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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Pendidikan dan Teknologi Indonesia
Amarudin
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Engineering Materials Science & Nanotechnology Physics

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Analisis Sentimen Pengguna Twitter terhadap Konten Edukasi Dokter Detektif dengan Metode Pohon Keputusan Astri Prasasti, Iyeti; Amarudin
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 7 (2025): JPTI - Juli 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.893

Abstract

Media sosial, khususnya Twitter, telah berkembang menjadi sarana yang efektif untuk menyampaikan konten edukasi kesehatan secara luas dan interaktif. Salah satu akun yang aktif dalam menyebarkan informasi kesehatan berbasis sains adalah Dokter Detektif, yang menyajikan konten dermatologi dengan pendekatan komunikatif. Penelitian ini bertujuan untuk menganalisis sentimen pengguna Twitter terhadap konten edukasi yang disampaikan oleh akun tersebut. Metode yang digunakan adalah klasifikasi sentimen dengan algoritma Decision Tree dan dibandingkan dengan Naive Bayes. Data diperoleh melalui web scraping, lalu diproses melalui tahapan cleansing, tokenisasi, normalisasi, dan penghapusan stopword menggunakan Sastrawi. Sentimen diklasifikasikan menjadi positif dan negatif, dengan penanganan ketidakseimbangan data menggunakan Synthetic Minority Over-sampling Technique (SMOTE). Hasil penelitian menunjukkan bahwa Decision Tree menghasilkan akurasi sebesar 84% dan menunjukkan performa yang lebih stabil dibandingkan Naive Bayes berdasarkan evaluasi precision, recall, f1-score, dan confusion matrix. Temuan ini menunjukkan bahwa Decision Tree lebih efektif dalam menganalisis sentimen teks terkait konten edukatif di media sosial, khususnya dalam domain kesehatan.
Implementation of Cache Memory Technology in Improving the Performance of Modern Computing Systems Sahyudi, M; Amarudin
Jurnal Penelitian Pendidikan IPA Vol 11 No 6 (2025): June
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i6.11545

Abstract

The gap between increased processor speed and access to the main memory wall is a significant obstacle in the optimization of modern computing systems, where today's applications require processing large data with real-time responses. This study aims to analyze the effectiveness of the implementation of cache memory technology in improving the performance of modern computing systems, focusing on: 1) identification of key parameters that affect the effectiveness of cache on various workloads, 2) evaluation of adaptive cache replacement algorithms, 3) analysis of performance trade-offs with energy efficiency and security, and 4) formulation of optimal cache architecture recommendations. The research method uses a qualitative approach through a comprehensive literature study of 2020-2024 publications from the academic databases of IEEE Xplore, ACM Digital Library, Scopus, ScienceDirect, and SINTA with thematic content analysis and comparative evaluation of various cache technology implementations. The results showed that: the multi-level caching architecture increased system throughput by an average of 37.5%; adaptive algorithms such as RRIP increased hit rate by 23.7% compared to conventional LRU; SRAM/STT-MRAM hybrid technology saves up to 44.3% energy with minimal performance overhead; and the proposed integrated framework resulted in a 34.8% performance increase with a 27.5% reduction in energy consumption. Further research is recommended to implement and experimentally test the proposed framework on various computing platforms, develop more adaptive machine learning-based cache replacement algorithms, and explore the integration of cache technology with neuromorphic computing architectures.
Co-Authors Astri Prasasti, Iyeti Sahyudi, M