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All Journal Jurnal Ilmiah Teknik (JUIT) International Journal Science and Technology (IJST) Jurnal Teknik dan Science (JTS)
Nelly Sofi
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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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.
Prototype Design of InMed (Information Medicine) Application Using Goal-Directed Design (GDD) Method with Figma Tri Sulistyorini; Muhammad Achsan Isa AL Anshori; Nelly Sofi; Dwi Widiastuti
Jurnal Teknik dan Science Vol. 4 No. 2 (2025): Juni : Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v4i2.2144

Abstract

In the world of health, a platform is needed to make it easier for a person to find information, especially related to drugs practically. To realize this, this research was carried out to produce an application called InMed (Information Medicine). This research aims to analyze, design, and evaluate matters related to telemedicine and make it easier for users to find information about medicines. The method used in this study is Goal Directed Design (GDD) which consists of several steps, namely Research, Modeling, Requirements, Framework, Refinement, Support. The results of the Likert Scale test of the InMed application prototype received a score of 92%.
Co-Authors Dwi Widiastuti Erma Sova Muhammad Achsan Isa AL Anshori Revida Iriana Napitupulu Tri Sulistyorini