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Sistem Absensi Otomatis Menggunakan RFID dan ESP32-CAM dengan Real-Time Notification Azmi, Falah Ilhan; Ujianto, Erik Iman Heri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9312

Abstract

Masih banyak sekolah di Indonesia yang menerapkan sistem absensi manual, seperti mencatat kehadiran siswa menggunakan tanda tangan di atas kertas. Metode ini dinilai kurang efisien, memakan waktu, serta rentan terhadap kecurangan seperti titip absen atau pemalsuan data. Untuk mengatasi permasalahan tersebut, penelitian ini mengembangkan sistem absensi otomatis berbasis Internet of Things (IoT) dengan menggunakan teknologi Radio Frequency Identification (RFID) dan ESP32-CAM. Sistem ini memanfaatkan kartu RFID sebagai identitas unik siswa dan ESP32-CAM sebagai verivikasi visual berupa pengambilan foto saat absensi dilakukan. Peneitian ini menggunakan metode rekayasa perangkat lunak yang mencakup analisis kebutuhan, perancangan sistem, implementasi, dan pengujian sistem. Hasil sementara menunjukan bahwa sistem ini mampu mencatat kehadiran siswa secara otomatis dan real-time, serta menyimpan bukti kehadiran dalam bentuk gambar, sehingga meningkatkan efisiensi dan meminimalisir potensi kecurangan. Sistem juga menyediakan notifikasi ke orang tua melalui Whatsapp sebagai bentuk transparansi kehadiran siswa
Sistem Pengelolaan Inventori Real-Time untuk UMKM Berbasis Flutter dan QR Code Menggunakan Metode R&D Saputra, Faiz; Ujianto, Erik Iman Heri
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9309

Abstract

The efficiency and accuracy of stock recording in MSMEs are enhanced through the development of a mobile-based inventory management application, addressing the challenges of manual systems, which are prone to human error and data delays. This study implements a real-time system by integrating three key technologies: Flutter as a cross-platform framework for efficient development, QR Codes for rapid item identification, and Firebase as a database for instant data synchronization. By applying the R&D method through the Waterfall model, the application was developed and tested in a case study at Warung Laras. The application is equipped with essential features for daily operations, including security verification using OTP via WhatsApp, unique QR code generation for each item, and the ability to automatically generate inventory reports in PDF format. The results from Black Box testing and user trials show a significant quantitative impact: data recording accuracy increased to 95%, while the average time per transaction was drastically reduced by 70%, from approximately 30 seconds to just 9 seconds. This finding proves that the technological integration has successfully created a reliable and effective solution to drive digital transformation in MSME-scale stock management
MENUJU TATA KELOLA KEPEGAWAIAN YANG EFEKTIF: ANALISIS DAN PERANCANGAN SISTEM DI KECAMATAN GIRINTONTRO, WONOGIRI Sujoko, Sujoko; Darmawan, Surya; Dewanto, Aditya Dimas; Sujarwadi, Agus; Ujianto, Erik Iman Heri; Mahardhika, Chaidar Panji
Amare Vol. 4 No. 2 (2025): Juli - Desember 2025
Publisher : Sekolah Tinggi Agama Katolik Negeri Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52075/sh0bkw35

Abstract

Pengelolaan kepegawaian di Kecamatan Giritontro masih dilakukan secara manual, yang menimbulkan berbagai kendala seperti keterlambatan proses administrasi, kesulitan pencarian data, serta tingginya risiko inkonsistensi dan ketidakakuratan data. Untuk mengatasi permasalahan tersebut, kegiatan pengabdian kepada masyarakat ini bertujuan menganalisis dan merancang sistem manajemen kepegawaian kecamatan guna meningkatkan efisiensi dalam pengelolaan data aparatur. Metode yang digunakan meliputi analisis kebutuhan melalui observasi dan wawancara untuk mengidentifikasi permasalahan utama. Selanjutnya dilakukan perancangan alur informasi menggunakan Data Flow Diagram (DFD), serta perancangan basis data dengan Entity-Relationship Diagram (ERD) guna memastikan sistem mampu menyimpan dan mengelola data pegawai secara terstruktur. Rancangan mencakup fitur utama seperti pencatatan data pegawai, pengelolaan jabatan, penilaian kinerja, serta riwayat mutasi dan pengangkatan. Selain itu, dibuat desain antarmuka untuk menggambarkan interaksi pengguna dengan sistem. Hasil dari perancangan ini diharapkan dapat menjadi acuan pengembangan sistem digital kepegawaian di Kecamatan Giritontro, sehingga pengelolaan kepegawaian dapat berjalan lebih optimal, efektif, dan efisien, serta mendukung peningkatan kualitas layanan administrasi di lingkungan pemerintahan kecamatan.
Mobile Based E-Commerce Application with Whatsapp Notification for Transactions Tuasikal, Afrizal Halim Naindhy; Ujianto, Erik Iman Heri
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 9 No. 1 (2026): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v9i1.55662

Abstract

Online shopping has become an essential part of modern society. Various e-commerce platforms have emerged offering a wide range of products, yet most still focus primarily on selling new items. In fact, there is a growing need for a platform that can accommodate both new and used goods transactions within a single, user-friendly application. Moreover, many existing platforms lack direct integration with instant messaging services such as WhatsApp, resulting in delayed transaction information and potentially leading to miscommunication. To address these challenges, a mobile-based e-commerce application was developed using Flutter as the frontend framework, Flask as the backend API, and MySQL as the database. The main advantage of this application lies in its automatic WhatsApp integration, which enables real-time transaction notifications. Testing results show that the application functions properly and remains stable. The main features include registration, login, product addition, and product listing, along with additional features such as favorites marking, live streaming, and automatic WhatsApp notifications. This application is expected to serve as an effective solution to overcome current platform limitations and to support efficient and convenient buying and selling of both new and used goods.
Face Detection Based on Anti-Spoofing with FaceNet Method for Filtering Contract Cheating in Online Exam Ujianto, Erik Iman Heri; Diyasa, I Gede Susrama Mas; Junaidi, Achmad; Fatullah, Ryan Reynickha; Permanasari, Wahyu Melinda; Sari, Allan Ruhui Fatmah
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1167

Abstract

This study develops a reliable face-based verification system for online examinations by integrating a face recognition model with a blink detection mechanism to minimize the risk of identity fraud, also known as "contract cheating," and static image manipulation. "Contract cheating" refers to the practice where students hire others to complete their exams or assignments, compromising academic integrity. The growing reliance on online exams has raised concerns about the credibility of facial verification, as conventional methods are often vulnerable to spoofing attempts. To address this issue, the proposed system combines FaceNet, a deep learning model for identity recognition, with Dlib’s eye blink detection to provide a stronger layer of protection. The system was evaluated using 5-fold and 10-fold K-fold cross-validation, and additional testing assessed the impact of different video frame rates on performance. The results show that the system performs effectively in identifying legitimate users and detecting spoofing. FaceNet achieved an accuracy of 96.67 percent, outperforming DeepFace, which showed poorer results in precision, recall, and F1 score for some participants. Both models were evaluated on the same dataset, consisting of 150 images. The preprocessing pipeline, including face detection using MTCNN, cropping, and resizing, was applied consistently to both models to ensure a fair comparison of their performance. The system also demonstrated adaptability, achieving correct classifications at both 15 and 30 frames per second. Anti-spoofing tests based on the eye blink detection system detected all real faces, while static images were classified as spoofing. These results confirm that combining face recognition with liveness detection enhances the security of online examination platforms. The findings demonstrate the system's potential to reduce contract cheating and impersonation fraud, making online examinations more credible. Future work may focus on implementing adaptive thresholding for blink detection and integrating multimodal verification techniques to improve robustness across diverse real-world environments.
BATINARA: Hybrid LLM-BERT-ML Chatbot for Safe Mental Health Support Walangitan, Jeanette; Ujianto, Erik Iman Heri
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 20, No 2 (2026): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.112432

Abstract

This study addresses the pressing need for safe and personalized digital mental health support by mitigating the inherent risk of Large Language Models (LLMs) generating unsafe or unethical responses during high-risk psychological crises. We developed BATINARA, a chatbot system based on a Neuro-Symbolic Hybrid framework. This architecture integrates a Predictive Module (IndoBERT for crisis detection, Random Forest for multi-label emotion classification) with a Generative LLM Module (OpenAI API). Ethical control is enforced by the Dynamic Context Integration Logic (D-CIL), which utilizes clinical rules to uphold the Principle of Nonmaleficence. Key results demonstrate the system’s ability to: (1) Enforce safety protocols through the automatic override of LLM responses when suicidal ideation is detected (Recall IndoBERT 0.9977). (2) Achieve high contextual accuracy in multi-label emotion detection (F1 = 0.94), which supports dynamic personalization via Dynamic Prompt Modulation based on specific therapeutic styles and user PHQ-9/GAD-7 clinical scores. (3) Enhance interaction transparency through the real-time visualization of detected emotions. This Neuro-Symbolic hybrid approach proves effective in mitigating clinical risks associated with generative AI, resulting in adaptive and ethically sound therapeutic interactions.