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International Journal of Basic and Applied Science
Published by Institute of Computer Science
ISSN : 23018038     EISSN : 27763013     DOI : https://doi.org/10.35335/ijobas
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Physics
International Journal of Basic and Applied Science provides an advanced forum on all aspects of applied natural sciences. It publishes reviews, research papers, and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.
Arjuna Subject : Umum - Umum
Articles 5 Documents
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Search results for , issue "Vol. 12 No. 3 (2023): December: Basic and Applied Science" : 5 Documents clear
Effect of process temperature and percentage of rock sugar on the functional group intensity of red ginger extract Amalia Cantika Asyafa; Dessy Agustina Sari
International Journal of Basic and Applied Science Vol. 12 No. 3 (2023): December: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v12i3.268

Abstract

Red ginger has various health benefits that can be consumed in various ways, one of which is an instant powder drink, which is practical and extends the shelf life of the product. The processing process involves cooking at high temperatures with the help of sugar as a crystallization agent. This research aims to understand the effects of temperature and sugar concentration on red ginger extract. The variables used are temperatures of 80 and 90°C and rock sugar concentrations of 60% and 100%. Product evaluation was carried out using Fourier Transform Infrared Spectroscopy (FT-IR) to identify product functional groups. The research results showed that there were differences in functional group content between solid and liquid samples, both fresh raw materials and dregs. In the solid sample, seven functional groups were identified: N-H, C-H, C-H bending, C-N, C=C, C-C, and C-O. Meanwhile, in liquid samples, only six groups were identified, namely O-H, C=C, O-H bending, C-N, C-C, and C-O. Overall, this study shows that the functional group content in fresh red ginger is higher than that in red ginger pulp, even though the temperature is lower. However, if the comparison is between the solid and liquid sample conditions for fresh red ginger with fresh red ginger or dregs with dregs, the content at a cooking temperature of 90°C is higher than 80°C. Apart from that, the higher the rock sugar content in the red ginger pulp, the higher the content of functional groups identified in the extract
Sentiment classification of coral reef 101 content using decision tree algorithm through CRISP-DM Singgalen, Yerik Afrianto
International Journal of Basic and Applied Science Vol. 12 No. 3 (2023): December: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v12i3.297

Abstract

This research aims to classify public sentiment regarding the content of "Coral Reef 101," published by National Geographic. The methodology employed is the Cross-Industry Standard Process for Data Mining (CRISP-DM), encompassing stages such as business understanding, data understanding, modeling, evaluation, and deployment. The Decision Tree algorithm is utilized in conjunction with the SMOTE operator. This comprehensive approach enables the systematic analysis of public sentiment towards coral reef content, facilitating a deeper understanding of public perception and attitudes. The results of this study indicate that the DT algorithm with SMOTE demonstrates an accuracy of 87.51% +/- 4.28% (micro average: 87.50%), a precision of 80.35% +/- 5.10% (micro average: 80.00%) (positive class: Positive), recall of 100.00% +/- 0.00% (micro average: 100.00%) (positive class: Positive), f-measure of 89.02% +/- 3.22% (micro average: 88.89%) (positive class: Positive), and an AUC of 0.875 +/- 0.044 (micro average: 0.875) (positive class: Positive). These metrics demonstrate the effectiveness of the DT algorithm with SMOTE in accurately classifying public sentiment towards coral reef-related content, particularly in correctly identifying positive sentiment instances. The high accuracy, precision, recall, f-measure, and AUC values underscore the robustness and reliability of the model in sentiment analysis tasks.
Comparative analysis of decision tree and support vector machine algorithm in sentiment classification for birds of paradise content Singgalen, Yerik Afrianto
International Journal of Basic and Applied Science Vol. 12 No. 3 (2023): December: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v12i3.298

Abstract

This research aims to analyze public sentiments towards National Geographic's content on the bird of paradise from the perspective of nature-based tourism. The method utilized is CRISP-DM, comprising stages of business understanding, data understanding, modeling, evaluation, and deployment. Focusing on sentiments expressed in response to National Geographic's Bird of Paradise content, this study seeks insights into how the public perceives and values nature-oriented tourism experiences. Comparing the results of DT and SVM algorithms with and without the SMOTE reveals noteworthy differences in classification performance. Without SMOTE, both DT and SVM exhibit relatively lower accuracy and AUC values compared to their counterparts with SMOTE. For DT, adding SMOTE substantially improves accuracy (from 92.44% to 95.20%) and AUC (from 0.517 to 0.956), indicating enhanced classification accuracy and model robustness. In addition, SVM demonstrates significant performance gains with SMOTE, achieving notably higher accuracy (from 92.12% to 98.63%) and AUC (from 0.617 to 0.999). The significantly higher values across various performance metrics for SVM underscore its effectiveness in handling imbalanced datasets and accurately classifying sentiment data. Therefore, researchers and practitioners may consider leveraging SVM for sentiment analysis tasks in similar contexts to achieve optimal classification results and enhance decision-making processes.
Culture and heritage tourism sentiment classification through cross-industry standard process for data mining Singgalen, Yerik Afrianto
International Journal of Basic and Applied Science Vol. 12 No. 3 (2023): December: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v12i3.299

Abstract

This study investigates the efficacy of machine learning algorithms in sentiment classification within the context of Culture and Heritage Tourism content analysis. This study adopts the CRISP-DM method, a comprehensive methodology encompassing distinct stages, including business understanding, data understanding, modeling, evaluation, and deployment. The k-nearest Neighbors, Decision Tree, Naive Bayes Classifier, and Support Vector Machine models are used. The performance of each model is scrutinized through confusion matrix analysis, encompassing metrics such as accuracy, precision, recall, and F-measure. Additionally, the impact of the Synthetic Minority Over-sampling Technique (SMOTE) implementation on addressing data imbalance is assessed. Leveraging data from the national geographic channel's YouTube platform, with a focus on ma'nene content, results reveal SVM's consistent superiority, particularly with SMOTE integration, showcasing elevated accuracy (77.89%), precision (72.60%), recall (89.62%), and F-measure (80.21%) values. These findings underscore the importance of algorithm selection and data preprocessing methods in enhancing sentiment classification accuracy for culture and heritage tourism content, thus contributing quantifiable insights to the tourism research domain.
Effectiveness of horizontal and vertical constructed wetlands performance systems with some vegetation on domestic waste concentrations Harahap, Azmi wijayanti; Rosmayati, Rosmayati; Rahmawati, Nini
International Journal of Basic and Applied Science Vol. 12 No. 3 (2023): December: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Population growth has resulted in the demand for waste water reclamation increasing rapidly. CW systems are an inexpensive technology with little or no energy requirements and very minimal equipment requirements, resulting in low construction costs. This research will test improving the quality of domestic wastewater using a Vertical Flow Artificial Wetland (VFCW) and Horizontal Flow Artificial Wetland (HFCW) system using kangkong, water hyacinth and lotus vegetation. The results of the research carried out can be concluded as follows: in water spinach vegetation there is no difference in the concentration of BOD, COD, DO, Oil and Fat, Detergent, Ammonia, and total coliform parameters of the horizontal CW type and the vertical CW type. In water hyacinth vegetation there were no differences in the concentrations of BOD, COD, DO, Oil and Fat, Detergent, Ammonia, and total coliform parameters of the horizontal CW type and vertical CW type. In lotus vergetation there were no differences in the concentration of BOD, COD, DO, Oil and Fat, Detergent, Ammonia, and total coliform parameters of the horizontal CW type and vertical CW type. In the research results, there is no significant difference in the horizontal CW and vertical CW types in improving water quality, especially domestic waste, you can use horizontal CW or vertical CW types.

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