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All Journal Jurnal Pengabdian Informatika (JUPITA) Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Made Wahyu Purnama Putra
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PENINGKATAN EFISIENSI DAN AKSESIBILITAS LAYANAN KONSULTASI & PENGADUAN SAHABAT MEDIATOR BALI MELALUI WEBSITE I Made Wahyu Purnama Putra; I Wayan Supriana; Cokorda Rai Adi Pramartha
Jurnal Pengabdian Informatika Vol. 3 No. 2 (2025): JUPITA Volume 3 Nomor 2, Februari 2025
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Abstract

Penelitian ini bertujuan untuk meningkatkan efisiensi dan aksesibilitas layanan konsultasi dan pengaduan pekerja di Bali melalui pembuatan sebuah website yang kami sebut sebagai "Layanan Konsultasi Dan Pengaduan Sahabat Mediator Hubungan Industrial Dan Pengawas Ketenagakerjaan (Samhi Peka) Bali Berbasis Website." Bali, sebagai destinasi wisata utama di Indonesia, telah mengalami pertumbuhan ekonomi yang pesat, menciptakan peluang kerja yang besar. Namun, tantangan dalam akses dan efektivitas layanan Hubungan Industrial dan Pengawasan Ketenagakerjaan di Bali mendorong perlunya solusi yang lebih efisien. Metode pelaksanaan penelitian ini mencakup empat tahap utama: perancangan desain antarmuka pengguna (UI), pengumpulan data admin, implementasi, dan uji coba. Kami memanfaatkan platform Google Sites dan Tawk.to untuk menciptakan website yang responsif dan interaktif. Hasil dari penelitian ini adalah website yang memungkinkan pekerja untuk dengan mudah mengakses layanan konsultasi dan pengaduan secara online. Website ini juga menyediakan akses yang lebih aman dan efisien, serta meningkatkan kesadaran masyarakat tentang hak dan kewajiban mereka dalam hubungan kerja.
Aplikasi Ekstraksi Fitur Citra Buah Berbasis Website Menggunakan Metode Histogram I Made Wahyu Purnama Putra; I Wayan Supriana
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 2023
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2023.v02.i01.p18

Abstract

Image recognition and feature extraction of fruits using histogram methods have garnered significant attention in the fields of agriculture, food industry, and image processing. The Histogram method is an effective approach in automatically identifying unique characteristics of each fruit. Previous studies have demonstrated the success of histogram method in fruit image recognition based on color, texture, and shape. In this research, we propose the use of histogram method for fruit image feature extraction. We utilize secondary data consisting of fruit images such as apple, banana, mango, orange, papaya, melon, and watermelon, obtained from publicly available research datasets. We conduct a literature review to deepen our understanding of the histogram method and implement feature extraction steps such as mean, standard deviation, energy, entropy, and skewness. The authors developed a web-based application using Python programming language with the Django framework to perform fruit image feature extraction. This application allows users to upload fruit images, perform image pre-processing, and extract features using the histogram method. The extracted feature results are stored in a database for further use. Through this application, we successfully extract features from fruit images, such as banana, using the histogram method. The extracted feature results include mean, standard deviation, energy, entropy, and skewness. These results can be utilized in further research and training machine learning models to recognize and classify various types of fruits with high accuracy. 
Co-Authors Cokorda Rai Adi Pramartha I Wayan Supriana