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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Komputer dan Elektro Sains Jejak digital: Jurnal Ilmiah Multidisiplin
Hazna At Thooriqoh
Universitas Pembangunan Nasional Veteran Jawa Timur
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences Other

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DIGITALISASI TATA KELOLA KEUANGAN UMKM LAUNDRY: IMPLEMENTASI & SOSIALISASI APLIKASI 1010DRY PADA FND LAUNDRY EXPRESS Hazna At Thooriqoh; Dimas Nugroho Dwi Seputro
BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Vol. 6 No. 1 (2026): BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Juni 2026
Publisher : LPPM UNIKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/bhakti_nagori.v6i1.5576

Abstract

UMKM FnD Laundry Express menghadapi kendala serius dalam tata kelola keuangan dan operasional akibat sistem pencatatan yang masih manual. Hal ini memicu berbagai masalah seperti risiko human error, inefisiensi waktu rekapitulasi, potensi kecurangan (fraud), hingga lemahnya analisis bisnis karena data tidak real-time. Kegiatan pengabdian masyarakat ini bertujuan untuk menyelesaikan permasalahan tersebut melalui digitalisasi manajemen keuangan menggunakan aplikasi 1010dry. Metode pelaksanaan mencakup observasi lapangan, sosialisasi urgensi digitalisasi, pelatihan operasional aplikasi, dan pendampingan implementasi. Hasil pengabdian menunjukkan adanya transformasi operasional yang signifikan; nota fisik beralih menjadi nota digital via WhatsApp, proses rekapitulasi omzet yang sebelumnya memakan waktu 2-3 jam per hari kini berjalan otomatis dan real-time. Aplikasi 1010dry yang berbasis cloud (Point of Sales) mampu menyederhanakan ekosistem bisnis mulai dari kasir, produksi, hingga dashboard admin. Kesimpulannya, implementasi ini berhasil menciptakan akurasi finansial mutlak (100% otomasi laporan) dan meningkatkan transparansi antara kasir dan pemilik usaha. Digitalisasi ini tidak hanya mengefisienkan biaya dan waktu operasional, tetapi juga memberikan pondasi sistem yang terukur bagi FnD Laundry Express untuk melakukan scale-up bisnis di masa depan.
Rupiah Classification System using Segmented Fractal Texture Analysis and HSV Color Features Ardhon Rakhmadi; Putri Nur Rahayu; Hazna At Thooriqoh; Budi Mukhamad Mulyo
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 2 (2025): September 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i2.560

Abstract

The crime of forgery of rupiah currency can be anticipated by examining the rupiah banknotes based on traits or features contained on the original paper money. Features that are not owned by the rupiah banknote counterfeit is an ultraviolet sign that are owned by the original paper money. Rupiah banknotes feature extraction consists of a combination of color and texture feature extraction. The proposed method is the HSV color histogram for color feature extraction and Segmented Fractal Texture Analysis (SFTA) for texture feature extraction. The combination of HSV and SFTA is expected to improve the performance of rupiah banknotes feature extraction. Moreover this paper will analyze feature redundancy in Two Threshold Decomposition Algorithm in SFTA Algorithm. Experimental results show the proposed method can reach 100% accuracy. Experiment results also show that redundant features can be removed without affecting the accuracy of of the system so that it can reduce the computational cost.
Implementasi Dashboard Multi-Role pada Sistem Afiliasi dan Marketplace Berbasis Web PT. BIZHUB DIGITAL INDONESIA Bayu Setiawan; Rajawali Shaktika Anugrah Prasetya; Andra Husnul Azmi; Hazna At Thooriqoh
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 4 (2026): JUNI-JULI
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/jx1t2766

Abstract

Digital marketing encourages companies to adopt systems capable of managing transactions, affiliate partners, commissions, and performance reports within a single integrated platform. Previously, PT Bizhub Digital Indonesia relied on third-party platforms to operate its affiliate marketing activities. This condition limited the company's flexibility in managing workflows, monitoring affiliate performance, and independently handling commission disbursements. This study aims to implement a multi-role dashboard within a web-based affiliate and marketplace system. The system was designed to accommodate three primary user roles: Admin, Member/Affiliator, and Customer. The research methodology consisted of requirements analysis, system design using use case diagrams, activity diagrams, and sequence diagrams, web-based interface implementation, and functional testing through the black-box testing method. The implementation results demonstrate that the multi-role dashboard effectively separates system functionalities according to user access privileges. Administrators are able to manage products, categories, transactions, affiliate data, ratings, and commission withdrawals. Members/Affiliators can generate affiliate links, monitor referral transactions, track commission balances, and submit withdrawal requests. Customers can browse product catalogs, complete purchases, view order histories, manage profiles, and provide product ratings. The testing results indicate that all major system features functioned according to the predefined test scenarios. Therefore, the implemented multi-role dashboard supports the management of affiliate and marketplace systems in a more structured, transparent, and operationally efficient manner, while meeting the specific business requirements of the company.
Empirical Performance Analysis of BST and AVL Tree on Modern Computing Architectures: A Stress Test Study Under Varying Data Distributions Hazna At Thooriqoh; Ibnu Khoirul Anwar; Dimas Nugroho Dwi Seputro
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5628

Abstract

Binary Search Tree (BST) and AVL Tree are fundamental data structures widely used for dynamic data management in performance-critical systems. Although both structures offer efficient theoretical complexity, their practical performance on modern systems is highly influenced by data distribution and workload characteristics. This study presents an empirical performance evaluation of BST and AVL Tree using a stress-test approach based on a game leaderboard system as a representative case study. Multiple workload patterns were simulated, including random, sequential (ascending and descending), and clustered data distributions, to reflect realistic high-frequency updates commonly observed in modern applications. Experimental results show that BST achieves slightly better performance under random data distributions due to the absence of balancing overhead. However, BST experiences severe performance degradation under sequential inputs, where it degenerates into an unbalanced structure. In contrast, the AVL Tree consistently maintains logarithmic height, achieving speedups of up to 32x compared to BST in worst-case scenarios.These findings indicate that while BST can be effective under controlled average-case conditions, AVL Tree provides superior robustness and predictable performance under non-uniform and adversarial workloads. For modern high-load systems such as game leaderboards, the balancing overhead of AVL Tree represents a minimal trade-off compared to the substantial stability and performance guarantees it offers.
Fusi Metadata dan Masked Mean–Max Pooling dengan DeBERTa-v3 untuk Klasifikasi Tweet Bencana Budi Mukhamad Mulyo; Hazna At Thooriqoh; Ardhon Rakhmadi; Devi Ambarwati Puspitasari; Bayu Permana Sukma
Jurnal Komputer dan Elektro Sains Vol. 4 No. 2 (2026): Komets
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/komets.v4i2.662

Abstract

Klasifikasi tweet terkait bencana merupakan permasalahan penting dalam pemrosesan bahasa alami karena teks media sosial cenderung pendek, tidak baku, dan sering ambigu. Namun, pemanfaatan metadata dan optimasi ambang keputusan secara terpadu pada model transformer masih terbatas. Penelitian ini mengembangkan model klasifikasi biner dengan mengintegrasikan representasi kontekstual DeBERTa-v3, kata kunci, lokasi, dan metadata numerik tweet. Dataset terdiri atas 7.613 data latih dan 3.263 data uji. Teks dibentuk menjadi masukan terstruktur menggunakan penanda kata kunci, lokasi, dan isi tweet. Representasi token dipadatkan melalui masked mean–max pooling, kemudian digabungkan dengan fitur numerik. Model dilatih menggunakan stratified cross-validation, multi-sample dropout, dan optimasi threshold berdasarkan probabilitas out-of-fold. Kebaruan penelitian terletak pada demonstrasi empiris kontribusi metadata fusion, masked mean–max pooling, dan optimasi threshold berbasis out-of-fold dalam melengkapi representasi kontekstual DeBERTa-v3, yang diperkuat melalui evaluasi ablation terkontrol. Pengujian terhadap 15 konfigurasi menunjukkan bahwa DeBERTa-v3 metadata fusion dengan 3-fold out-of-fold ensemble menghasilkan skor F1 tertinggi sebesar 0,84063, melampaui DeBERTa-v3 metadata fusion dengan holdout sebesar 0,83971, DeBERTa-v3 mean–max sebesar 0,83695, DistilBERT sebesar 0,83450, dan GloVe–SVM sebesar 0,81581. Hasil ini menunjukkan bahwa integrasi metadata dan penentuan threshold berbasis out-of-fold efektif meningkatkan kinerja klasifikasi. Penelitian ini berpotensi mendukung penyaringan informasi bencana dari media sosial secara lebih akurat.
Co-Authors Andra Husnul Azmi Ardhon Rakhmadi Ardhon Rakhmadi Bayu Permana Sukma Bayu Setiawan Budi Mukhamad Mulyo Devi Ambarwati Puspitasari Dimas Nugroho Dwi Seputro Dimas Nugroho Dwi Seputro Ibnu Khoirul Anwar Putri Nur Rahayu Rajawali Shaktika Anugrah Prasetya