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All Journal Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Social, Humanities, and Educational Studies (SHEs): Conference Series Journal of Informatics Management and Information Technology
Oky Kurniawan
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Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media Social Sciences

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Peningkatan Pembelajaran Materi Cerita Fiksi di Sekolah Dasar melalui Model Numbered Heads Together Dengan Media Audio Oky Kurniawan
Social, Humanities, and Educational Studies (SHES): Conference Series Vol 3, No 4 (2020): Social, Humanities, and Educational Studies (SHEs): Conference Series
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (261.886 KB) | DOI: 10.20961/shes.v3i4.53327

Abstract

The learning outcomes of fiction story material for 4th graders of Mandala 02 State Elementary School (SDN) Cimanggu District, Cilacap Regency were still low. The researcher applied the numbered heads together (NHT) learning model with audio as a media. This study used a Classroom Action Research (CAR) that designed in two cycles. The results showed that their average value of the class during the pre-test was 52.65, increased in the post-test results to 79.28 with an increase in classical learning completeness from 21.88% to 88.57%. Student learning activities in the first cycle of 73.91% increased in the second cycle to 77.76%. The teacher's performance score had reached the indicator of success with the final score in the first cycle of 82.5 increasing in the second cycle to 84.25. The application of the NHT learning model with audio media could improve Indonesian learning of fiction story material.
Analisis Tegangan Lebih Transien Impuls Pada Mixed Transmission Line (SUTT-SKTT) 150 KV Menggunakan Software ATP-EMTP Oky Kurniawan; Fri Murdiya
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 6 (2019): Edisi 2 Juli s/d Desember 2019
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The distribution of electrical power from the power plant to the center of the load on the transmission line can occur the electrical fault. This fault that often occurs is a transient overvoltage caused by a direct lightning stroke. Lightning stroke can cause the lightning impulses which are the dominant factor in generating the transient over voltages on 150 kV overhead lines compare to the high voltage cable lines. This investigation studied the effect of lightning stroke on the 150 kV mixed transmission lines using the ATP-EMTP (Alternative Transient Program – Electromagnetic Transient Program) software . The data analysis is carried out by simulating all line parameters and evaluating the transient overvoltage value on the transmission lines. It is shown that the highest transient overvoltage occurs when the lightning strikes on the ground static wires compared to when the lightning strikes on the phase wires. It is also shown that the use of the 150 kV mixed-lines can decrease the overvoltage caused by the direct lightning stroke. The installation of arresters on the transmission towers provides a significant reduction in over voltage caused by lightning stroke.Keywords : arrester, ATP-EMTP, lightning, mixed transmission lines, transient over voltage.
Pemodelan dan Prediksi Tingkat Pengangguran Menggunakan Pendekatan Hibrida GARCH dan BSTS Priyatna, Ade; Eva Zuraidah; Besus Maula Sulthon; Oky Kurniawan
Journal of Informatics Management and Information Technology Vol. 5 No. 3 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i3.699

Abstract

This study aims to understand and predict the unemployment rate patterns based on educational background in Indonesia between 1986 and 2024, with a focus on university graduates. The data, which was initially complex, was successfully processed into a format ready for time series analysis, and the GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model was applied to measure the volatility of unemployment. The evaluation results show that the GARCH model's assumption regarding the stability of the average unemployment rate is inaccurate, as evidenced by the large error values (RMSE 283209.26 and MAE 246252.37), indicating that this model does not fully capture the fluctuations in unemployment. The average coefficient (mu) is 436.50, and the log-likelihood is -284.05, with conditional volatility forecast values ranging from approximately 1.91e+11 to 2.79e+11. The Bayesian Structural Time Series (BSTS) model was also applied to decompose the data into long-term trend components and seasonal patterns, providing a clearer picture of unemployment movement. However, technical constraints in the implementation of BSTS using TensorFlow Probability resulted in predictions not being completed. Nevertheless, this analysis shows that the unemployment rate of university graduates is highly volatile, and improvements in the GARCH model, as well as resolution of the technical constraints in the BSTS model, are crucial for generating more accurate and reliable predictions.
Co-Authors Ade Priyatna Besus Maula Sulthon Eva Zuraidah Fri Murdiya, Fri