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All Journal Al-Zayn: Jurnal Ilmu Sosial & Hukum Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Muhammad Irwanto
Unknown Affiliation
Religion Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media

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Urgensi Utusan Khusus Presiden Berdasarkan Perpres No. 137 Tahun 2024 Perspektif Fiqh Siyasah Askana Fikriana; Muhammad Irwanto; Sri Sulistiya
Al-Zayn: Jurnal Ilmu Sosial, Hukum & Politik Vol 3 No 3 (2025): 2025
Publisher : Yayasan pendidikan dzurriyatul Quran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61104/alz.v3i3.1465

Abstract

Pembentukan tujuh utusan khusus presiden dalam Kabinet Merah Putih di era pemerintahan Presiden Prabowo Subianto menimbulkan dinamika baru dalam struktur kelembagaan negara. Keberadaan lembaga non-struktural ini, yang bidang tugasnya menyerupai kementerian, menimbulkan pertanyaan mengenai urgensi dan legitimasi yuridisnya. Penelitian ini bertujuan untuk menganalisis fungsi dan peran utusan khusus presiden dalam konteks hukum positif Indonesia serta meninjau urgensinya melalui pendekatan fiqh siyasah, khususnya dalam kerangka konsep wazir al-tanfidz yang dikemukakan oleh Imam al-Mawardi. Metode yang digunakan adalah penelitian hukum normatif dengan pendekatan konseptual, perundang-undangan, dan analitis. Hasil penelitian menunjukkan bahwa keberadaan utusan khusus presiden sah secara hukum selama tidak melanggar batas kewenangan kementerian, dan dalam perspektif fiqh siyasah, lembaga ini dapat dikategorikan sebagai pelaksana teknis yang bertugas menjalankan amanah politik kepala negara. Implikasi dari temuan ini menekankan pentingnya regulasi pelaksana yang jelas agar tidak terjadi tumpang tindih kewenangan serta perlunya pengawasan terhadap kinerja lembaga non-struktural ini agar sejalan dengan prinsip good governance
Optimization of Smart Building Electrical Load Prediction Using Long Short-Term Memory Ali Aqil; Nugraha, Yoga Tri; Sumita Wardani; Mawardi; Muhammad Irwanto
Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 13 No 1 (2026): Jurnal Ecotipe, April 2026
Publisher : Jurusan Teknik Elektro, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/hn0m4j24

Abstract

The advancement of smart building technologies requires energy management systems that are both efficient and capable of adapting to dynamic operational conditions. A key component of such systems is reliable electrical load forecasting, as building energy demand is affected by environmental conditions, occupancy behavior, and operational activities that exhibit nonlinear and time-dependent characteristics. This study explores the use of the Long Short-Term Memory (LSTM) approach for forecasting smart building electricity consumption based on multivariate time-series data. The input dataset incorporates temporal features, ambient temperature, humidity levels, occupancy-related patterns, and major electrical load components within the building. The research workflow consists of data preprocessing, normalization, time-series construction using a sliding window strategy, LSTM model training, and evaluation of forecasting performance. The findings indicate that the building’s electricity demand varies approximately between 6 kW and 17 kW, with an average load ranging from 11 to 12 kW. Performance assessment yields an RMSE of about 3 kW and a MAPE of roughly 25%. The largely symmetric error distribution around zero suggests minimal systematic bias in the predictions, although the model’s accuracy during peak demand periods remains limited.
Co-Authors Ali Aqil Askana Fikriana Mawardi Sri Sulistiya Sumita Wardani Yoga Tri Nugraha