Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Teknik (JUIT) International Journal Science and Technology (IJST)
Erma Sova
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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

Found 3 Documents
Search

 1 
PEMANFAATAN TELEGRAM UNTUK PENDETEKSI KEBOCORAN GAS BERBASIS NODEMCU Tri Sulistyorini; Nelly Sofi; Erma Sova
Jurnal Ilmiah Teknik Vol. 3 No. 2 (2024): Mei : Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/juit.v3i2.1339

Abstract

A significant increase in consumption of natural resources in the household sector is the use of LPG (Liquefied Petroleum Gas) gas, this can increase the risk of fire due to leaks from gas cylinders. These gas leaks are often unknown to users because not all LPG cylinder manufacturers provide a security system for the LPG cylinders they sell, so not all homes have gas leak sensors on LPG cylinders, therefore a tool is needed to detect LPG gas leaks. In view of these problems, in this research a device was created that can detect gas in a room with an MQ-2 sensor and apply a notification system using Telegram as an SMS notification sender and a buzzer as an alarm. The design of this detection tool as a whole is controlled by the NodeMCU ESP8226. During system testing, when a gas leak is detected at a distance of 1cm – 100cm with the MQ-2 sensor, the system will provide a notification via Telegram and activate the alarm (the buzzer will beep). The process of sending this message takes around 4-6 seconds. The tool was also tested on two different cellphones and obtained the expected results and good performance.
SENTIMENT ANALYSIS USING LONG TERM MEMORY (LSTM) BOOK CASE STUDY: UNSOLICITED ADVICE FOR MURDERERS BY VERA WONG'S Tri Sulistyorini; Erma Sova; Nelly Sofi; Revida Iriana Napitupulu
International Journal Science and Technology Vol. 2 No. 3 (2023): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v2i3.995

Abstract

Reading books is one of the most effective ways to reduce stress. In today's digital era, access to finding and buying books is getting easier, so reader reviews are important in choosing books that match interests. However, with a large number of reviews, Natural Language Processing (NLP) with the Long Short-Term Memory (LSTM) method is used to help analyze positive and negative sentiments from many book reviews. This sentiment analysis is useful for readers to evaluate the quality of books, as well as for authors and sellers to find out the opinions of readers and improve the quality of their work. In this study, the book review dataset "Vera Wong's Unsolicited Advice for Murderers" from the Goodreads website is used, which is then divided into training data and validation data with a ratio of 75%: 25%. The Long Short-Term Memory (LSTM) method is used to analyze the sentiment of the reviews. The model architecture built consists of Embedding Layer, LSTM Layer with 128 neuron units, 3 Dense Layer with ReLU activation function, 3 Dropout Layer, and Fully Connected Layer with and Sigmoid activation function, Binary Cross Entropy loss function, and RMSprop optimizer. The model training process was conducted with 30 epochs. The evaluation results show that the model achieved an accuracy of 90%, indicating the model performs relatively well in correctly classifying positive sentiments.
PERFORMANCE ANALYSIS OF BUSINESS STARTUP WEBSITE USING GT-METRIX WITH WATERFALL SOFTWARE DEVELOPMENT LIFE CYCLE METHOD Erma Sova; Makmun; Siti Shifa Tasliza
International Journal Science and Technology Vol. 3 No. 1 (2024): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v3i1.1338

Abstract

Business ventures began to expand towards technology that initially used conventional sales and payment methods, then developed by young people who saw business opportunities could be simplified in an easy way but had a lot of profit. They utilize computer technology by creating ways to sell through online, namely website media as startup business people. The purpose of the study was to analyze the performance of the "bikinian ibu" website with a http://bikinanibu.lovestoblog.com/ url address. Analysis activities in the form of measuring website speed performance, testing browser timing, testing Tab Structure, Testing Tab Waterfall in diagram form, Testing Tab History, Testing website vitals, Testing Tab Speed. The method used is the Waterfall method by following the following stages: analysis, design or design, coding, testing and maintenance. Based on the results of testing the performance of the "mother-made" website in the GTMetrix section, a Performance analysis score of 93% was obtained, CLS (Cumulative Layout Shift) has not shown good results because it exceeds the maximum standard score on CLS (Cumulative Layout Shift), the structure score covers 89% with the grade A category which means it shows good results. Website loading time also shows good results, website testing looks like there are constraints in the medium and low urgency categories. On the Waterfall tab of the website in the form of waterfall chart results there are 2 404 errors, 20 requests with a total file size of 622KB and 0.96MB for uncompressed files, while the time to load the website is 1.4 seconds. From the results of the Total Page Size of the website is 624KB, while the total page request is obtained as much as 20.
Co-Authors Makmun Nelly Sofi Revida Iriana Napitupulu Siti Shifa Tasliza Tri Sulistyorini