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PROSPEK PENGGUNAAN TEKNOLOGI BERSIH UNTUK PEMBANGKIT LISTRIK DENGAN BAHAN BAKAR BATUBARA DI INDONESIA Sugiyono, Agus
Jurnal Teknologi Lingkungan Vol. 1 No. 1 (2000)
Publisher : BRIN Publishing (Penerbit BRIN)

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Abstract

Hubungan yang erat antara penggunaan teknologi dan kerusakan lingkungan telah menyadarkan masyarakat untuk melakukan modifikasi dan inovasi dari teknologi yang ada saat ini. Penggunaan bahan bakar fosil, seperti batubara untuk pembangkit listrik akan dapat meningkatkan emisi partikel, SO2, NOx, dan CO2. Adanya peraturan pemerintah tentang standar emisi untuk pembangkit listrik di Indonesia, mendorong upaya untuk selalu mengurangi emisi tersebut. Batubara diperkirakan paling dominan digunakan sebagai bahan bakar untuk pembangkit listrik di masa datang. Penggunaan batubara dalam jumlah yang besar akan meningkatkan emisi gas buang di udara. Salah satu cara untuk mengurangi emisi adalah dengan menggunakan teknologi bersih. Ada dua cara dalam menerapkan teknologi tersebut, yaitu pertama diterapkan pada tahapan setelahpembakaran dan kedua diterapkan sebelum pembakaran batubara. Pada tahap pertama dapat digunakan teknologi denitrifikasi, desulfurisasi dan penggunaan electrostatic precipitator. Pada tahap kedua menggunakan teknologi fluidized bed combustion, gasifikasi batubara, dan magneto hydrodynamic.
Effectiveness of Topical use of Onion and Ginger for Joint Pain Cynthia, Fransisca; Priskila, Onny; Ang, Suryawan; Sugiyono, Agus; Ferdinand, Ferdinand
Jurnal KESANS : Kesehatan dan Sains Vol 2 No 10 (2023): KESANS: International Journal of Health and Science
Publisher : Rifa'Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54543/kesans.v2i10.197

Abstract

Introduction: Onion and ginger have been widely used as painkillers empirically. Its use is always associated with administration by mouth rather than application to the skin. Elderly people often experience joint pain in connection with their aging condition or because of the disease they suffer. Objective: This literature study is to determine the effectiveness of giving onion and ginger as pain relievers in topical administration to joint pain areas. Method: literature study with inclusion criteria, namely: articles including primary literature, articles in English or Indonesian, articles containing onion for topical joint pain, articles containing ginger for topical joint pain, research articles available in full text, and articles in the form of original articles. Result and Discussion: Three journals were found with a total of 101 elderly respondents suffering from joint pain. Given shallot compresses, 10% and 20% ginger cream, and ginger plaster Measurement of the pain scale by means of the visual analog scale and the WOMAC questionnaire The results showed that all groups of shallot compresses, 10% and 20% ginger cream, and ginger plaster reduced the joint pain of elderly respondents compared to the control group. Conclusion: Based on the literature study conducted, it is concluded that the administration of onion and ginger is effective for reducing joint pain in the elderly in all types of topical administration, whether given in the form of compresses, extract creams, or plasters
Enhancing wind energy prediction accuracy with a hybrid Weibull distribution and ANN model: a case study across ten locations in Java Island, Indonesia Fithri, Silvy Rahmah; Hesty, Nurry Widya; Wijayanto, Rudi P.; Pranoto, Bono; Wijaya, Prima Trie; Faqih, Akhmad; Kusuma, Wisnu Ananta; Nurrohim, Agus; Sugiyono, Agus; Yudiartono, Yudiartono
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 1: January 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i1.pp180-190

Abstract

Accurate wind speed forecasting is essential for optimizing renewable energy (RE) systems, especially in coastal and island regions with high variability. This study proposes a hybrid predictive model that combines Weibull distribution parameters with artificial neural networks (ANN) to enhance forecasting accuracy. Using ten years of hourly NASA POWER data from 10 locations across Java Island, 24 scenarios were tested with varying combinations of Weibull and meteorological variables. Results demonstrate that incorporating both Weibull shape (k) and scale (c) parameters significantly improves performance, with the best configuration (Scenario 1) achieving a MAPE of 0.44% in Garut. Excluding one or both parameters sharply reduced accuracy, with errors rising up to 35.12%. Beyond technical accuracy, the findings emphasize the practical relevance of Weibull-informed ANN models for energy planning. Reliable forecasts support better wind resource assessment, grid integration, and investment decisions, reducing uncertainties that often hinder wind power deployment. By providing accurate and stable predictions across diverse locations, this approach offers policymakers and planners a robust tool to accelerate RE development and meet national energy targets.