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All Journal Journal of Information Technology and Computer Science (JOINTECS) JURNAL ILMIAH INFOKOM
Yudhi Raymond Ramadhan
Sekolah Tinggi Teknologi Wastukancana
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics

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PERANCANGAN USER INTERFACE DAN USER EXPERIENCE APLIKASI BERBASIS MOBILE KLINIK KECANTIKAN MENGGUNAKAN METODE DESIGN THINKING (STUDI KASUS : KLINIK KATIA DERMA) Shifa Silfiana; Imam Maruf Nugroho; Yudhi Raymond Ramadhan
INFOKOM (Informatika & Komputer) Vol 11 No 1 (2023): JURNAL INFOKOM JUNI 2023
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v11i1.1052

Abstract

The design of the User Interface and User Experience is very influential for user comfort, so accurate analysis is needed according to user needs. The Katia Derma Clinic is a clinic that is devoted to the treatment of facial skin health care and releases skincare products which are currently planning to create a mobile-based application. With the planning of making the application, the user interface and user experience will be designed first using the Design Thinking method. Testing the results of the design in this study was carried out using the User Experience Questionnaire (UEQ) testing method. Based on the test method used to test the design results in this study, positive results were obtained for all scales, namely the Attractiveness scale with a mean value of 2.028, Efficiency with a mean value of 2.075 and Dependability with a mean value of 1.725 included in the Excellent category, while the Perspicuity scale with a mean value of 1.825, Stimulation with a mean value of 1.525 and Novelty with a mean value of 1.225 are included in the Good category.
Klasifikasi Penyakit Pada Daun dan Buah Jambu Menggunakan Convolutional Neural Network Fadlan Sayyidul Anam; Muhammad Rafi Muttaqin; Yudhi Raymond Ramadhan
JOINTECS (Journal of Information Technology and Computer Science) Vol 8, No 3 (2023)
Publisher : Universitas Widyagama Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jointecs.v8i3.4823

Abstract

Jambu biji merupakan komoditas tanaman di Jawa Barat dengan jumlah produksi tahun 2021 mencapai 692.488 kuintal. Produksi ini mengalami penurunan sebesar -12,82% dibandingkan dengan tahun 2020 yang sebesar 794.345 kuintal. Penelitian menggunakan teknologi deep learning dengan algoritma Convolutional Neural Network (CNN) dan berarsitektur MobileNetV2 untuk melakukan klasifikasi citra digital daun dan buah jambu biji yang telah diberi label atau disebut supervised learning. Metode pengembangan yang digunakan dalam penelitian ini adalah Cross Industry Standard Process for Data Mining (CRISP-DM). Berdasarkan hasil penelitian ini, model daun jambu biji memiliki hasil evaluasi yang sangat baik, training accuracy sebesar 99,6%, validation accuracy 100%, training loss 3,2%, dan validation loss 3,1%. Confusion matrix model ini memiliki akurasi 100% dari 63 data validasi. Sementara itu, model buah jambu biji memerlukan dropout sebesar 0,2 dan kernel regularizers L2 sebesar 0,01 untuk mengurangi overfitting. Model ini memiliki training accuracy sebesar 98,8%, validation accuracy 91,6%, training loss 19,1%, dan validation loss 38,6%. Hasil confusion matrix menunjukkan akurasi model ini mencapai 91,6% dari 84 data validasi. Kemudian model berhasil diimplementasikan menjadi aplikasi berbasis mobile menggunakan bahasa pemrograman Kotlin.
Co-Authors Fadlan Sayyidul Anam Imam Maruf Nugroho Muhammad Rafi Muttaqin Shifa Silfiana