231 research outputs found
KEBERADAAN PANTUN BALI MASA KINI (SEBUAH KONTEKSTUALISASI SENI BERBAHASA)
In terms of form of expression, traditional Balinese literature could be classified into two types: oral literature (kesusastraan gentian) and written literature (kesusastraan sesuratan). Oral lieterature is characterized by verbal arts and could be presented in the form of poem such as pantun, proverbs, riddles, etc. From formal perspective, it generally consists of two lines or four in a stanza.
Historically, the development of Balinese pantun (wewangsalan) has been unfavorable due to the fact that the medium of its expression is Balinese language, which has a marginal historical development as the result of national language policy. In order to preserve the existence of Balinese pantun, contextualization efforts in different activities should be made such as Barong Landung performing art
ANALISIS KETERKAITAN ANTAR KELOMPOK PENGELUARAN INFLASI MENGGUNAKAN VECTOR AUTOREGRESSIVE MODEL
In this study, testing steps were carried out, namely the stationarity test, determining the optimum lag, hypothesis testing and the formation of the VAR model, the Granger causality test and classical assumptions. The data used are month to month inflation data for each inflation expenditure group in Indonesia for the period January 2013 to December 2019. The inflation expenditure group is foodstuffs; processed food, beverages, cigarettes and tobacco; housing, water, electricity, gas and fuel; clothing; health; education, recreation and sports; and transportation, communication, and financial services. However, in this study only five inflation expenditure groups were used, namely foodstuffs; processed food, beverages, cigarettes and tobacco; housing, water, electricity, gas and fuel; clothing; as well as transportation, communication and financial services. The purpose of this study is to analyze the relationship between inflation expenditure groups and to find a forecasting model for inflation expenditure groups in Indonesia. After the Granger causality test was carried out, all probability values between endogenous variables, namely the five groups of inflation expenditures were less than 0,05 or rejected H0. Therefore, it can be concluded that there is a causal relationship between endogenous variables
Peramalan Eksistensi Cokelat dengan Efek Calender Variation dan Seasonal Menggunakan Pendekatan Time Series Klasik
Chocolate is the raw material for making cakes, so consumption of chocolate also increases on Eid al-Fitr. However, this is different in the United States where the tradition of sharing chocolate cake is carried out on Christmas. To monitor the existence of this chocolate can be through the movement of data on Google Trends. This study aims to predict the existence of chocolate from the Google trend where the use of chocolate by the community fluctuates according to the calendar variance and seasonal rhythm. The method used is classic time series, namely nave, double exponential smoothing, multiplicative decomposition, addictive decomposition, holt winter multiplicative, holt winter addictive, time series regression, hybrid time series, ARIMA, and ARIMAX. Based on MAPE in sample, the best time series model to model the existence of chocolate in Indonesia is ARIMAX (1,0,0) while for the United States it is Hybrid Time Series Regression-ARIMA(2,1,[10]). For forecasting the existence of chocolate in Indonesia, the best models in forecasting are ARIMA (([11],[12]),1,1) and Naïve Seasonal. In contrast to the best forecasting model for the existence of chocolate in the United States, namely Hybrid Naïve Seasonal-SARIMA (2,1,0)(0,0,1)12 Hybrid Time Series Regression- ARIMA(2,1,[10]), Time Series Regression, Winter Multiplicative, ARIMAX([3],0,0).
 Untuk sebagian kalangan, cokelat dapat dijadikan sebagai simbol kasih sayang atau sebagai bentuk perhatian lebih bagi orang-orang tertentu, terutama pada saat Valentine atau White Day. “Petani kakao Indonesia kebanjiran permintaan jelang perayaan hari kasih sayang atau valentine setiap tahunnya. Karena cokelat menjadi bahan baku pembuatan kue, maka konsumsi cokelat meningkat juga di hari raya Idul Fitri yang mana masyarakat banyak membuat kue sebagai persiapan perayaan hari raya Idul Fitri. Namun hal ini berbeda yang terjadi di United States yang mana tradisi berbagi kue cokelat dilaksanakan di hari raya Natal. Untuk memantau eksistensi cokelat ini dapat melalui pergerakan data di google trend. Pada zaman digital ini Google Trends digunakan untuk memahami perubahan secara sosial dan prediksi. penelitian ini bertujuan untuk meramalkan eksistensi cokelat dari google trend yang mana penggunaan cokelat oleh masyarakat ini mengalami fluktuasi mengikuti ritme calendar varians dan musiman. Metode yang digunakan adalah time series klasik yaitu naïve, , double exponential smoothing, dekomposisi multiplicative, dekomposisi addictive, holt winter multiplicative, holt winter addictive, time series regression, hybrid time series, ARIMA, dan ARIMAX. Berdasarkan MAPE in sampel model time series terbaik untuk meodelkan eksistensi cokelat di Indonesia adalah ARIMAX (1,0,0) sedangkan untuk United States adalah Hybrid Time Series Regression- ARIMA(2,1,[10]). Untuk peramalan eksistensi cokelat di Indonesia model terbaik dalam peramalan yaitu ARIMA (([11],[12]),1,1) dan Naïve Seasonal. Berbeda pada model peramalan terbaik untuk eksistensi cokelat di United States yaitu Hybrid Naïve Seasonal-SARIMA (2,1,0)(0,0,1)12 Hybrid Time SeriesRegression- ARIMA(2,1,[10]), Time Series Regression , Winter Multiplicative, ARIMAX ([3],0,0)
Peramalan Gelombang Covid 19 Menggunakan Hybrid Nonlinear Regression Logistic – Double Exponential Smoothing di Indonesia dan Prancis
ABSTRAKIndonesia dan Prancis adalah dua Negara yang mengalami Covid 19 dengan pola pergerakan kasus Covid 19 yang berbeda. Kondisi Indonesia masih mengalami siklus one wave namun Prancis sudah masuk pada pola second wave. Makna second wave adalah kondisi epidemi Covid 19 yang baru muncul setelah epidemi sebelumnya dianggap selesai. Dalam peramalan kasus Covid 19 baik itu terkait informasi puncak dari terjadinya kasus Covid 19 serta ramalan terkait akan berakhirnya pandemi kasus Covid 19 suatu negara merupakan hal penting bagi pemerintah suatu Negara. Model hybrid meningkatkan akurasi ramalan dibandingkan model time series yang dilakukan secara terpisah. Tujuan penelitian ini adalah melakukan peramalan kasus Covid 19 di Indonesia dan Prancis dengan menggunakan metode hybrid dan membandingkan dengan peramalan dengan salah satu metode tunggal. Metode yang digunakan adalah metode tunggal yaitu Nonlinear Regression Logistic dan metode Hybrid Nonlinear Regression Logistic–Double Eksponensial Smoothing. Hasilnya adalah model peramalan Hybrid Nonlinear Regression Logistic and Doubel Exponential Smoothing lebih bagus digunakan dalam peramalan kasus Covid 19 di Indonesia dan Prancis. Terlihat bahwa nilai MAPE model Hybrid Nonlinear Regression Logistic–Double Eksponensial Smoothing jauh lebih kecil dibandingkan model peramalan Nonlinear Regression Logistic. ABSTRACTIndonesia and France are two countries that have experienced Covid 19 with different patterns of movement of Covid 19 cases. Indonesia's condition is still experiencing a one wave cycle but France has entered into the second wave pattern. The meaning of the second wave is the condition of the Covid 19 epidemic which only emerged after the previous epidemic was considered over. In forecasting the Covid 19 case, whether it is related to the peak information on the occurrence of the Covid 19 case and predictions regarding the end of the pandemic of the Covid 19 case in a country, it is important for the government of a country. The hybrid model improves forecast accuracy compared to the time series model which is carried out separately. The purpose of this study is to forecast the cases of Covid 19 in Indonesia and France using the hybrid method and comparing with forecasting with one single method. The method used is a single method, namely Nonlinear Logistic Regression and Hybrid Nonlinear Regression Logistic-Double Exponential Smoothing methods. The result is that the Hybrid Nonlinear Regression Logistic and Double Exponential Smoothing forecasting model is better used in forecasting the Covid 19 cases in Indonesia and France. It can be seen that the MAPE value of the Hybrid Nonlinear Regression Logistic – Double Exponential Smoothing model is much smaller than the Nonlinear Regression Logistic forecasting model
Implementing Photovoice in Teaching Speaking to the Tenth Grade Students of SMA (SLUA) Saraswati 1 Denpasar
This classroom action study dealt with implementing photovoice in teaching speaking to the tenth grade students of SMA (SLUA) Saraswati 1 Denpasar. The purpose of study the student could explain about a picture that showed in the slide show orally. The study have been stated as the following: speaking skill at the tenth grade students of SMA (SLUA) Saraswati 1 Denpasar can be improved through photovoice. This study was conducted in X IPA class that consisted of 36 females and 13 males. These subjects were chosen because faced by the fact that the subjects under study still low in speaking English and lack of confident. It was proved that the mean score of pre-test was 59.18. To enhance the improvement of their speaking skill, the researcher tried to apply photovoice technique. The researcher conducted Cycle I and the results of the data analysis of the reflection were 70.81. Then, the researcher continued the research by conducting the cycle II and the result of the data analysis of reflections in cycle II were 81.02. The finding showed that there was improvement of the students’ scores after the implementing of photovoice technique. In addition, the results of the questionnaire showed that option A was 72.47%, option B was 20.70%, option C was 6.81%, and option D was 0%. From the result of the study, it could be concluded that photovoice technique could improve speaking skill of the tenth grade students of SMA (SLUA) Saraswati 1 Denpasar
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