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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Risalah Fisika
Arief Hermanto
Jurusan Fisika FMIPA UGM Sekip Utara Yogyakarta 55281
Astronomy Computer Science & IT Earth & Planetary Sciences Education Materials Science & Nanotechnology Physics Other

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Simulasi Komputer Pengaruh Efek Proksimitas pada Medan Kritis Superkonduktor Anwar, Fuad; Nurwantoro, Pekik; Hermanto, Arief
Risalah Fisika Vol 1, No 2 (2017): Risalah Fisika ISSN 2548-9011
Publisher : Physical Society of Indonesia (PSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.304 KB) | DOI: 10.35895/rf.v1i2.21

Abstract

Telah dibuat kajian pengaruh syarat batas efek proksimitas pada penyelesaian komputasi persamaan Ginzburg-Landau Gayut Waktu. Bahan kajian adalah superkonduktor berbentuk kotak yang berbatasan dengan bahan lain pada keempat sisinya dan dipengaruhi medan magnet luar. Metode pembuatan simulasi didasarkan pada persamaan Ginzburg-Landau gayut waktu serta persamaan syarat batas parameter benahan dan syarat batas medan magnet. Persamaan-persamaan tersebut lalu didiskretkan dengan menggunakan metode yU. Hasil kajian menunjukkan bahwa nilai medan kritis permukaan membesar, medan kritis rendah mengecil pada ukuran bahan Nx×Ny = 12×12 dan membesar pada ukuran bahan Nx×Ny = 32×32 jika nilai panjang ekstrapolasi membesar. Kata kunci: efek proksimitas, persamaan TDGL, superkonduktor
The Existence of Fourier Coefficients and Periodic Multiplicity Based on Initial Values and One-Dimensional Wave Limits Requirements Jufriansah, Adi; Khusnani, Azmi; Hermanto, Arief; Toifur, Mohammad; Prasetyo, Erwin
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Vol 10, No 2 (2020)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v10n2.p146-157

Abstract

Physical systems in partial differential equations can be interpreted in a visual form using a wave simulation. In particular, the interpretation of the differential equations used is in the nonlinear hyperbolic model, but in its completion, there are some limitations to the stability requirements found. The aim of this study is to investigate the analytical and numerical analysis of a wave equation with a similar unit and fractal intervals using the Fourier coefficient. The method in this research is to use the analytical solution approach, the spectral method, and the finite difference method. The hyperbolic wave equation's analytical solution approach, illustrated in the Fourier analysis, uses a pulse triangle. The spectral method minimizes errors when there is the addition of the same sample grid points or the periodic domain's expansion with a trigonometric basis. Meanwhile, different ways offer a more efficient solution. Based on the research results, the information obtained is that the Fourier analysis illustrates the pulse triangle use to solve the solution. These results are also suitable for adding sample points to the same spectra. Fourier analysis requires a relatively long time to solve one pulse triangle graph to need another solution, namely the finite difference method. However, its use is still limited in terms of stability when faced with more complex problems.
Hybrid Lexicon-Machine Learning Approach for Aspect-Based Sentiment Analysis on Large-Scale Indonesian App Reviews: A Case Study of Telegram Indriyatmoko, Toto; Hermanto, Arief
Journal of Applied Informatics and Computing Vol. 10 No. 5 (2026): October 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i5.14141

Abstract

Mobile application reviews provide critical unstructured feedback for developers, yet processing large-scale Indonesian app reviews remains hindered by informal language noise and severe class imbalance. While deep learning offers strong context modeling, its computational burden is impractical for industrial-scale deployment exceeding hundreds of thousands of entries. This study proposes a scalable, computationally efficient Hybrid Lexicon-Machine Learning framework for Aspect-Based Sentiment Analysis (ABSA) on large-scale Indonesian user reviews, using Telegram as a case study. We processed 399,527 reviews from the Google Play Store through a pipeline integrating TF-IDF n-grams, explicit domain-adapted lexicon scoring (incorporating negation and intensifier heuristics), and review length metadata into a LightGBM classifier. To overcome the scarcity and linguistic ambiguity of neutral ratings, a binary classification strategy (Positive vs. Negative/Critical) was implemented. The model achieved Accuracy of 80.4%, Macro-F1 of 76.7%, and AUC-ROC of 0.855 on a strictly held-out test set, peaking at 0.933 for Privacy. Ablation experiments confirm that incorporating explicit lexicon scores consistently improves Macro-F1 by up to 5.1% over standalone TF-IDF. Aspect distribution revealed critical bottlenecks in Privacy (73.0% negative) and Notification (66.1% negative), providing actionable roadmaps for software maintenance.
Co-Authors Adi Jufriansah Anwar, Fuad Azmi Khusnani Indriyatmoko, Toto Moh. Toifur Pekik Nurwantoro PRASETYO, ERWIN