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Advance Sustainable Science, Environmental Engineering and Technology (ASSET) 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,
Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Advance Sustainable Science, Engineering and Technology (ASSET) is a peer-reviewed open-access international scientific journal dedicated to the latest advancements in sciences, applied sciences and engineering, as well as relating sustainable technology. 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 sciences, engineering, and technology. The Scope of ASSET Journal is: Biology and Application Chemistry and Application Mechanical Engineering Physics and Application Information Technology Electrical Engineering Mathematics Pharmacy Statistics
Arjuna Subject : Teknik Kimia (semua kategori) - Teknik Kimia (Lain-Lain)
Articles 210 Documents
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Implementation Artificial Intelligence with Natural Language Processing Method to Improve Performance of Digital Product Sales Service Putri Ariatna Alia; Dian Kartika Sari; Nur Azis; Bernadus Gunawan Sudarsono; Purwo Agus Sucipto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.521

Abstract

Improving the performance of digital product sales services is the main focus of the company's attention in the face of increasingly fierce competition in the online market. In order to optimize these services, Artificial Intelligence (AI) technology with the Natural Language Processing (NLP) method is an attractive option. This research aims to find out how the application of AI with Natural Language Processing (NLP) can contribute to improving the performance of digital product sales services. The methods used in this research include collecting data on customer interactions via WhatsApp that have implemented artificial intelligence with the Natural Language Processing (NLP) method. The data is then analyzed using Natural Language Processing (NLP) techniques to understand the needs, preferences, and problems faced by customers. Natural Language Processing (NLP) assists the chatbot in correcting incoming questions if they do not match the database on the question. Differences that can be helped by Natural Language Processing (NLP) if there is inappropriate capitalization, excessive conjunctions. The results show that the application of AI with Natural Language Processing (NLP), can enable companies to be more responsive to customer needs and improve overall customer satisfaction. With in-depth analysis of customers' natural language data, companies can provide more relevant services and empower sales teams to provide faster and more accurate responses. This can be seen from the quality of service results which have a point of 4.1, this value indicates a good response from customers so that the system is considered to have improved sales services by buyers.
Predicting Waste Production Trends in Palu City Using Linear Regression Analysis Mohamad Labambe
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.523

Abstract

The aim of this research is to obtain predicted results for the volume of waste in Palu City. In Helping the Environmental Agency One of the complex aspects of the waste problem in Palu City is the lack of waste facilities, there is no basic reference for predicting the movement of waste carried out by the Environmental Agency. If this is left unchecked then the waste in Palu City will never be completely resolved. The algorithm chosen is a linear regression algorithm which can help make good predictions, one of which can create waste volume traffic which is useful for knowing the rise and fall of waste volume in each area. in Palu City, so it is a concern. For the community, it is important to protect the environment from waste. Therefore, the Linear Regression Method is used to predict the value of the dependent variable if the independent variable has a value that is known to describe the level of waste pollution. Waste production in the Palu City area to provide information to the Palu City Environmental Service regarding waste production which continues to increase every year. Trash Trends that occur in Palu City using the previous dataset, based on Trend results showing the accumulated volume of waste in Palu City. The highest waste volume occurred in 2017 to 2021, around 350,000 (kg/person/month), the lowest volume occurred in 2021, around 200,000 (kg/person/month). shows that the analysis carried out is as good as possible. The system creation process begins with creating a flowchart, collecting waste volume data, determining an algorithm that can manage waste data, and determining an algorithm that can predict data that shows trends.
Implementation Aes-128 Encryption For Enhanced Data Security In Central Sulawesi Provincial Inspectorate Imam Wahyudi; Syahrullah; Dwi Shinta Anggreni; Rahmah Laila
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.560

Abstract

One technique to secure data is to use the Advanced Encrypt on Standard (AES) 128 method. The Advanced Encrypt on Standard (AES) method can be applied in improving data security, especially at the Central Sulawesi Provincial Inspectorate. The data in question are audit reports of BOS funds (School Operational Assistance), reports of special investigations into violations of regional finances and reports of violations of civil servant discipline (PNS). The data must have a high level of security, so that it is not easily known by irresponsible parties and will have a negative impact and be misused. The conclusion in this study was obtained that, the AES-128 algorithm can be used as an alternative to the process of improving data security, namely by encryption and decryption. The results of encryption can be guaranteed as long as the symmetry key encryption is not leaked to irresponsible parties
Waste Analysis in The Production Process Urea Fertilizer Using The Lean Six Sigma Method and Recommendations for Improving Failure Mode Effect Analysis (FMEA) at PT. Damai Sejahtera Tivani Nava Arier; Rochmoeljati Rochmoeljati; Isna Nugraha
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.579

Abstract

Agriculture plays an important role in the Indonesian economy, fertilizer is an important element in the development of the agricultural sector, especially urea fertilizer. PT. Damai Sejahtera, as one of the largest fertilizer producers in Indonesia, experienced waste in the urea fertilizer production process. In this study, lean six sigma was utilized. Using a lean approach, a reduction in non-value-added activities formed by the nine types of waste of 1360 to 1276 or 6.17% was achieved. However, using six sigma, it was found that the production process was not satisfactory as it resulted in many product defects with 36,331 DPMO and a sigma level of 3.32. Improvement suggestions to increase the sigma value were obtained through FMEA. Through this research, Process Cycle Efficiency was obtained from 74.85% to 80.35%.
Analysis of Air Shot Blasting Machine Effectiveness using Overall Equipment Effectiveness (OEE) Ah. Andi Setiawan; Joumil Aidin Saifuddin
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.582

Abstract

The effectiveness of a machine is one of the main factors for a production process to run smoothly so that it can meet its demand. Companies must always ensure that their production machines have high effectiveness. The shot blasting machine is one of the production machines used at PT. X. This machine has been in use for quite some time. Additionally, the machine often experiences breakdowns. This study was conducted to measure the effectiveness of the shot blasting machine at PT. X in order to determine its effectiveness. The overall equipment effectiveness (OEE) approach is used here to measure it. The OEE value is influenced by three factors, namely availability, performance, and quality. The result obtained is that the effectiveness of the machine is still quite high, with an OEE value of 81.82% and is still above the standard value for OEE, which is 85%. To enhance OEE, additional steps could involve documenting the issues as they arise, followed by generating a pareto chart to pinpoint the most common problems. This enables directing improvement endeavors towards addressing these significant challenges
Phytochemical and Antioxidant Activity of Akway (Drymis piperita Hook f.) Stem Bark Ethanol Extract Angela Myrra Puspita Dewi; Umar Santoso; Yudi Pranoto; Djagal Wiseso Marseno
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.598

Abstract

The amount of solvent affects the effectiveness of the extraction, so the chemical components are extracted entirely from the plant. This study investigated the best ratio of Akway bark : solvent (ethanol) to produce Akway extract with the highest antioxidant activity. Extraction with the treatment of Akway skin: ethanol ratio of 1:2; 1:4; 1:6 (b/v) was carried out and then the results were tested for total phenolic and flavonoid content and antioxidant activity. The best Akway bark:ethanol ratio was obtained at 1:4 (b/v) ratio with 9.54% extract yield, 289.57 mg GAE/g total phenolic content, 185.47 mg eq quercetin/g total flavonoids. Akway bark extract has potential as a source of antioxidants as indicated by its high antioxidant activity with DPPH free radical scavenging and ferric reducing activity of 50% (IC50) at extract concentrations of 16.59 µg/mL extract and 60.93 µg/mL extract, and carotene bleaching inhibition activity of 85.76%. There are 4 types of phenolic compounds and 4 types of flavonoid compounds identified with the highest percentage of components, namely Pereniporin B (57%).
Harnessing Quantum SVR on Quantum Turing Machine for Drug Compounds Corrosion Inhibitors Analysis Akbar Priyo Santosa; Muhammad Reesa; Lubna Mawaddah; Muhamad Akrom
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.601

Abstract

Corrosion is an issue that has a significant impact on the oil and gas industry, resulting in significant losses. This is worth investigating because corrosion contributes to a large part of the total annual costs of oil and gas production companies worldwide, and can cause serious problems for the environment that will impact society. The use of inhibitors is one way to prevent corrosion that is quite effective. This study is an experimental study that aims to implement machine learning (ML) on the efficiency of corrosion inhibitors. In this study, the use of the Quantum Support Vector Regression (QSVR) algorithm in the ML approach is used considering the increasingly developing quantum computing technology with the aim of producing better evaluation matrix values ​​than the classical ML algorithm. From the experiments carried out, it was found that the QSVR algorithm with a combination of (TrainableFidelityQuantumKernel, ZZFeatureMap/ PauliFeatureMap, and linear entanglement) obtained better Root Mean Square Error (RMSE) and model training time with a value of 6,19 and 92 compared to other models in this experiment which can be considered in predicting the efficiency of corrosion inhibitors. The success of the research model can provide a new insights of the ability of quantum computer algorithms to increase the evaluation value of the matrix and the ability of ML to predict the efficiency of corrosion inhibitors, especially on a large industrial scale.
Improving the Accuracy of House Price Prediction using Catboost Regression with Random Search Hyperparameter Tuning: A Comparative Analysis Faezal Hartono; Muljono Muljono; Ahmad Fanani
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.602

Abstract

Achieving a significant improvement over traditional models, this study presents a novel approach to house price prediction through the integration of Catboost Regression and Random Search Hyperparameter Tuning. By applying these advanced machine learning techniques to the King County Dataset, we conducted a thorough regression analysis and predictive modeling that resulted in a marked increase in accuracy. The baseline model, a conventional linear regression, provided a foundation for comparison, evaluating performance metrics such as R-squared and Mean Squared Error (MSE). The meticulous hyperparameter tuning of the Catboost model yielded a remarkable improvement in predictive accuracy, demonstrating the efficacy of sophisticated data science techniques in real estate and property valuation. The percentage increase in accuracy over the baseline model is explicitly stated in the abstract.
Characteristics of the MQ-135 Sensor for Testing Medium Speed Ship Engine Exhaust Gases Arif Rakhman Suharso; Ario Hendartono; Slamet Supriyadi
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.615

Abstract

International Convention that regulates air pollution caused by shipping activities as is indicated in Annex VI. So far, many ships' exhaust gases still contain a lot of NOx and SOx gases which can damage the air and are one of the contributors to air pollution. The aim of this research is to analyse the use of the MQ-135 sensor as a ship exhaust gas detection sensor connected to an Arduino Uno and a computer. Testing ship exhaust gas was using the medium speed ship's main engine in the engine laboratory of the Indonesian State Maritime Polytechnic. The measuring point was at the end of the exhaust chimney. The measurement variations consisted of low, medium and high engine speed (RPM) of the main engine. The result suggested that the higher the engine RPM, the higher the reading on the serial monitor. The average of measurement results from three measurements concluded that the high RPM is 96, for medium RPM is 81 and low RPM is 66 as displayed on the Arduino IDE serial monitor. From the results of the equipment testing that has been carried out, it can be concluded that the MQ-135 sensor can be used to detect ship exhaust gas from medium ship engine
Performance Measurement of Outbound Logistics in the Fertilizer Industry for Distribution Activities Based on Performance Of Activity (POA) Model and Analytical Hierarchy Process(AHP) Method Della Afi Rizky Anggraini; Farida Pulansari; Nur Rahmawati
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.619

Abstract

This research presents problems in the fertilizer industry with the goal of knowing the performance of fertilizer distribution. The outbound logistics process in fertilizer distribution activities is important, because it is connected to the process of delivering fertilizer products to consumers. However, in carrying out fertilizer distribution activities, there are problems that occur due to the mismatch of warehouse capacity over storage and differences in estimated delivery time. This situation results in missed fertilizer supplies for consumers. This research uses KPI criteria based on the Performance Of Activity (POA) model and performance weighting with the Analytical Hierarchy Process (AHP) method to determine the value of the Company's outbound logistics performance. The discussion with company experts resulted in 12 KPI indicators based on POA criteria consisting of cost, time, capacity, capability, productivity, utility, and outcome. After weighting with the AHP method, the total outbound logistics performance of  85,918 is included in the good category and can still be improved in the excellent category by giving recommendations for improvement. So, further research can be made collaborating the AHP method with other methods such as the SCOR method to simplify the selection of supply chain process activities or using the Fuzzy AHP method to reduce the subjectivity of the research.

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