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Enhancing Abusive Language Detection on Twitter Using Stacking Ensemble Learning
Full text linkDetecting abusive language on Twitter is an important step in reducing the prevalence of negative content and harassment. This study aims to improve the accuracy and effectiveness of abusive language detection on Twitter by addressing the limitations of the single model commonly used previously. The stacking method is employed by combining Term Frequency-Inverse Document Frequency (TF-IDF) as the feature extraction method, along with the Naive Bayes and XGBoost algorithms as classification models. Naive Bayes is known for its simplicity in handling text classification, while XGBoost excels in processing complex data and achieving high accuracy. The combination of these two models is expected to improve performance in detecting coarse language. The research results show that the proposed model outperforms the methods in previous studies, with an accuracy of 91.91% and an AUC of 96.76%. These findings demonstrate the effectiveness of the stacking approach in reducing classification errors in coarse language detection. Further research could explore the use of larger datasets or more complex models to improve detection accuracy
Sentiment analysis spotify applications on google play store with naïve bayes and neural network methods
Full text linkDigital advancements have significantly changed the way music is accessed and enjoyed, with streaming platforms such as Spotify emerging as one of the most widely used applications worldwide. Along with this growth, user reviews on platforms like the Google Play Store have become an important source of information, offering insights into user satisfaction and areas for improvement. In this study, sentiment analysis was conducted on Spotify reviews using two classification methods, Naïve Bayes and Neural Networks. The reviews were collected, processed, and then analyzed with both approaches to evaluate their performance. The results show that Neural Networks outperformed in terms of accuracy, F1-score, and recall, while Naïve Bayes performed better in AUC, precision, and MCC. Analysis of the dataset also revealed that negative reviews dominated at 52.8%, followed by positive at 28.3%, and neutral at 19%. These findings highlight the value of sentiment analysis in understanding user perspectives and can support developers in improving application quality and user experience
Counselling on the correct use of antibiotics to prevent antibiotic resistance and the use of family medicinal plants (toga) for health
No full textA significant increase in the use of antibiotics in the community is often not matched by a proper understanding of their use, potentially leading to antibiotic resistance. This research aims to educate the community about the importance of proper antibiotic use and the utilization of Family Medicinal Plants (TOGA) as alternative medicine. Community service activities were carried out on November 24, 2024 in Salam Mulya Village, Pondok Salam District, Purwakarta Regency, in collaboration with Holistic Purwakarta Hospital. The methods used included education and discussion, with the distribution of brochures containing information on the use of antibiotics and TOGA. The results of the activity showed that the community showed high enthusiasm for the education provided, with 50 participants attending and actively participating in the discussion. The positive response from the community showed an increased understanding of the importance of the correct use of antibiotics and the utilization of herbal medicines. It is hoped that this activity can be continued and developed to increase public awareness about health
Valid and practical integrated monitoring instrument of tahfidz qur'an
Full text linkIn implementing tahfidz qur'an learning in Islamic boarding schools, students must face many activities, and they are usually given up to five times a day. Almost all of these activities must be recorded by the teacher in a logbook so that there is the potential for slow and invalid reporting. This study aims to create an integrated monitoring instrument of tahfidz qur'an and reveal its validity and practical values. This study was conducted using a research and development (R&D) approach. The instrument was created by combining the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) development procedure and the Rapid Application Development (RAD) development procedure. Furthermore, the application of the Object-Oriented Programming (OOP) paradigm into the application creation process aims to produce a monitoring instrument that is integrated into various types of devices and can provide data and information on the student's achievement of tahfidz qur'an learning to all interested parties. The results of the validity test revealed an Aiken's V value of 0.81 so it was worthy of being tested at the implementation stage. The implementation resulted in a practicality value of 80.65% from teachers, 79.84 from parents of students, and 78.28% from the management of the boarding school. Overall, both teachers, parents of students, and management stated that this integrated monitoring instrument of tahfidz qur'an was practical during use
Optimization of chitosan and sodium tripolyphosphate as a carrier system for nanoparticles of ethanol extract of aloe vera (Aloe vera l.) as an antioxidant
Full text linkAloe Vera has phenolic active compounds that are proven to have potential antioxidant activity but are sensitive to light, easily oxidized and unstable at high temperatures. To overcome this, aloe vera is formulated into a chitosan and sodium tripolyphosphate carrier system. The interaction between chitosan and sodium tripolyphosphate for nanoparticle formation is strongly influenced by the ratio of both. The purpose of this study was to obtain the optimal formula of aloe vera extract nanoparticle preparation with chitosan and sodium tripolyphosphate carrier system with critical parameters including particle size, polydispersity index, zeta potential, sorption efficiency and antioxidant activity. Aloe vera was extracted with 96% ethanol using maceration method. Determination of chitosan and sodium tripolyphosphate concentration variation using simplex lattice design method. The results of the tests that have been carried out, the characteristics of aloe vera nanoparticle preparations with variations in the concentration of chitosan: sodium tripolyphosphate in runs 2 & 6 have the most optimal formula with the ratio of chitosan: sodium tripolyphosphate = (0.3: 0.1)
Design of an Automatic Slat Conveyor Prototype Based on PLC
Full text linkThe transfer of goods, commonly known as pick and place, which still relies on manual labor, poses challenges for industrial production companies. In automotive quality inspection, the manual transfer of vehicles by drivers between inspection stations often leads to inefficiencies and missed production targets. This research aims to implement an automated slat conveyor system controlled by PLC to optimize vehicle quality inspection. With this system, vehicles are moved automatically between stations, allowing inspections to be conducted during transit. The automation aligns with the Kaizen philosophy, emphasizing continuous improvement in production processes. The results of testing the slat conveyor automation system indicate that the system successfully achieves a maximum response time of 0.8 seconds, with a speed of 0.6 meters per second
Implementation of internet of things for leakage current monitoring system in medical equipment
Full text linkThe rise in electricity consumption, especially in the health sector, has heightened concerns about electrical safety, particularly leakage current in medical equipment. The main objective of this research is to develop an IoT-based leakage current monitoring system specifically designed for low-voltage medical devices, aiming to enhance safety and prevent electrical hazards such as electric shocks and equipment damage. The system used two current sensors module (PZEMT-004T) to measure leakage at points near the voltage source and medical components. Data were processed by a microcontroller and transmitted to a web server for real-time monitoring via mobile devices. Testing on humidifiers and ECGs showed average accuracies of 90.11% and 92.49%, respectively, within a 10 mA range. However, the system could not detect currents below the 3 mA safety threshold because of the sensors reading limitation at 10 mA, indicating a need for sensor improvements. The IoT-based system enhances medical equipment safety, with future work focusing on better sensors and AI for predictive maintenance
Optimizing Seq2Seq LSTM for Regional-to-National language translation on a web platform
Full text linkMachine translation for low-resource languages remains a significant challenge due to the lack of parallel corpora and optimized model configurations. This study developed and optimized a Seq2Seq Long Short-Term Memory (LSTM) model for Tegalan-to-Indonesian translation. A manually curated parallel corpus was constructed to train and evaluate the model. Various hyperparameter configurations were systematically tested, with the best-performing model achieving a BLEU score of 11.7381 using a dropout rate of 0.5, batch size of 64, learning rate of 0.01, and 70 training epochs. The results demonstrated that higher dropout rates, smaller batch sizes, and longer training durations enhanced model generalization and translation accuracy. The optimized model was deployed into a web-based application using Streamlit, ensuring accessibility for real-time translation. The findings highlighted the importance of hyperparameter tuning in neural machine translation for low-resource languages. Future research should explore Transformer-based architectures, larger datasets, and reinforcement learning techniques to further enhance translation quality and generalization
Test of the activity of 96% ethanol extract gel of avocado seeds (Persea americana mill.) on burn wound healing in the back of new zealand rabbits
Full text linkAvocado seeds contain secondary metabolite compounds in the form of alkaloids, flavonoids, saponins, tannins, triterpenoids and steroids. The mechanism of flavonoids in inhibiting the inflammatory process in burns is through various methods, namely inhibiting capillary permeability, inhibiting the release of serotonin and histamine to the site of inflammation. In this study, avocado seed extract was obtained by maceration method and formulated into a gel preparation with a concentration of 5%, 10% and 15%. The gel base was used as a negative control, and the gel containing 10% placenta extract and 0.5% neomycin sulfate was used as a positive control, applied to burn wounds on the backs of New Zealand rabbits with a diameter of 2 cm. The activity test of avocado seed extract gel was conducted on 3 rabbits, with each formulation applied 3 times, and the wound diameter was measured daily. This test was conducted for ten days. Avocado seeds (Persea americana Mill.) contain alkaloids, flavonoids, tannins, saponins and titerpenoids. The results of observations of the healing and drying process of burns, avocado seed extract gel (Persea americana Mill.) on the 10th day were F1 (5%) wound diameter 0.2 cm, F2 (10%) wound diameter 0.1 cm, F3 (15%) wound diameter 0 cm. Avocado seed extract gel (Persea americana Mill.) with a concentration of 15% can provide the best effect on healing burns
Identification of lung cancer using gray level co-occurrence matrix (GLCM) and artificial neural network with backpropagation algorithm
Full text linkAir pollution is a problem that occurs in various countries, including Indonesia. One of the consequences of poor air quality due to air pollution is health problems in the lungs, one of which is lung cancer. According to WHO data, lung cancer caused 1.80 million deaths in 2020. This is due to limited services to identify lung cancer early, resulting in delays in treatment. This study aims to identify lung cancer using CT-Scan image processing. The identification method uses a Backpropagation Artificial Neural Network (ANN BP) with Gray Level Co-occurrence Matrix (GLCM) feature extraction. Preprocessing is carried out to improve image quality by removing noise using a median filter. Segmentation of preprocessing results using Otsu threshold. Texture features from segmentation can be calculated from the resulting GLCM, such as Angular Second Moment (ASM)/energy, contrast, correlation, Inverse Different Moment (IDM)/homogeneity, and entropy. These values are obtained from angles of 0°, 45°, 90°, and 135°, and a distance between pixels of 2 pixels. Identification using ANN with Backpropagation algorithm. This study used images of normal lungs and lung cancer with 160 training data images and 40 test data images. The best test results were obtained with the best accuracy level of 92.5%