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All Journal Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Community Empowerment
Ikhwan Alfath Nurul Fathony
Universitas Islam Indonesia
Arts Humanities Computer Science & IT Education Electrical & Electronics Engineering Public Health Social Sciences

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Shibboleth IdP for Single Sign-On with Kubernetes and Persistent Volume Longhorn Ikhwan Alfath Nurul Fathony; Mukhammad Andri Setiawan
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24272

Abstract

Many organizations do not use centralized user authorization with Single Sign-On (SSO) Management to seamlessly move from one system to another. The same thing also occurred at Universitas Islam Indonesia (UII). Students were having trouble login in from one web service to another. The Board of Information Systems of UII, or Badan Sistem Informasi (BSI), implements SSO to avoid this problem. However, after BSI implemented SSO on the virtual machine, it turned out that the server load became too high. A spiking number of user logins happened in a short period. The centralized system could not handle this. The research's solution is to use a clustered service using Shibboleth IdP. The Shibboleth IdP customization can be carried out to be deployed into the Kubernetes cluster infrastructure ecosystem to meet the needs of authentication login on the business processes at UII. The Shibboleth IdP itself will be equipped with a persistent storage longhorn to support and maintain the service and avoid a single point of failure. The Kubernetes and Persistent Volume Longhorn provide a redundancy function in an application and a more flexible replication process. Inside Kubernetes, there is containerization technology. It was used to optimize the server's resources instead of replicating the application using virtual machines. With the use of centralized login by Shibboleth IdP and persistent storage longhorn, the error because of server load could be minimized. The downtime of the downed services can also be reduced. The research also proves that using Kubernetes and Persistent Volume Longhorn could help the system by preventing a Single Point of Failure using its redundancy function.
Digital literacy training for female employees at CV Gemilang Kencana Adiana, Beta Estri; Mareta, Affix; Fathony, Ikhwan Alfath Nurul; Wardhani, Olivia
Community Empowerment Vol 10 No 6 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.13520

Abstract

CV Gemilang Kencana, a Micro, Small, and Medium-sized Enterprise (MSME) in the food and beverage processing sector in Wonosobo Regency, faces challenges in leveraging digital technology due to low digital literacy among its employees, particularly women. This community service initiative aimed to enhance the digital literacy skills of female employees through training that covered basic technology introduction, productivity application usage, and the utilization of social media for product marketing. The implementation method involved preparation, training delivery, and evaluation stages. The training results demonstrated a significant improvement in participants' digital understanding and skills, with the average pre-test score of 46.5% increasing to 81% post-training. Active participants were able to independently utilize social media for product marketing and contributed to improved operational efficiency and MSME competitiveness. This training proved effective in empowering women and supporting digital transformation within the MSME sector, while also enhancing participants' capabilities in navigating the increasingly digitalized era.
Optimisasi Whisper Speech-to-Text Bahasa Indonesia dengan Hybrid Cloud dan Multi-Engine Ikhwan Alfath Nurul Fathony; Affix Mareta; Beta Estri Adiana; Olivia Wardhani; Dimas Ardiansyah Halim
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 1 (2025): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/5n2d3s08

Abstract

Automatic Speech Recognition (ASR) for the Indonesian language faces significant challenges due to high Word Error Rate (WER), especially when using pre-trained models without fine-tuning. This study develops an optimized ASR system using a hybrid cloud architecture that integrates the Faster-Whisper large-v3 engine with advanced audio preprocessing techniques. The system adopts a distributed architecture, with Google Colab (Tesla T4, 15GB VRAM) as the GPU server and Ubuntu 22.04 LTS (8 core, 32GB RAM) as the client. Evaluation was conducted on five Indonesian audio samples covering formal news, informal conversations, and long-duration recordings. The system achieved an 80% success rate in processing, with WER ranging from 27.69% (formal news) to 645.16% (informal conversations). Resource utilization was also efficient, with 21.3% GPU usage and 35.4% RAM usage. Processing time remained stable for normal-sized files but experienced timeouts on large files (>50MB). The results indicate that hybrid cloud architecture is feasible for distributed ASR processing in Indonesian, with several areas still open for optimization toward production deployment.
Co-Authors Beta Estri Adiana Halim, Dimas Ardiansyah Mareta, Affix Olivia Wardhani Setiawan, Mukhammad Andri Wardhani, Olivia