PENERAPAN PENDEKATAN CONTEXTUAL TEACHING LEARNING (CTL) UNTUK MENINGKATKAN KETERAMPILAN MENULIS KARANGAN DESKRIPSI DI SD

Penelitian ini dilatarbelakangi oleh rendahnya kemampuan menulis siswa kelas IVB Sekolah Dasar pada mata pelajaran bahasa Indonesia. Hal ini terlihat berdasarkan pada observasi awal ketika pembelajarannya masih bersifat konvensional (siswa kurang diberikan stimulus untuk menulis), sehingga siswa-siswa kesulitan untuk mengungkapkan ide gagasannya dalam bentuk tulisan berupa karangan deskripsi. Kesulitan yang dihadapi siswa yaitu sulit menentukan judul, sulit membuat sebuah kalimat, sulit merangkai kalimat menjadi sebuah karangan sehingga karangan yang dibuat menjadi rancu dan tidak sesuai. Selain itu, kesalahan yang paling banyak ditemukan yaitu kesalahan dalam penggunaan ejaan dan tanda baca. Hal tersebut mengakibatkan banyaknya siswa yang mendapat nilai dibawah KKM yaitu sebanyak 16%. Salah satu upaya yang dilakukan yaitu dengan meningkatkan keterampilan menulis karangan deskripsi siswa dengan menerapkan pendekatan Contextual Teaching Learning (CTL). Tujuan yang hendak dicapai dalam penelitian ini adalah: (1) Untuk mengetahui pelaksanaan pembelajaran menulis karangan deskripsi dengan menggunakan pendekatan Contextual Teaching Learning (CTL), (2) Untuk mengetahui seberapa besar peningkatan keterampilan menulis karangan deskripsi siswa setelah menerapkan pendekatan Contextual Teaching Learning (CTL). Penelitian ini merupakan penelitian tindakan kelas yang diadaptasi dari model Kemmis dan Mc. Taggart. Penelitian ini dilakukan pada kelas 4 yang berjumlah 25 siswa. Instrumen pengungkap data yang digunakan dalam penelitian ini yaitu observasi, catatan lapangan, wawancara diakhir penelitian, dan dokumentasi. Hasil penelitian ini menunjukkan peningkatan ketuntasan keterampilan menulis karangan deskripsi, yaitu ketuntasan pada siklus I hanya 40% dan meningkat pada siklus II sebesar 92%. Selain itu, peningkatan terlihat dari nilai rata-rata, yaitu pada siklus I nilai rata-rata sebesar 59,4 dan meningkat pada siklus II menjadi 79,2 Hasil tersebut menunjukkan bahwa pendekatan Contextual Teaching Learning (CTL) mampu meningkatkan keterampilan menulis karangan deskripsi

Global gold prices forecasting using Bayesian nonparametric quantile generalized additive model

Gold is one of the most attractive commodities and popular investments. Investment experts often recommend investing in gold because gold is one of the safest investments. It is a stable classic hedge, although the conditions of currency volatility or global markets are depreciated. However, the gold price fluctuations can be influenced by some other factors, such as the USD Index, which reflect and measure the strength of the US Dollar currency, and the Index of Dow Jones Industrial Average (DJIA) or a reflection of the political and economic conditions of the stock market. In this study, we conduct a global gold price forecast (USD) based on the USD Index, the DJIA Index, and the influence of time trends. Based on the data's characteristics, we face the fact that the data is nonlinear, contains outliers, and its pattern is not easy to specify parametrically. Due to the complexity of the model, we then propose a more flexible, robust modeling technique called the Bayesian Nonparametric Quantile Generalized Additive Model method. According to the results for the median case, the proposed method shows an accurate forecasting category due to the value of the Mean Absolute Percentage Error, MAPE less than 10 percent

Penerapan Program GSTAT-R untuk Prediksi Kadar Abu Batubara di Lokasi Tidak Tersampel dengan Metode Universal Kriging

Geostatistika merupakan perpaduan ilmu pertambangan, geologi, matematika, dan statistika. Data yang digunakan dalam geostatistika merupakan data spasial yakni nilai pengamatan berdasarkan lokasi. Kriging merupakan metode penaksiran yang menggunakan data spasial yang bertujuan untuk menaksir nilai di suatu lokasi, berupa titik atau blok berdasarkan informasi nilai-nilai dari lokasi lain di sekitar lokasi yang akan ditaksir. Dalam paper ini akan dibahas mengenai metode universal kriging, karena data yang diprediksi merupakan data yang tidak stasioner.Universal kriging adalah metode interpolasi data yang mempunyai kecenderungan trend (drift) tertentu atau metode penaksiran yang digunakan untuk menangani masalah kenonstasioneran dari data sampel. Dengan menggunakan program GSTAT-R perhitungan hasil prediksi di lokasi tidak tersampel pada metode universal kriging ini didapat dengan persamaan trend (drift) berorde satu. Prediksi kadar abu batubara dilokasi tidak tersampel pada program GSTAT-R dengan menggunakan metode universal kriging menghasilkan hasil prediksi yang akurat

Prediction of Spread Shear Strength of Rock with Ordinary Point Kriging Method using GStat-R

In this study, we used the Ordinary Point Kriging for predicting the spread of shear strength of rock at a site in an unobserved location. Based on the nature of rocks, the rock quality index is measured by rock shear strength with less strong rock properties which has a weaker of the strength of rocks to support the load and become a weak field. The calculation of the spread of the shear strength of rock can be made using GStat-R program in R software to get accurate results. In the calculation of prediction using the kriging method, we can use gstat library, sp library, Rcmdr library and several algorithms in GStat-R and apply them to the data to get a prediction of shear strength index of deployment at an unobserved location

Penaksiran Model Autoregressive (AR) Pada Data Curah Hujan Di Jawa Barat Menggunakan Program R

Model Autoregressive (AR) adalah suatu model deret waktu univariat yang menggambarkan pengamatan suatu variabel yang dipengaruhi variabel itu sendiri pada periode sebelumnya untuk data stasioner. Model AR termasuk ke dalam model linier sehingga salah satu metode penaksiran parameter model yang dapat digunakan adalah Ordinary Least Square (OLS). Dalam penelitian ini dilakukanprediksi pada data curah hujan di wilayah Jawa Barat. Curah hujan merupakan ketinggian air hujan yang terkumpul di tempat yang datar, tidak menguap, tidak meresap, dan tidak mengalir. Data curah hujanmerupakan data yang berpola musiman sehingga membentuk model deret waktu. Untuk mempermudah perhitungan, denganmenggunakan program R diperoleh hasil peramalan curah hujan di wilayah Jawa Barat digunakan Model AR(1). Model AR(1) adalah model yang menyatakan bahwa pengamatan pada satu waktu sekarang dipengaruhi oleh satu waktu pada pengamatan sebelumnya.Hlm.44-5

Implementation of Generalized Space Time Autoregressive (GSTAR)-Kriging Model for Predicting Rainfall Data at Unobserved Locations in West Java

A Generalized Space Time Autoregressive or GSTAR is a special model of Vector Autoregressive (VAR) model which is a combination of time series and spatial models which has the assumption of autoregressive parameter and space time parameter having different value for each location of observation. In addition, it assumes stationary time series data at the mean and variance levels and applies to locations with heterogeneous characteristics. One disadvantage of the GSTAR model is that it can not be used to predict at unobserved locations. In this paper we combine the GSTAR model with the Ordinary Kriging (OK) technique, named GSTAR-Kriging model so that the GSTAR model can be used to predict in unobserved locations. GSTAR parameters are estimated using the Ordinary Least Squares (OLS) method and these are used as inputs for the Kriging technique. Furthermore, by using linear semivariogram we can obtain simulations to predict the GSTAR parameters. For the case study we applied the model to annual rainfall data in wet season (Desember, January and February) from several locations in West Java, Indonesia, such as Majalengka, Kuningan and Ciamis Regencies. The GSTAR (1;1) model in observed location have Mean Average Percentage Error (MAPE) value overall less than 15 percent and residual of model have identically independent distributed normal. The results of GSTAR-Kriging model show that the GSTAR-Kriging parameter at unobserved locations are almost similar to GSTAR parameter at observed locations

Optimizing the Synthesis of Lignin Derivatives from Acacia mangium to Improve the Enzymatic Hydrolysis of Kraft Pulp Sorghum Bagasse

The present study is aimed at optimizing the synthesis of Amphipilic lignin derivatives (A-LD) from the isolated lignin of A.mangium black liquor (BL), using the one and two step acid isolation method, and commercial lignin (LS) was used as comparison. The experimental design was conducted using Taguchi method, which consisted of four parameters and two level factors, with reference to the matrix orthogonal array, L8, including temperature, reaction time, amount of polyethylene glycol diglycidylethers (PEGDE) and Kraft lignin (KL). Furthermore, the kraft pulp of sweet sorghum bagasse (SSB) was used as substrate in the enzymatic hydrolysis (NREL method), with addition of A-LD, whose functional group and surface tension were then characterised using ATR-FTIR and surface tension equipment. Conversely, an improvement in the reducing sugar yield (RSY) compared to the control was observed after adding various A-LDs to the substrate during enzymatic hydrolysis. This product was more prospective for L2S than others products under milder circumstances, due to the fact that it possesses the lowest surface tension. Also, Taguchi analysis demonstrated the treatment at 60 °C for 1 h with 3.0 g and 1.0 g of PEDGE and lignin, respectively as the optimum condition, while the amount of lignin present was included as a factor with the propensity to significantly affect A-LD L1S and LS. Therefore, it was established that the A-LDs from A. mangium kraft lignin require milder synthesis conditions, compared to other existing methods and despite the differences in optimum experimental condition for L2S and LS, the functional groups in the IR spectra possessed very identical characteristics

Proceedings of the 3rd International Conference on Community Engagement and Education for Sustainable Development

This proceeding contains articles on the various ideas of the academic community presented at The 3rd International Conference on Community Engagement and Education for Sustainable Development (ICCEESD 2022) organized by the Universitas Gadjah Mada, Indonesia on 7th-8th December 2022.  ICCEESD is a biannual forum for sharing, benchmarking, and discussing HEI’s activities in developing Education for Sustainable Development towards community engagement. Education for Sustainability as a teaching strategy for resolving community challenges through formal, informal, or non-formal education is expected to benefit from various community service best practices by academics, researchers, and students. The 3rd ICCEESD has “Strengthening Education for Sustainability Towards Better Community Engagement” as its theme this year. It is expected that the 3rd ICCEESD will provide a forum for the presenters and participants to exchange best practices, policies, and conceptual implementation of Education for Sustainability towards better community engagement and explore ideas to address community needs.  Conference Title: 3rd International Conference on Community Engagement and Education for Sustainable DevelopmentConference Theme: Strengthening Education for Sustainability Towards Better Community EngagementConference Acronyms: ICCEESD 2022Conference Date: 7th-8th December 2022Conference Location: Grand Rohan Jogja Yogyakarta, IndonesiaConference Organizer: Universitas Gadjah Mada, Indonesi