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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Minda Baharu International Journal of Social Learning (IJSL) Jurnal Pendidikan Teknik Sipil (JPTS) Scientific Journal of Informatics
Rini Anggrainingsih
Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Sebelas Maret, Surakarta
Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences Other

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Sentence embedding to improve rumour detection performance model Anggrainingsih, Rini; Wihidayat, Endar Suprih; Widoyono, Bambang
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp115-121

Abstract

Recently, most individuals have preferred accessing the most recent news via social media platforms like Twitter as their primary source of information. Moreover, Twitter enables users to post and distribute tweets quickly and unsupervised. As a result, Twitter has become a popular platform for disseminating false information, such as rumours. These rumours were then propagated as accurate and influenced public opinion and decision-making. The issue will arise when a decision or policy with substantial consequences is made based on rumours. To avoid the negative impacts of rumours, several researchers have attempted to detect them automatically as early as feasible. Previous studies employed supervised learning methods to identify Twitter rumours and relied on feature extraction algorithms to extract tweet content and context elements. However, manually extracting features is time-consuming and labour-intensive. To encode each tweet's sentence as a vector based on its contextual meaning, we proposed utilising Bidirectional Encoder Representation of Transformer (BERT) as a sentence embedding. We then used these vectors to train some classifier models to detect rumours. Finally, we compared the performance of BERT-based models to feature engineering-based models. We discovered that the suggested BERT-based model improved all parameters by around 10% compared to the feature engineering-based classification model.
Exploration of Whatsapp Application as Learning Media in Vocational Schools Reviewed from the Teacher's Perspective Sekarkedhaton, Rhepita Hindun Pangesti; Sumarni, Sri; Isnantyo, Fajar Danur; Anggrainingsih, Rini
Jurnal Pendidikan Teknik Sipil Vol. 6 No. 2 (2024): November
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpts.v6i2.77541

Abstract

Background: Whatsapp is widely used as a learning medium to make it easier for teachers to send files of school assignment documents and learning materials to students. This study aims to explore the effectiveness of use, constraints, and solutions in using the Whatsapp application as a learning medium in vocational schools from the teacher's perspective. This research is a qualitative study with a narrative inquiry approach. Methods: The sampling method using purposive sampling obtained a sample size of 6 participants including teachers who have active teaching status and have implemented WhatsApp as a learning medium in their subjects. Interviews were conducted to collect data. Data were analyzed by content analysis using the QSR Nvivo application. Results: 1) the exploration of the use of Whatsapp application as a learning medium in vocational schools in the teacher's perspective was obtained in two categories, including, a) media: discussion, information, evaluation, communication, and b) learning process: offline learning support, and material sharing. (2) obstacles in the use of the Whatsapp application as a learning medium in vocational schools from the teacher's perspective include, a) user aspects: competence in using technology, lack of activity, lack of focus, and b) technical: wifi network, internet quota, and student devices. (3) Solutions in overcoming obstacles in using the Whatsapp application as a learning medium in vocational schools from the teacher's perspective include, a) school facilities: wifi network, whiteboards, and b) improvement efforts: interaction, and competence.Conclusion: The use of WhatsApp applications as a learning media in SMK from the perspective of teachers is said to be effectively used as a medium and support the learning process. The obstacles that teachers often encounter include user constraints and technical obstacles, with the solution taken to improve user competence and optimize the school facilities that have been provided.
PENINGKATAN KEAMANAN LINGKUNGAN DENGAN PENERAPAN CCTV DI DUKUH SRIMULYO Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Hendrasuryawan, Brilyan; Setiadi, Haryono; Doewes, Afrizal; Anggrainingsih, Rini; Wijayanto, Ardhi
MINDA BAHARU Vol 8, No 2 (2024): Minda Baharu
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/jmb.v8i2.7015

Abstract

. Berdasarkan kegiatan Pengabdian kepada Masyarakat (PkM) yang sudah terlaksana, yakni penerapan closed-circuit television (CCTV) di Dukuh Srimulyo, Boyolali, didapatkan hasil bahwa dapat membantu menyelesaikan masalah mitra. Adapun permasalahan yang ditemukan adalah kurangnya pengawasan yang dapat memberikan rasa aman kepada warga. Hal ini terjadi akibat banyaknya jalur kendaraan yang dapat melintasi wilayah tersebut tetapi belum diterapkan adanya pengawasan secara real-time. PkM ini bertujuan untuk mengatasi masalah keterbatasan tersebut. Solusi yang ditawarkan kepada mitra adalah penerapan CCTV yang dapat merekam kejadian di titik yang penting. Pendampingan dilakukan dalam bentuk pelatihan penggunaan CCTV dan penyediaan fasilitas untuk pengawasan yang akan digunakan oleh mitra. Adapun hasil dari PkM ini adalah ditemukan bahwa para warga memberikan sambutan baik dengan diterapkannya CCTV ini pada kegiatan yang dilakukan berdasarkan umpan balik yang diberikan setelah kegiatan selesai. Selanjutnya CCTV yang terpasang pada titik penting berjumlah dua dan telah melalui proses penelaahan bersama dengan warga. Adapun dampak yang diperoleh secara nyata setelah PkM ini berakhir adalah sebagian besar peserta dapat melakukan pengawasan secara mandiri menggunakan aplikasi aplikasi CCTV yang telah terpasang
Needs Analysis of Link and Match on Research Methodology Course: Student-Lecturer Based Teaching and Learning Experiences Sumarni, Sri; Akhyar, Muhammad; Nizam, Muhammad; Widyastono, Herry; Anggrainingsih, Rini
International Journal of Social Learning (IJSL) Vol. 5 No. 1 (2024): December
Publisher : Indonesian Journal Publisher in cooperation with Indonesian Social Studies Association (APRIPSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijsl.v5i1.294

Abstract

Research methodology is a mandatory course in higher education. Students are expected to be able to compile research and solve problems according to their field of study. However, many students still have difficulty operationalizing research competency indicators. This research aims to reveal learning needs through the experience of lecturers teaching and students learning in research methodology courses. This research uses an interpretive relativity paradigm with a narrative inquiry approach. Lecturers and students as participants. Data collection techniques using interviews. Data were analyzed using content analysis. By exploring lecturers' teaching experiences and students' learning experiences, information on learning needs is obtained. The learning needs include learning outcomes, literacy technology, learning time, lecturer's teaching experience, obstacles or shortcomings faced by lecturers, and the final learning product. Through the link and match between the learning needs of students and the fulfillment of learning needs from lecturers, a research methodology learning needs analysis is obtained, including learning outcomes, technological literacy, learning time, lecturer teaching experience, obstacles lecturers face, and the final learning product.
Which Features Matter Most? Evaluating Numerical and Textual Features for Helpfulness Classification in Imbalance Dataset using XGBoost Kirani, Anindita Putri; Saptono, Ristu; Anggrainingsih, Rini
Scientific Journal of Informatics Vol. 12 No. 4: November 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i4.33443

Abstract

Purpose: This study aims to develop and realistically evaluate a reliable model for identifying helpful online reviews, particularly in the context of Indonesian-language texts, which are often informal and challenging. Methods: This study addresses several key challenges in predicting review helpfulness: the relative effectiveness of numerical features from metadata compared with traditional text representations (TF-IDF, FastText) on noisy data; the impact of severe class imbalance; and the limitations of standard validation compared with time-based validation. To address these challenges, we built an XGBoost model and evaluated various feature combinations. A hybrid approach combining SMOTE and scale_pos_weight was applied to handle class imbalance, and the best configuration was further assessed using time-based validation to better simulate real-world conditions. Result: The results show that the model based on numerical features consistently outperformed the text-based model, achieving a peak macro F1-score of 0.7214. Compared to the IndoBERT baseline (F1-score = 0.6400) and the RCNN FastText baseline (F1-score = 0.5317), this indicates that simpler feature-driven models can provide more reliable predictions under noisy review data. Time-based validation further revealed a performance decline of up to 8.06%, confirming the presence of concept drift and highlighting that standard validation tends to yield overly optimistic estimates. Novelty: The main contribution of this research lies in offering a robust methodology while demonstrating the superiority of metadata-based approaches in this context. By quantifying performance degradation through temporal validation, this study provides a more realistic benchmark for real-world applications and highlights the critical importance of regular model retraining. 
Co-Authors Afrizal Doewes, Afrizal Dewi Wisnu Wardani Hasan Dwi Cahyono Hendrasuryawan, Brilyan Herry Widyastono, Herry Isnantyo, Fajar Danur Kirani, Anindita Putri Muhammad Akhyar Muhammad Nizam Ristu Saptono Sekarkedhaton, Rhepita Hindun Pangesti Setiadi, Haryono Sri Sumarni Widoyono, Bambang Wihidayat, Endar Suprih Wijayanto, Ardhi