Article Per Year (5 Year)
p-Index From 2019 - 2024
0.562
P-Index
This Author published in this journals
All Journal Journal of Information Technology and Computer Science (JOINTECS) Jurnal Riset Informatika 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

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
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.
Sentiment Analysis of Telemedicine Applications on Twitter Using Lexicon-Based and Naive Bayes Classifier Methods Arid Hasan; Yudhi Raymond Ramadhan; Minarto Minarto
Jurnal Riset Informatika Vol. 5 No. 4 (2023): September 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (751.857 KB) | DOI: 10.34288/jri.v5i4.244

Abstract

Since the onset of the COVID-19 pandemic in Indonesia, many people have turned to telemedicine programs as an alternative to minimize social interactions, opting for consultations from the safety of their homes using smartphones and internet connectivity. Given the necessity for physical distancing and avoiding crowded places, these applications have become indispensable substitutes for in-person medical consultations. Numerous apps facilitating access to healthcare services have been introduced in Indonesia, ranging from business startups to initiatives by the Ministry of Health. Telemedicine can potentially revolutionize healthcare in Indonesia, addressing critical health challenges. A significant issue within Indonesia's healthcare system is the scarcity of doctors and their uneven distribution. With only four doctors per 10,000 people, this figure falls far below the WHO guideline of 10 doctors per 1,000. Sentiment analysis of these applications was conducted to evaluate how telemedicine applications meet public needs and offer an alternative solution. Lexicon-based and naive Bayes methods were employed to classify tweet data into positive, neutral, and negative sentiments. The results revealed 908 positive tweets, 172 negative tweets, and 168 neutral tweets, indicating predominantly positive public perceptions of telemedicine applications. The naive Bayes classifier exhibited a 74% accuracy rate, with a precision of 98% and a recall of 86%. These findings underscore the positive impact and acceptance of telemedicine applications among the Indonesian populace, emphasizing their significance in augmenting the nation's healthcare landscape.
Co-Authors Arid Hasan Fadlan Sayyidul Anam Imam Maruf Nugroho Minarto Minarto Muhammad Rafi Muttaqin Shifa Silfiana