Fisika merupakan salah satu cabang IPA yang mendasari perkembangan teknologi, sehingga proses pembelajaran Fisika seyogyanya tidak hanya menekankan pada penguasaan konsep tetapi juga pada aspek penemuan. Oleh karena itu, kegiatan eksperimen dipandang sangat penting dalam pembelajaran Fisika. Salah satu eksperimen yang umum dilakukan ialah eksperimen Gerak Lurus Beraturan (GLB) dan Gerak Lurus Berubah Beraturan (GLBB) dengan menggunakan alat Pesawat Atwood. Hasil observasi menunjukkan bahwa pengukuran parameter gerak pada pesawat atwood dilakukan secara manual, yaitu menggunakan mistar dan stopwatch untuk menentukan kecepatan dan percepatan gerak benda, sehingga data yang diperoleh bersifat subjektif dan kurang menunjukkan karakteristik GLB dan GLBB. Salah satu solusi ialah menggunakan aplikasi Tracker. Pada eksperimen ini gerakan benda direkam menggunakan kamera High definition-HD dengan kecepatan mengambil gambar 24 frame per second. Hasil pengolahan Tracker untuk GLB memberikan grafik posisi fungsi waktu (y=f(t)) berbentuk garis lurus miring kanan dan grafik kecepatan fungsi waktu (v=f(t)) berbentuk garis lurus mendatar. Sedangkan untuk GLBB, pengolahan tracker memberikan grafik posisi fungsi waktu (y=f(t)) berbentuk kuadratik dan grafik kecepatan fungsi waktu (v=f(t)) berbentuk garis lurus miring kanan. Berdasarkan hasil analisis, dapat disimpulkan bahwa pemanfaatan aplikasi tracker pada pesawat atwood mampu menunjukkan karakteristik gerak GLB dan GLBB sehingga layak digunakan dalam pembelajaran fisika di sekolah.
The industrial revolution 4.0 encourages people to be able to maximize technology and information. Not least in the world of education, teachers are competing to innovate in terms of utilizing technology as a learning support. Learning will be fun when it is supported by interesting learning media. According to the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia by utilizing a variety of media on technology and information devices, teachers can present information / teaching materials in a more varied and interesting form (not just text) so that students understand lessons more easily. This can be used by teachers to increase students' interest in learning about Pancasila and Citizenship Education (PKn) lessons. Pkn learning will be interesting if the teacher can make updates in the implementation of learning. Infographic learning media can be a solution to attract students' interest in learning, with increased interest in learning expected to be in line with increased visual intelligence and learning outcomes. The novelty in this study is the existence of a mediator variable of spatial visual intelligence. The purpose of this study is to use infographic learning media in Pkn learning. The design of this research is Quasy Experimental with Nonequivalent Control Group Design . Sampling was carried out using cluster random sampling . The results can be concluded that the indirect effect of interest in learning on learning outcomes through visual-spatial intelligence = 0.203 <0.029 . This means that visual-spatial intelligence is not effectively mediates interest in learning towards learning outcomes Keywords: Interest in learning, Visual Spatial Intelligence, Learning Outcomes
Oil and gas industry are an industry with a high cost and high risk, artificial intelligence will help the work of humans to minimize the risk of accidents, reduce processing time and improve corporate profits. So, the work becomes more efficient. The aims of the study give information that the artificial intelligence help the work to evaluate the initial gas in place on reservoir and comparison the results between software and manual Material Balance (MBAL). Additional research is needed to know the type of reservoir and drive mechanism. The method used is the research on reservoir RGN, the data used are based on real data in field. This research uses artificial intelligence MBAL software and calculation with manual MBAL. Based on the analysis, the result of reservoir type dry gas reservoir with drive mechanism is depletion drive. Calculation initial gas in place using artificial intelligence MBAL software, get the initial gas in place result of 50661,3MMscf. And calculation using manual MBAL, get the initial gas in place result of 50063,59MMscf. There is a difference in the results of the initial gas content in place of 597.4 MMscf. Based on the analysis, there are differences in the results between using artificial intelligence and manual MBAL.
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