LAPORAN KEGIATAN PRAKTIK PENGALAMAN LAPANGAN LOKASI SMA KOLOMBO SLEMAN

Praktik Pengalaman Lapangan (PPL) merupakan program yang wajib diikuti oleh setiap mahasiswa jurusan kependidikan. Kegiatan PPL ini bertujuan agar mahasiswa lebih memahami teori mengajar yang selama ini di dapatkan di perkuliahan. Karena setiap ilmu yang didapat apabila dipraktekkan akan lebih tersimpan lama dibandingkan jika hanya dibaca maupun ditulis. Untuk itulah mahasiswa jurusan kependidikan harus melewati kegiatan PPL ini. Sebagai salah satu mahasiswa di Universitas egeri Yogyakarta, maka prktikan juga mengikuti kegiatan PPL dilaksanakan pada tanggal 15 Juli-15 September 2016 di SMA Kolombo Sleman. Mahasiswa yang melakukan praktik PPL di SMA Kolombo berjumlah 6 orang, yang terdiri dari 2 orang program Pendidikan Bahasa Inggris, 2 orang program Pendidikan Ekonomi, dan 2 orang program Pendidikan sejarah. Program kegiatan PPL dapat terlaksana dengan baik dan lancar berkat adanya bimbingan dan arahan dari guru pembimbing dan dosen pembimbing selama praktek mengajar serta peran aktif peserta didik selama berlangsungnya kegiatan belajar mengajar (KBM). Selain itu terlaksananya program PPL ini tidak terlepas dari dukungan dan bantuan dari pihak sekolah yang telah memberikan keluasan kesempatan kepada para mahasiswa PPL untuk mengembangkan potensi yang dimilikinya. Namun terdapat hambatan yang ditemui praktikan dalam melaksanakan PPL yakni praktikan masih kurang dalam penguasaan kelas, selama pembelajaran berlangsung seringkali praktikan mengalami kesulitan dalam mengontrol siswa terutama saat penguasaan kelas dan menerangkan materi karena ada sebagian siswa yang tidak memperhatikan. Ketika diberi umpan balik, untuk menanyakan kejelasan dan ketidakjelasan siswa terhadap materi, hanya sedikit siswa yang memberikan respon. Praktikan menyadari bahwa munculnya hambatan dalam pelaksanaan kegiatan PPL adalah hal yang wajar. Karena hal ini merupakan salah satu tantangan yang harus dihadapi praktikan selama mengajar

TEACHERS’ STRATEGIES IN TEACHING SPEAKING AT THE EFFECTIVE ENGLISH CONVERSATION COURSE (EECC PARE)

ABSTRACT Zuhdi, Syifaul. Student Registered Number. 12203183177. 2022. “The Teachers’ Strategies in Teaching Speaking at the Effective English Conversation Course (EECC Pare)”. Sarjana Thesis. English Education Department. Sayyid Ali Rahmatullah Islamic State University (UIN SATU) of Tulungagung. Advisor: Dr. Hj. Nanik Sri Rahayu, M.Pd. Keywords: Speaking, Strategies, Teaching Strategies Speaking is one of the important skills when we learn English Language besides listening skill, writing skill and reading skill. Speaking has relation to general information and knowladge. Because of the importantce of speaking skill in learning, teacher must be able to provide the right strategies to get maximum result. This research aims to discover and discribe (1) What are the teachers’ strategies in teaching speaking and (2) How do students respond to the strategies applied by the teachers in EECC Pare The research design of this study is a descriptive design and a qualitative method. Data source of this research were English teacher and students of EECC Pare. The data of this study are obtained through in-depth interviews and observations. The analysis used was method of Miles and Huberman to analyze the data, including data reduction, data display, and drawing conclusions. In order to check the credibility of the data, the researchers used data sources and methodological triangulation in this study. In the use of data source triangulation, researchers collect data from multiple sources to check the validity of the data. At the same time, researchers also use a variety of methods to collect data. The result of this study revealed that the teachers used many stratgies when teaching speaking. The strategies used public speaking, group discussion, dialogue and telling story, reading aloud, speech and strategie drill. From the strategies used when teaching speaking class, the students' responses were positive. Can be seen with students who are enthusiastic, happy, comfortable in participating in speaking lessons followed by students practicing it outside the classroom with their study groups

Monitoring early-successional trees for tropical forest restoration using low-cost UAV-based species classification

Logged forests cover four million square kilometres of the tropics, capturing carbon more rapidly than temperate forests and harbouring rich biodiversity. Restoring these forests is essential to help avoid the worst impacts of climate change. Yet monitoring tropical forest recovery is challenging. We track the abundance of early-successional species in a forest restoration concession in Indonesia. If the species are carefully chosen, they can be used as an indicator of restoration progress. We present SLIC-UAV, a new pipeline for processing Unoccupied Aerial Vehicle (UAV) imagery using simple linear iterative clustering (SLIC)to map early-successional species in tropical forests. The pipeline comprises: (a) a field verified approach for manually labelling species; (b) automatic segmentation of imagery into ’superpixels’ and (c) machine learning classification of species based on both spectral and textural features. Creating superpixels massively reduces the dataset’s dimensionality and enables the use of textural features, which improve classification accuracy. In addition, this approach is flexible with regards to the spatial distribution of training data. This allowed us to be flexible in the field and collect high-quality training data with the help of local experts. The accuracy ranged from from 74.3% for a four-species classification task to 91.7% when focusing only on the key early-succesional species. We then extended these models across 100 hectares of forest, mapping species dominance and forest condition across the entire restoration project.NE/N008952/

Monitoring early-successional trees for tropical forest restoration using low-cost UAV-based species classification

Peer reviewed: TrueAcknowledgements: We thank Rhett Harrison for his significant input into grant writing. We are grateful to Dr. Tuomo Valkonen, whose early attempt to classify species without delineating trees was unsuccessful but paved the way for the development of more sophisticated approaches. We wish to thank all partners at Hutan Harapan for their help with managing the UAV and tree data collection at Hutan Harapan. We particularly wish to thank Adi, Agustiono, and Dika for their support with UAV flying and data collection. We are also very grateful for the support from members of Universitas Jambi who supported the logistics of our collaboration.Logged forests cover four million square kilometers of the tropics, capturing carbon more rapidly than temperate forests and harboring rich biodiversity. Restoring these forests is essential to help avoid the worst impacts of climate change. Yet monitoring tropical forest recovery is challenging. We track the abundance of early-successional species in a forest restoration concession in Indonesia. If the species are carefully chosen, they can be used as an indicator of restoration progress. We present SLIC-UAV, a new pipeline for processing Unoccupied Aerial Vehicle (UAV) imagery using simple linear iterative clustering (SLIC)to map early-successional species in tropical forests. The pipeline comprises: (a) a field verified approach for manually labeling species; (b) automatic segmentation of imagery into “superpixels” and (c) machine learning classification of species based on both spectral and textural features. Creating superpixels massively reduces the dataset's dimensionality and enables the use of textural features, which improve classification accuracy. In addition, this approach is flexible with regards to the spatial distribution of training data. This allowed us to be flexible in the field and collect high-quality training data with the help of local experts. The accuracy ranged from 74.3% for a four-species classification task to 91.7% when focusing only on the key early-succesional species. We then extended these models across 100 hectares of forest, mapping species dominance and forest condition across the entire restoration project.</jats:p