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All Journal Building of Informatics, Technology and Science Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Septiani, Karlina Dwi
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Computer Science & IT

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Implementasi Transfer Learning Menggunakan Convolutional Neural Network untuk Deteksi Jenis Kulit Wajah Septiani, Karlina Dwi; Subhiyakto, Egia Rosi
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6154

Abstract

In Indonesia, extreme tropical climate conditions with high humidity and sun exposure increase the risk of facial skin problems for the community. Facial skin that is not properly cared for is often prone to disorders, ranging from dry skin, oily skin, to acne. However, Indonesian people's awareness of the importance of maintaining healthy skin is still relatively low, which is exacerbated by limited time and access to consult a dermatologist. Most people may not know their skin type, even though each skin type requires different care to stay healthy and avoid more serious skin problems. To answer this problem, this study aims to develop an iOS-based application that is able to automatically detect facial skin types using transfer learning with a Convolutional Neural Network (CNN) architecture. The model was developed by training a dataset of facial images to classify skin types such as dry, oily, normal, and acne-prone, and integrated into an iOS application for real-time analysis through user facial images. The evaluation results showed a model accuracy of 87% and an application accuracy of 83.3% in identifying facial skin types. It is hoped that this application will help Indonesian people better understand their skin conditions and obtain appropriate treatment recommendations to maintain healthy skin in a tropical climate.
Implementasi Firebase Realtime Pada Aplikasi Self-Order Restoran Berbasis iOS Triginandri, Rifqi; Septiani, Karlina Dwi; Subhiyakto, Egia Rosi; Rakasiwi, Sindhu; Astuti, Yani Parti
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol 5, No 04 (2024): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v5i4.10680

Abstract

Perkembangan teknologi aplikasi memberikan dampak signifikan pada gaya hidup masyarakat modern, terutama dengan hadirnya aplikasi inovatif seperti Pick 'n Serve yang mengatasi antrian di restoran melalui platform mobile iOS. Dikembangkan dengan Firebase Realtime Database, aplikasi ini memastikan akses real-time terhadap informasi menu, pesanan, dan ketersediaan. Integrasi model bisnis, perhatian terhadap kebutuhan pelanggan, dan penerapan metode pengembangan Waterfall membuat Pick 'n Serve berhasil meningkatkan efisiensi dan pengalaman pemesanan. Metode Waterfall memberikan struktur pengembangan terorganisir dengan langkah-langkah jelas dari perencanaan hingga implementasi. Hasil pengujian mencerminkan kinerja baik, memudahkan pengguna dalam pemesanan, dan efektif mengurangi antrian di restoran. Skor tinggi dari uji penerimaan pengguna (UAT) mencerminkan penerimaan positif terhadap aplikasi ini. Dengan memanfaatkan teknologi Firebase dan pendekatan pengembangan yang terstruktur, Pick 'n Serve diharapkan memberikan kontribusi positif terhadap efisiensi operasional, kepuasan pelanggan, dan pertumbuhan bisnis restoran dalam era digital, menjadikannya solusi holistik untuk adaptasi terhadap perubahan kebutuhan konsumen dan tuntutan pasar yang terus berkembang.
Co-Authors Astuti, Yani Parti Egia Rosi Subhiyakto, Egia Rosi Sindhu Rakasiwi Triginandri, Rifqi