Penerapan Contextual Teaching And Learning (Ctl) dengan Model Pembelajaran Kooperatif Tipe Numbered Heads Together (Nht) untuk Meningkatkan Aktivitas dan Kemampuan Kognitif Siswa

This aim of research are to improve (1) the student learning activities at VIII G of 8 Junior High School at Surakarta academic year 2011/2012 on subject matter Pressure. (2) the student cognitive aspect at VIII G of 8 Junior High School at Surakarta academic year 2011/2012 on subject matter Pressure.This research used a Classroom Action Research with Kurt Lewin and Collaborative model that was held in two cycles. The cycles were started by preparation phase and then were continued execution phase that consist of action planning, action, observation, evaluation, and reflection. The research subject was VIII G of 8 Junior High School Surakarta student at academic year of 2011/2012, which was consist of 30 students in the subject matter Pressure. The techniques of collecting data were observation, interview with teacher, test, questionnaire and documentation. Techniques of data analysis were qualitative and quantitative.Based on result this research, it can be concluded that: (1) The application of CTL (Contextual Teaching and Learning) with model cooperative type NHT (Numbered Heads Together) can improve the student learning activities on subject matter Pressure in VIII G of 8 Junior High School in Surakarta academic year 2011/2012. It can be seen from the implementation of before cycle, cycle I and cycle II. Based on the indicators of activities can be concluded that: (a) student ask to teacher if there are uncleared explanation 6.66% at before cycle, 19.38% at cycle I, and 38.33% at cycle II, (b) student answer the teacher question independently 8.33% at before cycle, 34.51% at cycle I, and 46.66% at cycle II, (c) student give a perception for a friend opinion 1.66% at before cycle, 48.33% at cycle I, and 56.67% at cycle II, (d) student give an idea to solve the problem in group discussion 8.33% at before cycle, 60.00% at cycle I and 80.00 at cycle II, (e) student give the attention on the board or powerpoint slide during presentation of their teacher 72.33% at before cycle, 73.99% at cycle I and 96.66% at cycle II (f) student read physics book, module or student worksheet 35.11% at before cycle, 49.56% at cycle I, and 61.66% at cycle II, (g) student write the result of the problem in the discussion 20% at before cycle, 48.79% at cycle I and 88.33% at cycle II, (h) student write the object matter which has explained by teacher 65.01% at before cycle, 70.63% at cycle I and 90.00% at cycle II. (2) The application of CTL (Contextual Teaching and Learning) with model cooperative type NHT (Numbered Heads Together) can improve cognitive aspect on subject matter Pressure in VIII G of 8 Junior High School in Surakarta academic year 2011/2012. Based on 70 point as standard of minimum completion, the completed learning students were 66,67% at cycle I and 86,67% at cycle II

Profil Prakonsepsi Siswa SMP Kelas VIII Pada Materi Cahaya

Tujuan penelitian ini adalah untuk menjelaskan profil prakonsepsi yang dimiliki siswa kelas VIII SMP Negeri 1 Jenar Sragen pada materi Cahaya.Penelitian ini menggunakan metode deskriptif yang dilakukan pada siswa kelas VIII SMP Negeri 1 Jenar Sragen. Sampel dalam penelitian sejumlah 96 siswa dari 201 siswa. Pemilihan subjek penelitian dengan teknik cluster - random sampling. Teknik pengumpulan data dengan teknik tes, dan teknik wawancara. Tes yang digunakan dalam penelitian adalah tes pilihan ganda dengan alasan tertutup. Teknik analisis data yang digunakan adalah statistik deskriptif.Dari hasil analisis data dan pembahasan dalam penelitian ini maka dapat disimpulkan bahwa profil prakonsepsi yang dimiliki oleh siswa SMP Negeri 1 Jenar Sragen sebagai berikut: siswa yang memiliki rata-rata prosentase prakonsepsi benar tertinggi sebanyak 59.72 % yaitu pada konsep cahaya dan penglihatan. Siswa yang memiliki rata-rata prosentase prakonsepsi bersifat miskonsepsi tertinggi sebanyak 52.09 % yaitu pada konsep warna dan cahaya. Siswa yang memiliki rata-rata prosentase prakonsepsi salah tertinggi sebanyak 40.62 % yaitu pada konsep bayang-bayang dan bayangan. Profil prakonsepsi siswa bersifat miskonsepsi yang lebih dari 55 % adalah sebagai berikut :1) benda berwarna merah terlihat karena cahaya putih yang mengenai benda terserap selain warna merah, sedangkan warna merah tertinggal di benda (81.25 %); 2) semakin terang sumber cahaya, maka kecepatan cahayanya akan semakin cepat (62.5 %); 3) semakin jauh jarak benda terhadap cermin datar maka tinggi bayangannya akan semakin mengecil (62.5 %) ; 4) semua cahaya yang mengenai cermin akan dipantulkan tidak ada yang diserap (61.46 %); 5) cahaya yang berasal dari sebuah sumber pada siang hari akan tetap tinggal pada sumber atau tidak merambat (59.38 %) ; 6) langit mendung tidak terbentuk bayangan karena cahaya terserap semua oleh awan (57.29 %)

Applying machine learning to understand the properties of biomass carbon materials in supercapacitors

Carbon is a fundamental material in developing electrochemical double-layer capacitors (EDLCs), also known as supercapacitors. Many studies have proven the impact of various carbon material properties, such as surface area, pore volume, and chemical surface composition, on the specific capacitance of supercapacitors (EDLCs). However, research endeavors to comprehensively evaluate the contribution of these material properties in correlation with experimental parameters, such as electrolyte concentration, voltage window, and current density, are scarce. This study aimed to employ machine learning algorithms to comprehend the interdependence between the properties of biomass-based carbon and the aforementioned experimental parameters with the capacitance of EDLCs. Four models of the machine learning algorithms were utilized in this study, including linear regression (LR), M5-Rules, Random Tree (RT), and Multi-Layer Perceptron (MLP), to determine the most suitable algorithm for analyzing and predicting the capacitance of EDLCs. The results revealed that the MLP model exhibited the highest determination correlation coefficient (R) of 0.871 with a Mean Absolute Error (MAE) of 45.069 F/g. Besides, the study utilized a machine learning correlation attribute model and observed that the supercapacitor’s surface area and pore volume demonstrated significant correlations with the same correlation ratio of 0.4. In conclusion, these findings emphasize the importance of considering surface area and pore volume in developing and optimizing supercapacitors. Finally, this study adds knowledge in supercapacitors and provides valuable insights for designing and developing high-performance energy storage devices