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Augmented Reality dan Virtual Reality sebagai Media Promosi Sekolah berbasis Android Fitrianto, Yuli; Susatyono, Jarot Dian; Wahyudi, Wiwid
Krea-TIF: Jurnal Teknik Informatika Vol 10 No 1 (2022)
Publisher : Fakultas Teknik dan Sains, Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/krea-tif.v10i1.7087

Abstract

Media promosi sekolah berupa brosur tidak dapat menampilkan bangunan sekolah yang layak sehingga dibutuhkan media lain yang dapat menampilkannya secara lengkap dan dapat menarik calon siswa untuk mendaftar ke sekolah. Dengan potensi dimana hampir semua orang saat ini memiliki smartphone, maka solusi yang paling tepat adalah membangun aplikasi android yang menerapkan teknologi Augmented Reality (AR) dan Virtual Reality (VR) dengan memanfaatkan brosur yang telah ada sebagai marker dari AR-nya. Pembuatan AR dengan menggunakan software Unity3D, dengan plugin Vuforia sebagai tempat database markernya, sedangkan pemodelan objek 3D yang akan dimunculkan di atas marker, dibuat dengan software Google SketchUp. AR memunculkan objek gedung sekolah yang dapat dilihat atau diputar ke segala arah dan VR memungkinkan user untuk jalan-jalan secara virtual ke dalam gedung sekolah. Rangkaian pengujian memperoleh nilai 3.1 untuk performance, 3.84 untuk usability, 2.44 untuk compatibility, dan memperoleh hasil nilai rata-rata 3.1 dari nilai total 4 termasuk kategori sangat baik.
Designing User Experience for a Mobile Application for Agricultural Product Marketing Using the Human-Centered Design Method Yunianto, Irdha; Wahyudi, Wiwid
International Journal of Graphic Design Vol. 2 No. 2 (2024): December: International Journal of Graphic Design
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/ijgd.v2i2.2123

Abstract

This research explores the application of Human-Centered Design (HCD) in developing a mobile application for agricultural product marketing, aiming to address critical challenges faced by farmers, such as limited market access and inconsistent internet connectivity. By involving farmers and consumers in each stage of the design process, the application was iteratively improved based on user feedback. The study implemented low-fidelity and high-fidelity prototyping, with five iterations of user testing to enhance usability, navigation, and accessibility. Results show a significant increase in task success rates, user satisfaction, and application efficiency, mainly by including offline features for users in areas with poor internet infrastructure. The study also highlights the effectiveness of HCD in adapting technology to local conditions, offering a practical solution that supports the digital transformation of the agricultural sector, particularly in rural areas. This research contributes to the literature by demonstrating that HCD can be effectively used to develop user-friendly applications that meet the specific needs of the agricultural community
Design of an Environmental-Friendly Supplier Selection DSS Model using AHP-TOPSIS Bunga, Harley; Wahyudi, Wiwid
Jurnal Ilmiah Sistem Informasi Vol. 4 No. 1 (2025): Januari : Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/b8wpb307

Abstract

Hasil penelitian menunjukkan bahwa model Decision Support System (DSS) berbasis kombinasi Analytical Hierarchy Process (AHP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) mampu memberikan hasil evaluasi supplier yang objektif dan konsisten. Dari hasil perhitungan, kriteria Harga memperoleh bobot tertinggi sebesar 42,31%, diikuti oleh Waktu Pengiriman dan Layanan masing-masing 22,72%, serta Kualitas sebesar 12,25%. Peringkat akhir menunjukkan bahwa Supplier A memiliki nilai kedekatan tertinggi terhadap solusi ideal, menandakan keseimbangan terbaik antara efisiensi biaya dan kinerja non-finansial. Implementasi dalam bentuk dashboard interaktif terbukti mempermudah manajemen dalam memahami hasil analisis serta mempercepat proses pengambilan keputusan. Penelitian ini membuktikan bahwa integrasi metode AHP-TOPSIS dapat digunakan secara efektif sebagai alat bantu dalam manajemen pengadaan berbasis data. Namun, penelitian ini masih memiliki keterbatasan pada jumlah responden dan konteks industri yang relatif sempit. Penelitian mendatang disarankan untuk memperluas cakupan sektor industri, menambah jumlah pakar, serta mengintegrasikan model ini dengan teknologi machine learning atau real-time analytics agar sistem pendukung keputusan dapat beradaptasi secara dinamis terhadap perubahan kondisi pasar dan performa supplier.
Resilient Federated Learning Against Injection and Evasion Attacks in Edge Smart Grids: A Simulation Study Wahyudi, Wiwid
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 5 No. 2 (2025): Oktober : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v5i2.1027

Abstract

The modernization of smart grids through edge computing introduces significant cybersecurity challenges, most stemming from adversarial machine learning attacks that compromise distributed intelligence. Although Federated Learning is an appealing decentralized model training paradigm for edge smart grids, its resilience against coordinated injection and evasion attacks has not yet been thoroughly explored. To address this critical gap, we develop and evaluate a resilient Federated Learning model for edge-based innovative grid applications. Under a rigorous simulation-based experimental design, we created a controlled environment based on synthetic energy-demand data and implemented adversarial attack scenarios to ensure model robustness. We propose a resilience enhancement layer in our framework during the federated aggregation process to curtail malicious model updates and adversarial inferences. The results show significant improvement in the stability of the proposed model under attack, maintaining a robustness index above 0.62, whereas baseline approaches exhibit complete degradation. This corresponds to a reduction of approximately 34% in the attack impact rate across different-intensity attack scenarios, while maintaining high stability in aggregation. In addition to the adversarial testing framework in the domain of Federated Learning, this work provides a validated resilience model that secures analytics of smart grids without requiring access to raw data. Our methodology presents a resource-efficient alternative to physical testing and enables safe yet comprehensive security evaluation in critical infrastructure applications.
Pengembangan Aplikasi Cerdas Berbasis AI untuk Analisis Tren Penjualan Produk Fashion Lokal Menggunakan Algoritma Data Mining Yunianto, Irdha; Wahyudi, Wiwid; Indriyani, Novita; Darusyifa F, Muhamad
Jurnal Teknik Informatika dan Elektro Vol 8 No 1 (2026): Jurnal Teknik Elektro dan Informatika
Publisher : Universitas Gajah Putih

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55542/jurtie.v8i1.1644

Abstract

This study develops an AI-driven application for analyzing sales of local fashion products and mapping customer heterogeneity to support marketing decision-making for micro, small, and medium enterprises (MSMEs). A mixed-methods approach is employed, combining a structured literature review, surveys/interviews, and Focus Group Discussions (FGDs) to validate findings and system usability. Quantitatively, first-quarter 2025 transaction data (100 respondents) are analyzed using K-Means on three standardized features age, aggregated number of items purchased, and aggregated spending. Cluster evaluation with the silhouette score for k=2-5 indicates the best separation at k=5, yielding a stable and interpretable segmentation. The resulting profiles reveal at least one high-value segment (larger baskets and higher spending) suitable for tiered loyalty programs and premium bundling; a mid-value segment responsive to targeted cross-sell/upsell offers; and a low-intensity segment that benefits from staged onboarding interventions to improve retention. These insights are integrated into a prototype analytics application that presents a segmentation dashboard and key performance indicators, providing actionable support for MSMEs’ marketing, catalog curation, and inventory allocation.