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All Journal Tadrib: Jurnal Pendidikan Agama Islam Jurnal E-Komtek
Aulia Nur Aini
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Computer Science & IT Education Electrical & Electronics Engineering Environmental Science Library & Information Science Mechanical Engineering Social Sciences

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The Effect of Islamic Religious Education Teachers on Improving Student Behaviour and Personality at SMP Muhammadiyah 8 Surakarta Aulia Nur Aini; Mohammad Zakki Azani
Tadrib: Jurnal Pendidikan Agama Islam Vol 10 No 1 (2024): Tadrib: Jurnal Pendidikan Agama Islam
Publisher : Program Studi Pendidikan Agama Islam Fakultas Ilmu Tarbiyah Dan Keguruan UIN Raden Fatah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/5x5a2e59

Abstract

The influence of Islamic religion teachers in changing the behaviour and personality of students at SMP Muhammadiyah 8 Surakarta and the efforts of Islamic religion teachers as a means of motivation, directing, analysing. Responsible for shaping the character, knowledge, faith and commitment of students. Islamic Religious Education (PAI) should be used as a means to teach noble morals to children by placing Islamic Religious Teachers (PAI) as teachers and providing appropriate methods and media related to Islamic religion. Factors that help and hinder student character building at SMP Muhammadiyah 8 Surakarta come from teachers, parents, peers, and the environment in the community.
An Analysis and Forecasting of Electricity Demand Using the Triple Exponential Smoothing Method Aulia Nur Aini; Hakim, Dimara Kusuma; Feri Wibowo; Elindra Ambar Pambudi
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2483

Abstract

Electricity is a basic necessity required in daily life, supporting various activities, including economic development. The growing demand for electricity requires reliable and efficient planning and management of the power system. Electricity demand forecasting is essential due to its fluctuating nature and seasonal patterns. This study aims to forecast electricity demand using the Triple Exponential Smoothing method with data from the Australian Energy Market Operator (AEMO) for the New South Wales region, Australia, covering the period from January 2015 to February 2025. This method is chosen because it effectively handles time series data patterns consisting of level, trend, and seasonal components. The forecasting results show that this method is capable of closely following the actual data patterns and produces a Mean Absolute Percentage Error (MAPE) of 2.89%, indicating a very good performance. This model is expected to serve as a basis for decision-making in anticipating future fluctuations in electricity demand.
Co-Authors Dimara Kusuma Hakim Elindra Ambar Pambudi Feri Wibowo Mohammad Zakki Azani