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All Journal Journal of Information Systems and Informatics Journal of Electrical Power Control and Automation (JEPCA)
Atmojo, Toni Tri
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Computer Science & IT Electrical & Electronics Engineering

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Analisa Performa Website Badan Penanggulangan Bencana Daerah (BPBD) Provinsi Sumatera Selatan menggunakan Automated Software Testing GTmetrix Ramadhan, Moch Rizky Zulian; Mukti, Aan Restu; Atmojo, Toni Tri
Journal of Electrical Power Control and Automation (JEPCA) Vol 7, No 1 (2024): Juni
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/jepca.v7i1.108

Abstract

Websites are an important communication medium for disseminating information openly and widely to all corners of the world. Websites are very important as a supporting facility for information and communication needs. A good website is a website that has fast access speed. Therefore the aim of this research is to analyze the website loading speed performance of the South Sumatra Regional Disaster Management Agency (BPBD) using GTmetrix. GTmetrix is a Google product designed to measure the performance of a website with results in the form of a page speed score and structure score in percent. GTmetrix will later provide information about parts of the website that have poor scores and provide solutions to improve the website.
Machine Learning-Based E-Archive for Archives Management of South Sumatra Province Atmojo, Toni Tri; Kunang, Yesi Novaria
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.566

Abstract

Archives play a crucial role in institutional operations, yet efficiently retrieving specific information from them can be challenging. This research addresses this issue by developing an information retrieval system that incorporates advanced methods to enhance search efficiency. The system employs the TF-IDF (Term Frequency-Inverse Document Frequency) formula, which assesses the significance of a word within a document set, and the BM25 method, a sophisticated algorithm for ranking documents based on their relevance to the input query. Both methods undergo a preprocessing stage, enabling the system to calculate the relevance of each document to the given query accurately. The effectiveness of this system is evaluated using key performance metrics: precision (accuracy), recall (completeness), and the F1 Score (the harmonic means of precision and recall, representing the best value). Testing with various keywords revealed that the BM25 method yielded impressive results, achieving an average precision of 0.75, recall of 0.6, and an F1 Score of 0.6665. In contrast, the TF-IDF method scored lower, with a precision of 0.33, recall of 0.2, and an F1 Score of 0.2500. The system was tested using a dataset of 350 documents.
Co-Authors Aan Restu Mukti, Aan Restu Ramadhan, Moch Rizky Zulian Yesi Novaria Kunang