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All Journal Jurnal Ilmiah Ilmu Terapan Universitas Jambi Tematik: Jurnal Penelitian Pendidikan Dasar
Kusrini, Sri
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Education Engineering Industrial & Manufacturing Engineering

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Peningkatan Aktivitas dan Hasil Belajar Materi Tari Pendek Bertema Melalui Metode Field Trip pada Siswa Kelas II SD Negeri 010 Sei Simpang Dua Kusrini, Sri
Tematik: Jurnal Penelitian Pendidikan Dasar Vol. 2 No. 2 (2023)
Publisher : Medan Resource Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57251/tem.v2i2.1260

Abstract

This study aimed to improve teacher performance, student engagement, and learning outcomes in Thematic Short Dance for third-grade students at SD 010 Sei Simpang Dua. Twenty-six students from SD Negeri Kalibatur in the academic year 2021/2022 participated in the two-cycle research, involving planning, implementation, observation, and reflection. In that academic year, students' learning outcomes were hindered by a teacher-centered approach, limiting their creativity and engagement. To address this, the teacher implemented a field trip method in Thematic Short Dance. Results showed improvement from cycle I to cycle II. Average student learning outcomes increased from 75.40 to 80.65, with mastery rising from 69.23% to 88.46%. Student activity during learning also improved from 71.93% to 78.77%. Teacher performance rose from 80.42 (B) to 88.72 (A). The field trip method effectively enhanced teacher performance, student engagement, and learning outcomes. This research contributes to teaching methods in Arts and Skills (Seni Budaya dan Keterampilan - SBK) at the elementary school level.
Estimation of Queue Length at Signalized Intersections Using Artificial Neural Network Respati, Sara; Isram, Mohamad; Fatmawati, Fatmawati; Kusrini, Sri
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Desember 2022
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v6i2.22958

Abstract

Signalized intersections are points in the transportation network where vehicles from various directions meet. They are critical points for traffic jams, and this is an application of applied science in the technology field. The vehicle queue length is one of the performance parameters of a signalized intersection. Long queues of vehicles pose a high risk of accidents involving many vehicles. Feedback signal control (actuated signal control) can improve intersection performance. One variable that can be used as feedback input is the vehicle queue length. Traffic in Indonesia is mixed traffic where various vehicles use the same road lane and with low lane discipline. This causes the traffic system to become complex stochastic, and non-linear. Modeling queue length using a static linear algorithm cannot capture the phenomenon of this complex traffic system. Therefore, this research aims to build a machine learning-based queue length model using artificial neural networks (ANN). This model studies the traffic system with historical data so that it can model queue lengths with reasonable accuracy through the training process. The estimation model was built and applied to the Muara Rapak signalized intersection, Balikpapan. Data on queue length for 10 days, 2 hours/day, was obtained using CCTV and direct field surveys. The model testing results show that ANN has a good level of accuracy with MAE, RMSE, and MAPE of 3.8 m, 4.9 m, and 6%, respectively.
Co-Authors Fatmawati Fatmawati Isram, Mohamad Respati, Sara