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Mega Novita
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asset@upgris.ac.id
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Jl. Sidodadi Timur No.24, Karangtempel, Kec. Semarang Tim., Kota Semarang, Jawa Tengah 50232
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INDONESIA
Advance Sustainable Science, Engineering and Technology (ASSET)
Published by Universitas PGRI Semarang
ISSN : -     EISSN : 27154211     DOI : https://doi.org/10.26877/asset
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology
This journal aims to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of science, engineering, and technology
Arjuna Subject : Energi (semua kategori) - Teknik Energi dan Teknologi Daya
Articles 141 Documents
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A Combination of Vigenere Cipher and Advanced Encryption Standard for Image Security Ivan Stepheng; Christy Atika Sari; Eko Hari Rachmawanto; Folasade Olubusola Isinkaye
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.17150

Abstract

In an era where digital information security is paramount, this research addresses the pressing need for robust encryption methods. We propose a novel approach that combines the Vigenere Cipher and the Advanced Encryption Standard (AES) for secure digital image transmission. Our study recognizes the research gap in secure image transmission methods and aims to bridge it with a powerful encryption solution. We implement this hybrid encryption approach using the Vigenere Cipher in C++ and the AES algorithm in MATLAB. Our experiments validate the effectiveness of our program in concealing and restoring digital images during transmission. This hybrid encryption technique has promising applications in healthcare, military, and confidential business operations, bolstering image security in real-life scenarios. By enhancing image security, our research can contributed to safeguarding sensitive information in the digital age
INCREASING MATERNAL KNOWLEDGE IN PREVENTING STUNTING THROUGH COMMUNITY-BASED NUTRITION EDUCATION Emaniar, Ade Emaniar; Octafania, Nabila Shafira; Buchori, Arie Maulana; Anggraeni, Diah Ayu; Widyawati, Rachma Widyawati; Mawardhani, Anastasya Yushinta; Astuti, Derina Fuji; Anggrena, Rifa Safitri; Putri.M.S, Andi Zahra; Roosana, Mia Roosana; Kurniawati, Yuliana Dwi; Septianingrum, Belinda Dian; Veria Setyawati, Vilda Ana
Advance Sustainable Science, Engineering and Technology Vol 5, No 2 (2023): May-July
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i2.16252

Abstract

Stunting is a disorder of growth and development of children due to chronic malnutrition and recurrent infections, which is characterized by their length or height being below the standards set by the minister who organizes government affairs in the health sector. The respondents in this activity were mothers and toddlers in RW 02, RT 01, 02, and 03. The sample in this activity was 42 toddler. The purpose of this activity is to increase mothers' knowledge about feeding, especially fruits and vegetables with balanced nutritional content for toddlers. The method used is the Wilcoxon Test with a confidence level of 95% and α = 0.05. The results and discussion using the Wilcoxon test showed an increase in maternal knowledge related to stunting. There are 5 toddlers affected by stunting. There are efforts to change behavior for the better and increase maternal knowledge in stunting prevention, namely by socialization about the importance of preventing stunting, nutritious food demos, posters of processed fruit and vegetable creations, and distribution of PMT (Supplementary Feeding).
Innovatif Engineering Strategies for Revenue Growth : a SWOT and QSPM Analysis of UD AMJ Jaya Teknik Alif Putra Awanda; Elly Ismiyah; Akhmad Wasiur Rizqi
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.17253

Abstract

Business competition in the current era of globalization is very rapid, so it is increasing competition between companies which is getting higher and tighter. UD AMJ Jaya Teknik is a company in the field of turning and manufacturing spare parts. As long as the business run by UD AMJ Jaya Teknik experiences a decline in income, good and appropriate strategic management is needed for UD AMJ Jaya Teknik. The methods used in this research are the SWOT and QSPM methods. The aim of this research is to provide strategy suggestions for companies to experience increasingly rapid increases in income. The four stages carried out are the stage of looking for internal and external company factors, the IFE and EFE matrix stage, the SWOT matrix matching stage, the stage of determining the main strategy with the largest total attractive score using QSPM. There are 7 proposed marketing strategies for UD AMJ Jaya Teknik. Improving the quality of the products produced and innovating the products produced is the strategy with the highest TAS score of 5.95.
Analysis of Listen Before Talk Protocol Implementation in Terrestrial Network Using Multi-Node LoRa Communication Shafiatullaily Mahmud
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.16520

Abstract

Wireless communication today plays a very important role in technological development but often faces challenges in terms of reliability and quality of data transmission; this study implements the Listen Before Talk (LBT) protocol in the terrestrial network environment through Multi-Node LoRa communication to test its effectiveness in avoiding packet loss ending the quality of communication in variations of the land environment. Test results showed that LBT effectively produced zero percentage packet loss at 50 to 500 meters. At the same time, LoRa devices could maintain communication quality even though the Received Signal Strength Indicator (RSSI) value decreased with the distance. The findings provide positive indications of the potential of LBT protocols inning data transmission integrity in terrestrial environments and foster the development of reliable and high-quality wireless communications in complex ground network environments.
Fast and Accurate Indonesian QnA Chatbot Using Bag-of-Words and Deep-Learning For Car Repair Shop Customer Service Muchamad Taufiq Anwar; Azzahra Nurwanda; Fajar Rahmat; Muhammad Aufal; Hindriyanto Dwi Purnomo; Aji Supriyanto
Advance Sustainable Science Engineering and Technology Vol 5, No 2 (2023): May-July
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i2.14891

Abstract

A chatbot is a software that simulates human conversation through a text chat. Chatbot is a complex task and recent approaches to Indonesian chatbot have low accuracy and are slow because it needs high resources. Chatbots are expected to be fast and accurate especially in business settings so that they can increase customer satisfaction. However, the currently available approach for Indonesian chatbots only has low to medium accuracy and high response time. This research aims to build a fast and accurate chatbot by using Bag-of-Words and Deep-Learning approach applied to a car repair shop customer service. Sixteen different intents with a set of their possible queries were used as the training dataset. The approach for this chatbot is by using a text classification task where intents will be the target classes and the queries are the text to classify. The chatbot response then is based on the recognized intent. The deep learning model for the text classification was built by using Keras and the chatbot application was built using the Flask framework in Python. Results showed that the model is capable of giving 100% accuracy in predicting users’ intents so that the chatbot can give the appropriate responses and the response time is near zero milliseconds. This result implies that developers who aim to build fast and accurate chatbot software can use the combination of bag-of-words and deep-learning approaches. Several suggestions are presented to increase the probability of the chatbot’s success when released to the general public.
Review and Bibliometric Analysis of Biogas Power Plants in Indonesia Dhasa Ikrar Setyanansyach; Muji Setiyo; Thirunavukkarasu Raja
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.16806

Abstract

The demand for energy is increasing due to population growth, technological advancements, and a growing need for sustainable energy sources. Indonesia, which faces an energy deficit, is exploring alternatives to fossil fuels. Biogas, produced through the anaerobic fermentation of organic matter, offers a clean and sustainable energy option while addressing waste disposal issues. Therefore, this literature review examines various aspects of a biogas power plant, including a feasibility study that encompasses technical and economic analyses, generator design, trials, implementation, and post-implementation evaluation. In this review, we gathered scientific papers from Google Scholar using the keywords "pembangkit listrik biogas" between 2019 and 2022, with a focus on recent content. Patents and citations were excluded from the Google Scholar searches to ensure article relevance. Out of a total of 40 articles, 30 were rejected because they did not originate from scientific journals. The collected articles are categorized based on the materials used for biogas generation in power plants. This systematic approach yielded 10 relevant articles. Consequently, the literature reveals that various raw materials, such as palm oil mill waste (POME), livestock manure, and organic waste, hold the potential for biogas production. The results emphasize the economic feasibility of specific biogas projects, the environmental challenges they pose, and the positive impact they have on community well-being
Effect of Chitosan Variation in Starch and Cellulose Based Biofoam Ayu Lintang Cahyani; Vidrika Linda; Dody Guntama; Mubarokah N Dewi; Lukmanul Hakim
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.17126

Abstract

Styrofoam’s using as packaging is increasing. Styrofoam is difficult to decompose so alternatives such as biofoam are needed. This study explores the creation of eco-friendly packaging material by varying cellulose (0%, 3%, 5%, and 7%) and chitosan concentrations (0%, 2%, 4%, 6%, 8%, and 10%) in biofoam, aiming to replace non-biodegradable Styrofoam. Production is carried out by delignifying sugarcane bagasse and corn cobs with 10% NaOH, making tofu pulp starch and biofoam. The research focuses on tensile strength, absorption capacity, biodegradation, and morphology of the biofoam. Results indicate that chitosan concentration affects water absorption and biodegradation, while cellulose impacts tensile strength. The findings highlight the potential of biofoam made from tofu dregs, corn cobs, and sugar cane bagasse, offering a promising alternative to Styrofoam
Design of Android and IoS Applications for Mobile Health Monitoring Devices Ade Silvia Handayani; Anisah Fadhilah; Ibnu Ziad; Nyayu Latifah Husni; Sri Chodidjah; Mega Hasanul Huda; Nur Agustini; Mieska Despitasari; Riswal Hanafi Siregar
Advance Sustainable Science Engineering and Technology Vol 5, No 2 (2023): May-July
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i2.16508

Abstract

This research proposes a multifunctional wireless health monitoring tool with a display for Android and iOS devices. This research aims to develop a realistic solution for real-time and conveniently accessible health monitoring via mobile devices. The device allows users to test and track health factors such as heart rate, blood pressure, blood oxygen levels, body temperature, and blood glucose. It collects data properly by using wireless technology and sensors. The data is subsequently supplied to the appropriate apps on Android and iOS devices. The data is presented visually in the program, making it instructive and user-friendly. The device's development technique involved extensive testing and validation against established comparators to assure accuracy. The results of this study show that this digital, multi-purpose health monitoring device works well and reliably to give real-time health information. This innovation promotes health monitoring and digital health information access.
Mangrove Tree Species Classification Based on Leaf, Stem, and Seed Characteristics Using Convolutional Neural Networks with K-Folds Cross Validation Optimalization
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.17188

Abstract

Mangrove classification plays a pivotal role in environmental monitoring and conservation efforts. In this study, our meticulously curated dataset comprised diverse mangrove tree images standardized to 250 x 250 pixels, capturing the nuances of various species. Employing advanced deep learning techniques, our models demonstrated exceptional accuracy, reaching 99.23% without K-Folds and a slightly enhanced 99.78% with K-Folds. These models exhibited outstanding consistency, showcasing recall, precision, and F1-Score metrics all surpassing 99%. Through rigorous testing in 10 experiments, both K-Folds and non-K-Folds methods consistently achieved 100% accuracy, evidenced by the presence of True Positives in every classification scenario. This remarkable performance underscores the robustness of our algorithms in precisely classifying mangrove species, offering a valuable tool for ecological research and conservation initiatives.
A Good Performance of Convolutional Neural Network Based on AlexNet in Domestic Indonesian Car Types Classification
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.16854

Abstract

Classification of car vehicle types has been carried out using CNN. There are weaknesses in the CNN algorithm so that it can be continued in the research we propose. This study aims to improve the previous accuracy by using the Alexnet architecture. To improve the results of the data set used we use threshold and brightness adjustment and data augmentation techniques for Reflection, Rotation, and Translation. Sample images with a resolution of 227x227x3 totaling 840 images used to represent 8 class types of cars, including Avanza, Fortuner, Freed, Inova, Pajero, Terios, Xenia, and Xpander. Alexnet with 10 epochs consisting of a total of 760 iterations, and validation is carried out every 30 iterations, the test results show that the use of the "sgdm" optimization function achieves a training accuracy of 99.74%, while the use of the "adam" optimization function produces an accuracy of 96.85%. This experiment shows the model's ability to classify the types of trainers after a success rate of 100%.

Page 9 of 15 | Total Record : 141

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