM tentang pentingnya pengelolaan SDM dalam mendukung pertumbuhan usaha. Kegiatan dilaksanakan pada 26–27 April 2025 melalui metode penyuluhan, diskusi, pelatihan, dan simulasi pelayanan dan manajemen usaha. Materi mencakup konsep dasar manajemen SDM, peran SDM dalam persaingan usaha, serta strategi digitalisasi dan ekspansi pasar. Hasil kegiatan menunjukkan peningkatan pemahaman peserta secara signifikan, dengan skor pre-test rata-rata 48% meningkat menjadi 82% pada post-test. Sebanyak 80% peserta mampu membuat draft job description sederhana, 72% berhasil menyusun rencana perekrutan, dan 68% mulai merancang strategi pemasaran digital. Tingginya antusiasme selama diskusi dan keberhasilan peserta dalam simulasi menunjukkan kegiatan ini memberikan dampak positif dalam menumbuhkan kesadaran pentingnya pengelolaan usaha yang profesional. Kegiatan ini diharapkan menjadi awal dari penguatan kapasitas UMKM berbasis masyarakat lokal dan direplikasi di wilayah lain dengan karakteristik serupa.
Real Time Mobility Intelligence: Evaluating Kafka Based Pipelines in Global Smart Transit Systems Sugianto; Corizon Sinar Arainy
Digitus : Journal of Computer Science Applications Vol. 3 No. 4 (2025): October 2025
Publisher : PT Penerbit Ilmiah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v3i4.959

Abstract

Real-time streaming architectures are redefining the landscape of urban transit analytics by enabling low latency, data driven decision making. This study evaluates and compares the real time data processing capabilities of public transit systems in London, New York, and Singapore. The objective is to determine how architectural choices, data freshness, and machine learning integration influence key performance indicators such as latency, ETA accuracy, and anomaly detection. The methodology involves a multi city case study, where Kafka based pipelines integrated with Apache Flink and Spark were assessed for ingestion, processing, and service delivery. Datasets included GTFS Realtime, SIRI feeds, and contextual APIs (e.g., speed bands and crowd density). Metrics for evaluation included feed latency, mean absolute error (MAE) and root mean square error (RMSE) for ETA, and response times for anomaly detection. The results demonstrate that Singapore’s transit system outperformed its counterparts with the lowest latency (~12s), highest ETA accuracy (MAE = 18s; RMSE = 25s), and superior anomaly detection via multi sensor fusion. London and New York, while technologically robust, faced constraints due to longer feed update intervals and integration complexities. Kafka ML's online learning enhanced model adaptability, significantly reducing ETA prediction errors across dynamic conditions. Furthermore, stress testing revealed Singapore’s architecture as the most resilient under peak load. The study concludes that the effectiveness of real-time urban transit systems depends on harmonizing streaming infrastructure... Singapore’s architecture may serve as a potential reference model for other cities, while recognizing contextual differences in implementation. Singapore’s architecture offers a scalable template for other cities. Ethical considerations, including data governance and passenger privacy, are essential for sustainable implementation.
Co-Authors Abdurrohman Ahmad Soderi Anjelis Ratu Wulan Anwar T Sitorus Juwari Karno Diantoro Muhammad Ikrar Yamin Rinaldo Samroh Saromah Sugianto