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All Journal Wahana Didaktika Prosiding Universitas PGRI Palembang Pendas : Jurnah Ilmiah Pendidikan Dasar Parafrase: Jurnal Kajian Kebahasaan dan Kesastraan Esteem Journal of English Study Programme Wahana Dedikasi : Jurnal PkM Ilmu Kependidikan JELT (Jambi-English Language Teaching) Blockchain Frontier Technology (BFRONT)
Aswadi Jaya
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Arts Humanities Computer Science & IT Control & Systems Engineering Education Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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PENGARUH MODEL PEMBELAJARAN MULTILITERASI TERHADAP HASIL BELAJAR BAHASA INDONESIA PADA SISWA KELAS IV SD NEGERI 30 PALEMBANG Septiana; Aswadi Jaya; Mega Prasrihamni
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 02 (2025): Volume 10, Nomor 02 Juni 2025 publish
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i02.28088

Abstract

This study aims to analyze the impact of implementing a multiliteracy learning model on improving Indonesian language learning outcomes among fourth-grade students at SD Negeri 30 Palembang. This research employs a quantitative approach using a quasi-experimental method with a nonequivalent control group design. The study subjects consist of two classes: one serving as the experimental group and the other as the control group. Data were collected using objective multiple-choice tests to measure students' learning achievement. The data analysis results indicate a significant difference in learning outcomes between the experimental and control groups. The average posttest score of students in the experimental class was 71.94, which was higher than the control class, which had an average score of 52.58. The t-test analysis showed a significance value of 0.001, which is less than α = 0.05. Therefore, H₀ is rejected and Hₐ is accepted. It can be concluded that there is a significant difference between the two groups, and the application of the multiliteracy learning model assisted by audiovisual media has a positive contribution to improving Indonesian language learning outcomes compared to the conventional learning model.
Self Supervised Transformers for High Dimensional Time Series Anomaly Detection Aswadi Jaya; Derlina; Qurotul Aini; Agung Rizky; Richard Evans
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1078

Abstract

This study addresses anomaly detection in high dimensional time series data within the context of Artificial Intelligence (AI) driven software development, where modern systems generate large temporal data streams and reliable monitoring remains difficult due to noise, complexity, and limited labeled anomalies. The objective of this research is to develop an effective and scalable anomaly detection framework based on self supervised transformer models that can learn meaningful temporal representations without heavy reliance on manual annotation. The proposed method applies self supervised pretraining through masked sequence reconstruction and contrastive temporal learning on large scale, unlabeled multivariate time series datasets, followed by transformer based attention mechanisms to capture long range dependencies and compute anomaly scores. Experiments are conducted using benchmark datasets and real world system log data implemented with Python based deep learning tools and transformer architectures to evaluate detection performance. The results indicate that the proposed approach improves detection accuracy and reduces false positive rates compared to traditional statistical techniques and supervised deep learning models, particularly in high dimensional and low label settings. In conclusion, integrating self supervised learning with transformer architectures provides a robust and generalizable solution for time series anomaly detection, contributing to software analytics and monitoring systems by lowering labeling costs and improving adaptability across application domains.
Co-Authors Agung Rizky Alfina Sundari Amin Rohmat Anggun Mahesti Chandra Kurniawan Dea Khusnul Khotimah Derlina Evi Rosmiyati Fitri Nur Hakiki Hermansyah Hermansyah Hermansyah Januardi, Januardi Masnunah, Masnunah Mega Prasrihamni Neta Dian Lestari Noviati Noviati Nurlina Nurlina Pratiwi, Nova Qorry Pramesti Regita Cahyani Qurotul Aini Richard Evans Riswan Aradea Septiana