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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Ilmiah Media Sisfo Journal of Dinda : Data Science, Information Technology, and Data Analytics
Apri Junaidi
Institut Teknologi Telkom Purwokerto
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Klasifikasi Penyakit Kanker Kulit Menggunakan Metode Convolutional Neural Network (Studi Kasus: Melanoma) Reynaldi Rio Saputro; Apri Junaidi; Wahyu Andi Saputra
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 2 No 1 (2022): February
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v2i1.349

Abstract

Skin cancer is one of the most commonly diagnosed cancers worldwide, especially in the white population. One of the most dangerous skin diseases is melanoma cancer. Melanoma is a skin cancer that can develop in melanocytes, the skin pigment cells that produce melanin. Melanin is what absorbs ultraviolet rays and protects the skin from damage. Melanoma is a type of skin cancer that is rare and very dangerous, many laypeople have not been able to distinguish between ordinary moles and melanoma. Therefore, a study on the classification of melanoma skin cancer was carried out using the CNN method, where CNN was able to classify melanoma images. In CNN itself there is an architectural model, while the architecture used in this research is using conv2d layer, max pooling, flatten, dense, dropout, and using ReLu activation. The image size used in this architecture is 128x128, at the 50th epoch, an accuracy rate of 92.64% is obtained. It is hoped that this research can help the community in distinguishing normal moles and melanoma cancer.
Implementasi Deep Learning Untuk Klasifikasi Citra Undertone Menggunakan Algoritma Convolutional Neural Network Rizka Fayyadhila; Apri Junaidi; Novian Adi Prasetyo
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 1 No 2 (2021): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (448.788 KB) | DOI: 10.20895/dinda.v1i2.366

Abstract

The beauty of Indonesian women is distinguished by skin color, facial structure, hair color and body posture. For women today trying to look beautiful is a must. The way to make yourself look beautiful can be tricked by using make-up. But it's not that easy to use make-up because the type of make-up is differentiated based on the basic skin color, this is the problem for women in using make-up. Undertone is the basic color of the skin, there are three types of undertones, namely warm, cool and neutral. By knowing the type of undertone, it will make it easier for women to use make-up, namely to determine the appropriate shade based on the type of undertone. For this reason, a modeling of undertone image classification was made using the Convolutional Neural Network algorithm. This algorithm is claimed to be the best algorithm for solving object recognition and detection problems. The wrist vein color image dataset is required. The dataset used is 30 data per class, then preprocessing is carried out by homogenizing the image size to 64x64 pixels, then augmentation is carried out on each image by rotating and zooming. At this stage, the dataset will be divided into 3000 images which are divided into 80% training data and 20% testing data. Then it is processed through the convolution and pooling process at the feature learning stage, then the fully connected layer and classification stage where the feature learning results will be used for the classification process based on subclasses. Produces accuracy and training model values ​​reaching 98% with a loss value of 0.0214 and for accuracy from data validation it reaches 99% with a loss value of 0.0239 with model testing results of 99.5%.
Aplikasi Berbasis Web Deteksi Undertone Menggunakan Metode Agile Untuk Rekomendasi Makeup Sang Dara Parameswari; Novian Adi Prasetyo; Apri Junaidi
Jurnal Ilmiah Media Sisfo Vol 16 No 1 (2022): Jurnal Ilmiah Media Sisfo
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/mediasisfo.2022.16.1.1111

Abstract

Berpenampilan menarik adalah keharus bagi kaum perempuan, agar wajah bisa terlihat indah dan menawan dibutuhkan sebuah makeup. Saat ini perempuan yang mengenal berbagai jenis makeup, kosmetik yang dibutuhkan dalam makeup seperti pensil alis, maskara, foundation, lipstik, bedak dan lain sebagainya. Pemilihan shade pada foundation masih menjadi kesulitan bagi para perempuan, hal tersebut dapat membuat warna kulit jadi terlihat berbeda sehinga membuat perempuan merasa insecure atau tidak percaya diri. Tiga jenis udertone yaitu warm, cool dan neutral. Cara manual untuk mengetahun jenis undertone untuk melihat warna urat nadi pada tangan, namun terkadang dengan melakukan cara manual perempuan masih kesulitan untuk menentukan jenis undertone yang dimiliki. Oleh karena itu, dengan semakin berkembangnya zaman, diperlukannya sebuah aplikasi untuk mempermudah perempuan dalam mengetahui jenis undertone dan mendapatkan rekomendasi makeup. Metode agile digunakan untuk pengembangan aplikasi karena berfokus pada penanganan perubahan sesuai kebutuhan pengguna dan kecepatan. Deteksi undertone diimplementasikan sebagai aplikasi berbasis website yang dibangun menggunakan metode Agile. Metode Agile berhasil diterapkan pada penelitian ini dengan hasil berupa aplikasi deteksi Undertone, keberhasilan tersebut diukur menggunakan pengujian blackbox dengan menunjukan hasil semua fitur berjalan dengan baik sesuai dengan kebutuhan pengguna.
Sistem Rekomendasi Desain Website Berdasarkan Tingkat Kemiripan Menggunakan Euclidean Distance Cahyani Ainun Awaliyah; Agi Prasetyadi; Apri Junaidi
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 2 No 2 (2022): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v2i2.543

Abstract

The more internet users, the more interest in creating websites for certain purposes. To create a website that can attract visitors, a good website design is required. Website design is an important element in making a website, because the design of a website will create its own impression and image for website users. One of the technological developments is artificial intelligence, namely the Recommendation System which is a computer technology that is able to provide recommendations for the layman, in this study a website design recommendation system based on the Euclidean distance assessment resulted in a "good" SUS (System Usability Scale) grade C “good”.
Co-Authors Afandi Nur Aziz Thohari Agi Prasetyadi Alfira Mahda Ramadini Cahyani Ainun Awaliyah Condro Kartiko Ely Purnawati Ilham Fauzi Khurun Ain Muzaqi Lusiana Haryanti Mohtar Khoiruddin Muhammad Fathoni Hervi Hermawan Nashrulloh Khoiruzzaman Novanda Alim Setya Nugraha Novian Adi Prasetyo Nurul Isna Ganggalia Ramadhani, Rima Dias Reynaldi Rio Saputro Rizka Fayyadhila Rudolf Dekha Silaen Sang Dara Parameswari Sindhi Pradnya Nareswari Tri Ginanjar Laksana Wahyu Andi Saputra Wibowo, Fahrudin Mukti