Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Jurnal Sistem informasi dan informatika (SIMIKA) Indonesian Technology and Education Journal Journal of Renewable Energy and Smart Device
Dini, Juliano Nufiansyach
Unknown Affiliation
Computer Science & IT Education Electrical & Electronics Engineering

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

Found 3 Documents
Search

 1 
Pengembangan Sistem Informasi Muna Barat Satisfaction Survey System (MUARA) Sardar Faroq Ahmad Khan; Novianti, Andi Fitri; Dini, Juliano Nufiansyach; Mei R., Ayada
Indonesian Technology and Education Journal Volume 2 No. 2 Agustus 2024
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/itej.v2i2.426

Abstract

Muna barat satisfaction survey system (MUARA) adalah sebuah platform sistem informasi yang dirancang khusus untuk memfasilitasi proses survei kepuasan pelanggan di wilayah Muna Barat. Sebagai sebuah solusi komprehensif, MUARA tidak hanya memberikan alat untuk mengumpulkan data survei, tetapi juga menyediakan berbagai fitur yang memungkinkan pengguna untuk mengelola, menganalisis, dan mengambil tindakan berdasarkan hasil survei tersebut.Dalam pengembangan aplikasi website ini digunakan metode Software Development life Cycles SDLC dengan model incremental, Model inkremental merupakan evolusi dari model waterfall yang biasa digunakan dalam pengembangan software.Berdasarkan hasil pengujian dan evaluasi, aplikasi MUARA telah memenuhi kebutuhan fungsional dan non-fungsional yang diharapkan. Aplikasi ini memudahkan proses survei kepuasan masyarakat dengan menyediakan antarmuka yang user-friendly serta fitur-fitur yang lengkap untuk admin dan pengguna. Dengan demikian, diharapkan aplikasi ini dapat menjadi alat yang efektif dalam meningkatkan kualitas pelayanan publik di Kabupaten Muna Barat.Untuk pengembangan lebih lanjut, disarankan agar tim developer terus melakukan pembaruan dan penyempurnaan aplikasi MUARA. Salah satu prioritas utama adalah meningkatkan keamanan data untuk melindungi informasi pribadi responden dan hasil survei. Selain itu, penambahan fitur analitik yang lebih mendalam dapat membantu admin dalam menganalisis data survei dengan lebih efektif.
KLASIFIKASI TINGKAT KESEGARAN DAUN BAWANG MENGGUNAKAN JARINGAN SYARAF TIRUAN BERBASIS PENGOLAHAN CITRA DIGITAL Novianti, Andi Fitri; Atthariq, Muhammad; Dini, Juliano Nufiansyach; Kaswar, Andi Baso; Lapendy, Jessica Crisfin
Jurnal Sistem Informasi dan Informatika (Simika) Vol 7 No 2 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i2.3378

Abstract

Green onions, commonly used in Indonesian cuisine, have significant agricultural potential. Despite high production, their quality, particularly freshness, is traditionally evaluated visually, leading to inconsistent and subjective results. This study aims to develop an objective and accurate method for classifying the freshness of green onions using an Artificial Neural Network (ANN). Previous studies have employed ANN but have not specifically targeted the freshness classification of leeks. The proposed method utilizes the color and texture features of green onions.The research methodology includes image acquisition, preprocessing, segmentation, morphology, feature extraction, and classification using ANN. A total of 300 images were acquired and categorized into three freshness levels: not fresh, less fresh, and fresh. During the training phase, 240 images were used, and 80 images were reserved for testing. The optimal feature combination identified includes HSV and LAB color features along with texture features (Contrast + Energy). The results demonstrated that the freshness classification of green onions achieved 100% accuracy in both training and testing phases. The training process, with 240 images, had a computation time of 142.684 seconds, while the testing process, with 80 images, took 35.648 seconds. These findings indicate that using ANN based on color and texture features is highly effective in determining the freshness level of green onions.
Perancangan Modul Keamanan Website dan Basis Data dalam Lingkup Sistem Terdistribusi dengan Strategi Pembelajaran Berbasis Case Method Ramli, Hartini; Kadir, Muh. Yasin; Hatima, Husnul; Dini, Juliano Nufiansyach; Al'Safinat.R, Reyna Buryani; Azhari, Reynaldi Nafzal
Journal of Renewable Energy and Smart Device Vol. 2 No. 2 Mei 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/joresd.v2i2.254

Abstract

In today's digital era, information systems have evolved from centralized models to distributed systems that span across various platforms and geographic locations. While this transformation enhances efficiency and scalability, it also increases security risks, particularly concerning websites and databases, which are core components of digital services. This module is designed to provide in-depth understanding of information security within distributed systems, focusing on the protection of websites and databases. The learning approach applies the case method, placing students in real or simulated scenarios to analyze, solve problems, and design security solutions based on the principle of defense in depth. This module aims to enhance students' critical thinking and technical skills in addressing ever-evolving information system security threats.
Co-Authors Al'Safinat.R, Reyna Buryani Andi Baso Kaswar Andi Baso Kaswar Atthariq, Muhammad Azhari, Reynaldi Nafzal Hatima, Husnul Kadir, Muh. Yasin Lapendy, Jessica Crisfin Mei R., Ayada Novianti, Andi Fitri Ramli, Hartini Sardar Faroq Ahmad Khan