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Dewi Purnamasari
Universitas Ivet
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Pelatihan Pembuatan Prototype Palang Parkir Otomatis Berbasis Internet of Things Purnamasari, Dewi; Jumrianto; Didin Herlinudinkhaji; Henny Prasetyani; Riffa Bella Wahyu
TEMATIK Vol. 5 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/tematik.v5i2.12243

Abstract

SMA PGRI 1 Kendal menghadapi masalah rendahnya pemahaman siswa tentang Internet of Things (IoT), khususnya dalam membangun sistem palang parkir otomatis. Hal ini disebabkan belum adanya mata pelajaran khusus maupun modul pembelajaran IoT di sekolah. Untuk mengatasi hal tersebut, Tim Pengabdian UniversitasIvet melaksanakan pelatihan pembuatan palang parkir otomatis berbasis IoT menggunakan Arduino UNO dalam bentuk prototype. Kegiatan ini bertujuan memberikan simulasi pembelajaran IoT kepada siswa melalui metode ceramah, diskusi, bimbingan, dan praktik langsung. Hasil kegiatan meliputi penyampaian materi, perakitan perangkat sesuai modul, pemrograman Arduino, dan penyerahan produk ke sekolah. Evaluasi menunjukkan peningkatan pemahaman siswa sebesar 80% setelah pelatihan, meskipun terdapat satu kelompok yang gagal membuat prototype. Secara keseluruhan, kegiatan dinilai berhasil berkat dukungan peserta, guru, dan kepala sekolah dalam meningkatkan literasi dan keterampilan siswa di bidang teknologi IoT
Energy-Saving Handwasher Design Using Infrared Obstacle Sensor Based On Arduino Microcontroller Jumrianto Jumrianto; Dewi Purnamasari
Jurnal Inovasi Pendidikan dan Sains Vol 5 No 3 (2024): December
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Nahdlatul Wathan Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51673/jips.v5i3.2292

Abstract

The Covid-19 pandemic is over, the good habit of washing hands with soap must be maintained, because it concerns a clean and healthy lifestyle. The unavailability of automatic hand washing devices on the IVET University Campus is a motivation to create an application tool, in its application it will use an infrared obstacle sensor by coding commands through Arduino software. Based on a review of previous research, no one has designed a hand washer device with an energy-efficient infrared obstacle sensor. Utilizing Arduino software and hardware with a current consumption of <0.050 amperes on standby. When operating, this device consumes a current of <0.5 amperes which opens and closes the water tap. The operating voltage of the microcontroller is 5 volts, so this device consumes 2.5 watts of electricity, and if it operates for 1000 hours or for ±41 days continuously without stopping, it only uses 2.5 KWh of electricity and when on standby for 1000 hours this device uses 0.25 KWh of electricity.
Rancang Bangun Sistem Informasi Survei Kepuasan Pelanggan Berbasis Web menggunakan Metode Prototype (Studi Kasus Pada Toko Audi Elektronik Semarang) Dinda Resti Octaviana; Dewi Purnamasari; Kurniawati Kurniawati
Joined Journal (Journal of Informatics Education) Vol 8 No 1 (2025): Volume 8 Nomor 1 (2025)
Publisher : Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/joined.v8i1.3895

Abstract

Toko Audi Elektronik Semarang merupakan toko ritel yang bergerak di bidang penjualan barang elektronik belum memiliki sistem untuk mengumpulkan umpan balik pelanggan, baik melalui kotak saran maupun survei kepuasan pelanggan sehingga menyulitkan mengevaluasi kualitas layanan dan produk. Penelitian ini bertujuan untuk merancang dan membangun sistem informasi survei kepuasan pelanggan berbasis web bertujuan untuk mempermudah proses pengumpulan, penyimpanan, dan analisis data kepuasan pelanggan secara lebih sistematis dan terstruktur. Metode yang digunakan adalah metode prototype berdasarkan masukan pengguna. Pengujian sistem dilakukan dengan metode black box testing difokuskan pada aspek fungsionalitas. Hasil pengujian menunjukkan bahwa seluruh fungsi utama pada sistem, seperti pengisian survei, penyimpanan data, dan penampilan hasil survei, berjalan sesuai dengan skenario yang telah dirancang. Dengan demikian, sistem ini dinilai telah memenuhi aspek fungsional yang dibutuhkan dan siap digunakan sebagai sarana untuk mendukung evaluasi layanan dan pengambilan keputusan berdasarkan umpan balik pelanggan.
Deepfake Image Detection Using Transfer Learning Method Tsalatsatun Nur Rohmah; Dewi Purnamasari; Kurniawati Kurniawati; Didin Herlinudinkhaji; Yunifa Miftachul Arif; Santiago Criollo-C
International Journal of Electrical and Intelligent Engineering Vol 1, No 2 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i2.40796

Abstract

The development of Artificial Intelligence (AI) technologies, particularly deep learning has led to the emergence of innovative applications such as deepfake technology, which enables the realistic manipulation of digital images and videos. While this technology offers positive applications in fields such as entertainment and education, it also poses significant risks of misuse, particularly in the dissemination of false information and violations of privacy. Therefore, deepfake detection has become a crucial aspect in preserving the authenticity of digital content. This study aims to analyze the effectiveness of transfer learning methods in detecting deepfake images using VGG16, VGG19, and ResNet50 architectures. The research employs a dataset of deepfake and real images sourced from Kaggle, comprising 10,826 facial images with a resolution of 256 × 256 pixels, evenly balanced between authentic and manipulated content. The data are split in an 80:20 ratio for training and testing purposes. Each model is trained using identical parameter configurations. The performance evaluation of the models was conducted using confusion matrix metrics, including accuracy, precision, recall, and F1-score. The results indicate that the VGG16 model achieved the best performance, with an accuracy of 76%, followed by VGG19 at 72%, and ResNet50 at 58%. VGG16 also outperformed the other models in terms of precision, recall, and F1-score, demonstrating more effective performance in identifying visual manipulation patterns. In contrast, ResNet50 exhibited the lowest performance, which may be attributed to its architectural complexity not being optimally aligned with the characteristics of the dataset. It can be concluded that the transfer learning approach using the VGG16 model is more effective in detecting deepfake images on this dataset. This study also highlights the importance of selecting appropriate architectures and fine-tuning models to the characteristics of the data.
Co-Authors Aeni Nikhlah Ahmad Riki Andreas Akhmad Nayazik Didin Herlinudinkhaji, Didin Dinda Resti Octaviana Handini Arga Damar Rani Isti Mulyawati Jumrianto Jumrianto Jumrianto Jumrianto Jumrianto Jumrianto, Jumrianto Kurniawati Kurniawati Kurniawati Kurniawati lenny kurniati, lenny Lingga Kurnia Ramadhani Masruroh, Nila Masalikul Nindita Erwanti Prasetyani, Henny Riffa Bella Wahyu Santiago Criollo-C Sri Widayati Sudomo, R. Irlanto Tsalatsatun Nur Rohmah Yunifa Miftachul Arif