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Journal of Software Engineering and Information System (SEIS)
Published by Universitas Muhammadiyah Riau
ISSN : -     EISSN : 28090950     DOI : https://doi.org/10.37859/seis.v3i1
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Journal of Software Engineering and Information System (SEIS) is a peer-reviewed journal published twice a year (January and August) by the Department of Information System - Faculty of Computer Science, Universitas Muhammadiyah Riau. The scope of the journal is: Artificial Intelligent Business Intelligence and Knowledge Management Data Mining E-Bussiness IT Governance Enterprise System System Design Information Design & Development Database System Expert System Decision Support System
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 12 Documents
 1   2 
Search results for , issue "Vol. 5 No. 2 (2025)" : 12 Documents clear
PERANCANGAN SISTEM INFORMASI PEMESANAN TIKET TRAVEL BERBASIS WEB DI PT YOSSY MANDIRI Mulyana, Wide; Izaky Arif Rahman; Meli Aulia; Muhammad Fadly; Nabil Andra Putra; Sintia Hadisty
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 2 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i2.9894

Abstract

This research aims to design a web-based ticket booking information system that can enhance the efficiency and quality of services at PT. Yossy Mandiri. This system is designed to facilitate customers in making ticket reservations online and assist the admin in managing booking data, departure schedules, and customer information. The system development method used is the waterfall method, which includes requirements analysis, system design, implementation, testing, and maintenance. The result of this research is a web-based travel ticket booking information system that can improve efficiency and service quality at PT. Yossy Mandiri. This system is expected to be a solution for the company in enhancing customer service and optimizing internal business processes.
KLASIFIKASI BUAH JERUK LEMON BERDASARKAN TINGKAT KEMATANGAN MENGGUNAKAN METODE SVM DAN NAIVE BAYES Mualfah, Desti; Rivaldi, Hardi; Januar Al Amin; Sunanto
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 2 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i2.9952

Abstract

This study aims to develop a classification model for determining the ripeness level of lemons (Citrus limon) using digital image analysis. Two methods, namely Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC), were compared to evaluate their performance in terms of accuracy and prediction consistency. The results show that SVM outperformed NBC with an accuracy of 97%, along with precision, recall, and F1-Score of 97% each. The model consistently determined lemon ripeness levels in percentage terms, such as 85% or 95%. In contrast, NBC achieved an accuracy of 82%, with precision, recall, and F1-Score of 83%, 82%, and 83%, respectively. However, NBC was more prone to classification errors, especially in distinguishing between ripe and unripe lemons. In conclusion, the SVM method proved superior to NBC in determining lemon ripeness levels, particularly in handling complex data. SVM's ability to provide accurate and consistent predictions makes it a more effective choice for helping farmers optimize the quality and quantity of lemon production. This study contributes significantly to the application of image processing technology in the agricultural sector.

Page 2 of 2 | Total Record : 12

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