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All Journal Journal of Environmental Engineering and Sustainable Technology Jurnal Informatika IJGIE (International Journal of Graduate of Islamic Education)
Nuraini, Nabila
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Energy Environmental Science Mechanical Engineering Social Sciences Other

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Analysis of FastText with Support Vector Machine for Hate Speech Classification on Twitter Social Media Nuraini, Nabila; Latipah, Asslia Johar; Verdikha, Naufal Azmi
Jurnal Informatika Vol 11, No 2 (2024): October
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v11i2.21107

Abstract

Hate speech refers to sentences or words that aim to demean or insult individuals, groups, or communities based on factors such as ethnicity, religion, race, or social class. In this study, Natural Language Processing (NLP) techniques were employed using FastText feature extraction and SVM algorithm for text classification. The evaluation was conducted using F1 Score as the performance metric. The data was divided using the Cross-Validation method with 10 folds, and the experiment was performed with four SVM kernels: RBF, Linear, Polynomial, and Sigmoid. The results of this research, based on the effectiveness of the FastTextSVM method combination, demonstrate a strong performance in hate speech classification. By adopting FastText parameters from previous studies and involving four SVM kernels, this research achieved a satisfactory average F1 Score. The results obtained for the Polynomial kernel showed the best performance with an F1 Score of 0.813, followed by the Linear kernel with 0.809, the RBF kernel with 0.808, and the Sigmoid kernel with 0.805. This indicates that the F1 Score results do not show significant differences in outcomes.
NUTRITION ESTIMATION OF LEFTOVER USING IMPROVED FOOD IMAGE SEGMENTATION AND CONTOUR BASED CALCULATION ALGORITHM Adinugroho, Sigit; Sari, Yuita Arum; Maligan, Jaya Mahar; Sari, Kartika; Bihanda, Yusuf Gladiensyah; Nuraini, Nabila; Fatchurrahman, Danial
Journal of Environmental Engineering and Sustainable Technology Vol 9, No 01 (2022)
Publisher : Directorate of Research and Community Service (DRPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jeest.2022.009.01.5

Abstract

In pandemic conditions, awareness of keeping a healthy balance is necessary. One is considering food consumption and understanding its nutrition content to avert food waste. We have been developing a prototype to estimate the nutrition of leftover food, and the main problem lies in image segmentation. Therefore, we propose the Improved Food Image Segmentation (IFIS) and Contour Based Calculation (CBC) to measure the area of the segmented image instead of pixel-wise. First, the tray box image is acquired and broken down into compartments using an automated cropping algorithm. The first step of this proposed method is tray box image acquisition and dividing the compartment using an automatic cropping algorithm. Then each compartment is treated using IFIS, calculates the result of IFIS by CBC, measures the estimated leftover by Automatic Food Leftover Estimation (AFLE), and then predicts the nutritional content. The evaluation is applied by comparing the actual measurement from the Comstock method and leftover estimation by the proposed algorithm. The result shows that Root Square Means Error (RMSE) reaches 0.48 compared to the actual weighing scale and 96.67% accuracy compared to the Comstock method. Based on the results, the proposed algorithm is sufficient to be applied.
Enhancing Fourth Grade Students’ Mathematics Achievement through the Snowball Throwing Model Assisted by the Smart Wheel Nuraini, Nabila; Hidayat, Puput Wahyu; Andriani, Opi
IJGIE (International Journal of Graduate of Islamic Education) Vol. 6 No. 2 (2025): September
Publisher : Master of Islamic Studies Masters Program in the Postgraduate Institute of Islamic Studies Sultan Muhammad Syafiuddin Sambas, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37567/ijgie.v6i2.4192

Abstract

Mathematics education in Indonesia continues to face challenges such as low student engagement and achievement in elementary schools, often due to traditional teacher-centered methods. This study implemented the Snowball Throwing model assisted by Smart Wheel media to improve fourth-grade students’ mathematics achievement at SDN 112/II Purwobakti. The research employed Classroom Action Research (CAR) with two cycles, each consisting of planning, implementation, observation, and reflection stages. Data were collected through teacher and student observations, learning outcome tests, and documentation. The study involved 28 students and utilized quantitative and qualitative analysis to evaluate the effectiveness of the intervention. Results and discussion: he research employed Classroom Action Research (CAR) following Kemmis and McTaggart’s framework, conducted in two cycles to achieve measurable improvement within a practical timeframe. Participants were 28 students. Data were gathered through validated observation sheets, achievement tests, and documentation, with reliability ensured through expert review and inter-rater agreement. Quantitative data were analyzed using percentage and gain score calculations, while qualitative data were triangulated from observations and reflections. This study highlights the effectiveness of active learning models combined with interactive media in improving mathematics education. Teachers are encouraged to adopt such innovative strategies, while schools should provide support through training and resources. Future research could explore the model's applicability to other subjects or digital platforms.
Co-Authors Andriani, Opi Bihanda, Yusuf Gladiensyah Fajar Nugraha Fatchurrahman, Danial Hadi Kurniawan, Hadi Hidayat, Puput Wahyu Jaya Mahar Maligan Jayawarsa, A.A. Ketut Latipah, Asslia Johar Naufal Azmi Verdikha Sigit Adinugroho Yuita Arum Sari