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All Journal Al Khidma: Jurnal Pengabdian Masyarakat Journal of Informatics and Vocational Education
Zikri Wahyuzi
Universitas Muhammadiyah Bangka Belitung
Religion Humanities Computer Science & IT Education Social Sciences

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Pencegahan Pernikahan Dini Sebagai Upaya Megurangi Stunting pada Anak di Desa Keciput Zikri Wahyuzi; Muhammad Alfajri; Nurtri Oktavia; Juliana Juliana; Kiranda Kiranda
Al Khidma: Jurnal Pengabdian Masyarakat Al Khidma Vol. 6 No. 2 April - Juni 2026
Publisher : Sekolah Tinggi Ilmu Al-Qur'an (STIQ) Amuntai Kalimantan Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35931/ak.v6i2.6353

Abstract

Pernikahan pada usia anak masih menjadi permasalahan yang sering dijumpai dan berpengaruh besar terhadap tingginya kasus stunting pada anak. Praktik ini umumnya muncul pada masyarakat dengan tingkat pendidikan yang rendah, pengetahuan kesehatan reproduksi yang terbatas, serta kondisi ekonomi yang belum memadai. Desa Keciput di Kecamatan Sijuk, Kabupaten Belitung, menjadi salah satu wilayah yang menghadapi persoalan tersebut, dengan prevalensi stunting mencapai 22,2% dan masih terdapat remaja yang menikah di usia muda. Untuk menjawab permasalahan itu, kegiatan pengabdian masyarakat dilakukan dengan tujuan meningkatkan pemahaman remaja dan warga mengenai risiko pernikahan dini serta hubungannya dengan stunting. Sosialisasi yang berlangsung pada 15 September 2025 ini menghadirkan pemateri dari KUA Kecamatan Sijuk dan Puskesmas Tanjung Binga. Kegiatan dilakukan melalui metode ceramah, sajian visual, dan diskusi interaktif. Materi yang diberikan mencakup definisi pernikahan usia anak, kesiapan reproduksi, dampak kesehatan pada ibu remaja, faktor penyebab stunting, serta langkah-langkah pencegahannya. Hasil kegiatan menunjukkan peningkatan pengetahuan peserta yang ditandai dengan tingginya partisipasi, diskusi yang hidup, dan tanggapan positif terhadap materi. Secara keseluruhan, program ini efektif dalam menumbuhkan kesadaran masyarakat untuk menunda usia pernikahan dan memperkuat upaya pencegahan stunting. Kegiatan serupa disarankan untuk terus dilaksanakan melalui kerja sama antar pihak terkait.
Revitalisasi Plang dan Digitalisasi Homestay Berbasis Google Sites dan QR-Code Sebagai Upaya Branding Desa Tanjong Tinggi Rio Ferdiansyah; Zikri Wahyuzi; Suhendri Suhendri; Sri Widari Ainantia; Perawati Perawati; Alviola Mawar Tifani; Nova Febriyanti; Alya Rahmadea; Abela Ayu Lusianty
Al Khidma: Jurnal Pengabdian Masyarakat Al Khidma Vol. 6 No. 2 April - Juni 2026
Publisher : Sekolah Tinggi Ilmu Al-Qur'an (STIQ) Amuntai Kalimantan Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35931/ak.v6i2.6405

Abstract

Permasalahan keterbacaan plang homestay dan minimnya informasi digital menjadi hambatan dalam penguatan branding Desa Tanjong Tinggi sebagai destinasi wisata. Kondisi ini menyulitkan wisatawan dalam menemukan akomodasi dan memperoleh informasi yang dibutuhkan. Penelitian ini bertujuan mendeskripsikan pelaksanaan revitalisasi plang dan digitalisasi informasi homestay melalui Google Sites yang terintegrasi dengan QR-Code. Metode yang digunakan adalah deskriptif kualitatif melalui observasi, pendataan, dokumentasi, dan sosialisasi kepada pemilik homestay, melibatkan delapan mahasiswa KKN dan masyarakat. Dari 22 homestay teridentifikasi, 14 di antaranya aktif dan layak ditindaklanjuti. Kegiatan menunjukkan peningkatan visibilitas dan keterbacaan plang melalui pengecatan ulang dan penebalan identitas visual. Digitalisasi melalui katalog daring memudahkan akses terhadap fasilitas, tarif, lokasi, dan kontak homestay. Sosialisasi pemilik homestay turut meningkatkan literasi digital dan kemampuan pemanfaatan teknologi untuk promosi. Temuan ini menegaskan bahwa intervensi partisipatif dan berbasis teknologi mampu memperkuat citra wisata desa serta mendorong kemandirian masyarakat, dan berpotensi direplikasi pada desa wisata lain yang memiliki kebutuhan serupa.
Generation of Batik Cual Bangka Belitung Motif Variations Using Stable Diffusion Models Rakha Piadika; Zikri Wahyuzi; Arvi Pramudyantoro
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.3215

Abstract

Batik Cual Bangka Belitung is a visual cultural heritage characterized by repetitive motifs, fine line details, and high ornament complexity, presenting significant challenges for digital exploration without compromising its visual identity. This study aims to generate variations of Batik Cual motifs using a prompt-guided image-to-image (img2img) approach based on the Stable Diffusion model with a single-reference image. Furthermore, the research analyzes the influence of the strength parameter on the delicate balance between structural similarity and generative visual variation. The dataset consists of 13 independently collected Batik Cual motifs, pre-processed through RGB conversion and standardized to a resolution of 512×512 pixels. Controlled experiments were conducted using varied strength values of 0.4, 0.6, and 0.8, while maintaining other parameters constant. Quantitative evaluation utilized the Structural Similarity Index Measure (SSIM) to assess structural integrity and CLIP similarity to measure semantic alignment between the prompt and output image. The results indicate that increasing strength consistently decreases SSIM values, signifying greater structural deviation from the reference image, whereas CLIP similarity remains relatively stable across configurations. Quantitatively, a strength of 0.4 offers the optimal combination of structural similarity and semantic suitability. However, qualitative assessments reveal that for certain motifs, a strength of 0.6 produces a more balanced variation between pattern innovation and motif character preservation. These findings confirm a measurable trade-off between identity preservation and generative exploration, demonstrating the potential of Stable Diffusion as a controlled method for developing Batik Cual digital assets.
Integration of Artificial Intelligence Models into a Flask-Based Web Application for Classification and Generation of Batik Cual Motifs from Bangka Belitung Syifa Nandini Girfita; Muhammad Ressi Rabsanjani; Zikri Wahyuzi; Rike Pradila
Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i2.3225

Abstract

Artificial Intelligence (AI) has been increasingly adopted to support digital preservation and creative exploration of cultural heritage. However, many existing studies primarily focus on model development, while limited attention is given to the practical integration and deployment of AI models in real-world applications. This study presents the integration of AI models into a web-based application using the Flask framework for Batik Cual motif classification and generation. The proposed system enables users to interact with AI functionalities through a browser-based interface, supporting motif classification from uploaded images and motif generation based on textual input and reference images. The integration is implemented using a RESTful backend architecture, where Flask manages request handling, preprocessing, AI inference workflows, postprocessing, and result visualization. Functional testing results indicate that the system operates according to its intended design, providing structured outputs with acceptable response times. The findings demonstrate that Flask is an effective and practical framework for deploying AI-driven web applications, particularly for prototype-scale systems aimed at supporting digital preservation and dissemination of traditional cultural motifs.
Early Fire Detection Using IoT and Deep Learning Syandhu Dea Fermanda; Zikri Wahyuzi; Arvi Pramudyantoro
Journal of Informatics and Vocational Education Vol. 9 No. 3 (2026): November 2026
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i3.3515

Abstract

Fire incidents in strategic facilities such as weapon storage rooms can cause severe damage, threaten personnel safety, and disrupt operational readiness. Conventional fire detection systems generally rely on smoke or temperature sensors, which often respond only after hazardous conditions reach a certain threshold. Therefore, this study proposes an early fire prevention system based on Internet of Things (IoT) and deep learning using CCTV cameras. The system was developed using the System Development Life Cycle (SDLC) with the Waterfall model. The object detection model employed YOLOv8 and was trained on a laptop before being deployed to a Raspberry Pi 5 as the real-time processing unit. The implemented hardware consisted of a Raspberry Pi 5, a Logitech webcam, monitor, keyboard, and mouse. Testing was conducted in a room measuring 6 m × 4 m × 3.5 m. The developed system successfully detected four object classes, namely fire, smoke, cigarette, and person. The implemented logic mechanism classified fire detection as a fire incident, while simultaneous cigarette and smoke detection was categorised as smoking activity with potential fire risk. In addition, the system successfully sent automatic warning notifications through Telegram, enabling faster response without continuous manual monitoring. The results indicate that combining YOLOv8, Raspberry Pi 5, and IoT communication can provide an effective, practical, and low-cost intelligent fire prevention solution for indoor strategic facilities.
Face Recognition-Based Attendance System for Village Officials Using YOLOv8n, ArcFace, and Web-Based Microservice Architecture Wenni Siswanti; Zikri Wahyuzi; Arvi Pramudyantoro
Journal of Informatics and Vocational Education Vol. 9 No. 3 (2026): November 2026
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i3.3516

Abstract

The attendance system at Bencah Village has been conducted manually, creating vulnerability to data manipulation, recording errors, and lack of transparency in managing village official attendance data. This study aimed to design and develop a face recognition-based attendance system for Bencah Village officials using deep learning technology, implemented as a web-based platform. The system was developed using the Waterfall Software Development Life Cycle (SDLC) model with a layered microservice architecture, integrating face detection using the lightweight YOLOv8n model, face feature extraction using InsightFace buffalo_l with the ArcFace approach generating 512-dimensional embedding vectors, and identity matching using cosine similarity with a threshold of 0.5. The backend was built with Laravel 12 and Python Flask, containerized using Docker and communicating via REST API. Functional testing using the black-box testing method on 25 main system functions confirmed that all functions performed as expected. Face recognition performance evaluation on 30 test data yielded a Recognition Accuracy of 93.33%, a False Acceptance Rate (FAR) of 0%, and a False Rejection Rate (FRR) of 10%. The FAR of 0% confirmed the system successfully prevented unauthorized identity acceptance, which is critical for attendance data integrity. These results demonstrate the system is feasible as a biometric attendance solution for village government environments.
Co-Authors Abela Ayu Lusianty Alviola Mawar Tifani Alya Rahmadea Arvi Pramudyantoro Juliana Juliana Kiranda Kiranda Muhammad Alfajri Muhammad Ressi Rabsanjani Nova Febriyanti Nurtri Oktavia Perawati Perawati Rakha Piadika Rike Pradila Rio Ferdiansyah Sri Widari Ainantia Suhendri Suhendri Syandhu Dea Fermanda Syifa Nandini Girfita Wenni Siswanti