Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal Infotekmesin Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal Sistem Informasi Galuh
Lisda Lisda
Informatics Engineering Department, Universitas Amikom Yogyakarta,
Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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

Found 3 Documents
Search

 1 
Analisa Slope Wilayah Kebakaran Hutan menggunakan Metode Naive Bayes Lisda; Isnaeni, Nenen; Firmansyah, Muhammad Raafi'u
Jurnal Sistem Informasi Galuh Vol 2 No 2 (2024): Journal of Galuh Information Systems
Publisher : Fakultas Teknik Jurusan Sistem Informasi Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jsig.v2i2.3934

Abstract

Forest and land fires are an economic and environmental problem that can cause serious damage. We can predict what factors cause forest fires. It is undeniable that topographical conditions affect the triggering and propagation of fires. The topographical condition itself is in the form of a slope, where fire propagation will be faster when going up the slope than going down the slope. This study aims to match whether the slope and display locations that are prone to the spread of certain fires with high fire intensity actually have a high fire potential and report the magnitude of the influence of the slope in the prediction of fire potential. One of the common approaches to classifying data is to use data mining. So in this study the researchers used the Naive Bayes Classifier as a classification method by getting the highest accuracy value of 0.99%.
Designed a Waste Management Application by Applying Requirements Engineering Methods to Meet User Needs and Expectations Lisda, Lisda; Febrianto, Dany Candra; Kusumastuti, Rajnaparamitha
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2509

Abstract

Efforts to manage waste through recycling have been implemented frequently but continue to receive minimal attention from the public, who are daily contributors to waste generation. As a result, the volume of waste keeps increasing, leading to environmental pollution, such as ecosystem damage, unpleasant odors, and blockages in waterways. This research aims to demonstrate that waste management can be enhanced by integrating data to uncover insights that can inform new strategies for addressing excess waste. In this study, a prototype for a waste recycling application was developed, focusing on digital-based waste management using IoT technology. The system incorporates sensors capable of measuring waste volume as a supporting tool developed using the requirements engineering method. Questionnaires were distributed to 30 respondents to gather feedback on platform designs and IoT product designs. Through requirements validation testing, the results showed that 70% of the 30 respondents approved the platform design, while 63.2% approved the IoT product design.
Illegal Motorcycle Parking Detection in The Car Area Isnaeni, Nenen -; Wisesa, Bradika Almandin; Lisda, Lisda; Febrianto, Dany Candra
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 2 (2025): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v5i2.1948

Abstract

Illegal motorcycle parking in designated car areas at Politeknik Manufaktur Negeri Bangka Belitung (Polman Babel) disrupts campus parking management, reduces space availability, and poses safety risks. This paper proposes an automated detection system using computer vision and license plate recognition to identify motorcycles parked in car areas and notify their owners via WhatsApp and email alerts. The system integrates CCTV cameras with YOLOv11 for vehicle detection and EasyOCR for license plate recognition, coupled with a database for owner identification. Upon detection, owners receive immediate notifications to rectify the violation. Experiments in Polman Babel’s parking lot show a 94% accuracy in motorcycle detection and 88% in license plate recognition under diverse conditions. The system enhances parking enforcement efficiency, reduces manual intervention, and supports smart campus initiatives. This work offers a scalable, cost-effective solution adaptable to other institutions facing similar parking challenges.
Co-Authors Bradika Almandin Wisesa Dany Candra Febrianto Dhani Ariatmanto Firmansyah, Muhammad Raafi'u Kusrini Kusrini Kusumastuti, Rajnaparamitha Nenen Isnaeni