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<![CDATA[DETERMINAN PERILAKU REMAJA MEROKOK SETIAP HARI DI INDONESIA ]]>
<![CDATA[Charvia Ismi Zahrani]]>;
<![CDATA[I Made Arcana]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.412
<![CDATA[Prevalensi remaja yang merokok terus mengalami kenaikan pada beberapa tahun terakhir. Lebih dari separuh remaja yang merokok merupakan perokok setiap hari. Kebiasaan merokok yang dimulai sejak remaja akan meningkatkan ketergantungan pada masa tua. Hal ini sangat mengkhawatirkan mengingat dampak negatif dari merokok dapat menyebabkan berbagai macam penyakit hingga kematian. Risiko ini akan meningkat apabila perilaku merokok dilakukan setiap hari. Penelitian ini bertujuan untuk mengetahui karakteristik sosial demografi yang memengaruhi perilaku remaja merokok setiap hari di Indonesia beserta kecenderungannya. Analisis deskriptif dan analisis regresi logistik biner dilakukan pada data remaja berusia 15-24 tahun yang merokok yang bersumber dari data Riskesdas 2018. Hasil penelitian menunjukkan bahwa jenis kelamin, status wilayah tempat tinggal, status perkawinan, tingkat pendidikan, status bekerja, dan usia pertama merokok memiliki pengaruh signifikan terhadap perilaku merokok setiap hari. Kecenderungan terbesar untuk berperilaku merokok setiap hari ditunjukkan oleh remaja laki-laki, remaja berstatus bekerja, dan remaja yang merokok pertama kali pada usia di bawah 18 tahun.]]>
<![CDATA[PENGGUNAAN GENERALIZED LINEAR AUTOREGRESSIVE MOVING AVERAGE (GLARMA) DALAM ANALISIS FENOMENA RESESI DI INDONESIA TAHUN 2008Q1 – 2020Q1 ]]>
<![CDATA[Dimas Maladzi Wibawa]]>;
<![CDATA[Nucke Widowati Kusumo Projo]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.413
<![CDATA[Resesi merupakan penurunan secara signifikan dalam kegiatan ekonomi yang tersebar di seluruh aspek ekonomi. Resesi yang berkepanjangan dapat membawa perekonomian ke arah depresi. Indonesia termasuk ke dalam kategori fragile country yang menyebabkan kerentanan untuk masuk ke masa resesi semakin besar. Resesi merupakan bagian dari siklus bisnis yang mungkin akan dialami pada suatu waktu. Penelitian ini menggunakan model Generalized Linear Autoregressive Moving Average (GLARMA) untuk mengakomodir prediksi peluang dari fase resesi yang di definisikan dengan metode Bry Boschan dan meramal variabel independen dengan Autoregressive Integrated Moving Average (ARIMA). Variabel yang digunakan yaitu laju inflasi, fed fund rate, transaksi berjalan, harga minyak dunia, dan selisih U.S. 10Year-Bond dengan 3-Month LIBOR. Dari hasil penandaan siklus bisnis pada Produk Domestik Bruto riil, Indonesia mengalami delapan kali resesi sejak tahun 1993Q1-2020Q1 dengan durasi terpendek selama dua triwulan dan terpanjang selama delapan triwulan. Hasil dari model GLARMA(1,0) menunjukkan bahwa resesi di Indonesia didominasi oleh faktor eksternal yang dalam penelitian ini adalah selisih U.S. 10Year-Bond dengan 3-Month LIBOR dan fed fund rate memiliki pengaruh negatif secara signifikan terhadap resesi. Autoregressive lag-1 memiliki pengaruh positif terhadap resesi atau dengan kata lain kondisi yang terjadi pada triwulan sebelumnya berpengaruh terhadap terjadinya resesi di triwulan selanjutnya. Resesi di Indonesia diprediksi terjadi pada 2020Q3.]]>
<![CDATA[KAJIAN UNDERGROUND ECONOMY DAN KAITANNYA DENGAN PENERIMAAN PAJAK DI INDONESIA ]]>
<![CDATA[Fakhri Hafidzul Azhar]]>;
<![CDATA[Gama Putra Danu Sohibien]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.415
<![CDATA[Underground economy is income generated from economic activities, both legal and illegal, which are not included in the calculation of Gross Domestic Product (GDP). Underground economy activities that are allowed to continue to develop will result in loss of tax revenue. To overcome this, a tax amnesty policy was implemented, with the aim of minimizing the lost tax revenue, but it is not yet known whether this goal can be achieved or not. This study aims to provide an overview of the variables used, measure the size of the underground economy and the lost tax revenue due to the underground economy, and compare the average lost tax revenue before and after the tax amnesty. The measurement of underground economy and lost tax revenue is carried out through a monetary approach using the Error Correction Model method and the comparison of the average lost tax revenue using the average difference test. The results showed that there was an increasing trend in the variable money supply, ADHK GDP, BI interest rates and exchange rates and a downward trend in the variable ratio / tax burden, inflation and world oil prices. The size of the underground economy in Indonesia from 2005 to 2018 on average reached 34.157 trillion rupiah or 1.84% of GDP. The average lost tax revenue reached IDR 4 trillion or 0.22% of GDP. The tax amnesty that has been implemented in Indonesia since 2015-2018 has not been able to achieve the desired goals.underground economy, tax amnesty, error correction model (ECM), uji beda rata-rata dua populasi]]>
<![CDATA[PENERAPAN REGRESI DATA PANEL PENGARUH KESETARAAN GENDER TERHADAP PERTUMBUHAN EKONOMI DI PROVINSI RIAU PERIODE 2011-2015 ]]>
<![CDATA[Sutri Vininda]]>;
<![CDATA[Lia Yuliana]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.416
<![CDATA[Economic growth is which one indicator to evaluate the economic performance of a region. During the 2011-2015 period, economic growth in Indonesia decline, where Sumatra Island had the lowest economic growth, especially in Riau Province. Economic growth is obtained from production factors owned by a region. The existence of gender differences can lead to differences in productivity between workers, so in assessing economic growth it is necessary to include gender equality in the economy. This study aims to describe in general economic growth and gender equality and to determine the impact of gender equality on economic growth in Riau Province during the 2011-2015 period using descriptive analysis and panel data regression. The results showed that conditions of gender equality in the field of technology and labor force had increased while conditions for gender equality in the field of education had decreased. The panel data regression results show that the ratio of accessing the internet, the ratio of working hours, and the ratio of wages have a significant positive effect on economic growth, while the MYS ratio has not significant positive effect on economic growth.]]>
<![CDATA[KETIMPANGAN KETIMPANGAN AKSES TERHADAP TEKNOLOGI INFORMASI DENGAN PENDEKATAN HUMAN OPPORTUNITY INDEX (HOI) ]]>
<![CDATA[Riyadi Riyadi]]>;
<![CDATA[Putri Larasaty]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.419
<![CDATA[Inequality is one of the crucial problems in society that may not be fully resolved. This paper analyzes the inequality of opportunity in accessing to technology and information in Indonesia. This study uses data from SUSENAS Kor 2019 form Statistics Indonesia-BPS. The analysis uses a method the Human Opportunity Index (HOI) by the World Bank. The HOI measures the contribution of individuals’ socio-economic and demographic circumstances to inequality of opportunity in accessing to technology and information services. The logit model is also used to determine the socio-economic and demographic factors of accessing to technology and information. The results of empirical analysis show that there are still wide opportunities for access to technology and information services in Eastern Indonesia and Western Indonesia. In addition, the conditions of expenditure per capita and residential areas are the most dominant factors towards the inequality of opportunity in accessing to technology and information. This suggests that household poverty dan residential areas have a crucial role in determining equitable access to technology and information.]]>
<![CDATA[DETERMINAN STATUS PENYALAHGUNAAN NARKOBA PADA REMAJA USIA 15-24 TAHUN DI INDONESIA TAHUN 2017 ]]>
<![CDATA[Sahara Sabilah Putri]]>;
<![CDATA[Budyanra Budyanra]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.421
<![CDATA[Illicit drug has become a global problem that obtain serious concern (BNN,2019). In Indonesia, drug abuser keeps increasing and among them are students both in school and college. In 2017, 24 out of 100 drug abusers in Indonesia are students. Based on 2018 BNN data, the percentage of students who abuse drugs in 13 provincial capitals of Indonesia is 3.2 percent or equivalent to 2.29 million adolescents. UNODC (2018) declared that adolescents are the most vulnerable group to falling into drug abuse problem. That occurs since adolescents are in their period of searching for identity and have a very high curiosity. In the process of finding their identity, adolescents often involved into negative things including drug abuse. This study was conducted to determine the factors that affect the status of drug abuse among adolescents 15-24 years in Indonesia using the 2017 IDHS data. The analytical method used is binary logistic regression. The results showed that the variables of gender, age, level of education, residence, smoking status, and alcohol consumption status had a significant influence on the status of drug abuse among adolescents in Indonesia.]]>
<![CDATA[PENGARUH COVID-19 TERHADAP HARGA SAHAM DI INDONESIA TAHUN 2019-2020 ]]>
<![CDATA[Shaula Andreinna Arthamevia]]>;
<![CDATA[Maulidya Ayu]]>;
<![CDATA[Umniyyatul Ula]]>;
<![CDATA[Silva Rizqi]]>;
<![CDATA[Farhatun Nissa]]>;
<![CDATA[Hendro Cahyo]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.427
<![CDATA[Stock is a capital market instrument that can be defined as a sign of individual or unilateral capital participation (business entity) in a company or limited liability company. The current factor in the stock market sector is the impact of the corona virus on the stock price index and the flow of foreign funds to the stock market. So it is very necessary to conduct an analysis of the impact of the corona pandemic virus on the stock market sector to see how the JCI movement in Indonesia compares before the pandemic and during the Covid-19 pandemic. The method used for comparative analysis is the Simple Moving Average and the Weighted Moving Average. From the results of descriptive analysis on the JCI data in Indonesia, the average Adj Close variable before the pandemic occurred was 6353.71, with a minimum value of 5907.12 and a maximum value of 6525.36. The average value during the pandemic was 5143,929, with a minimum value of 3937,632 and a maximum value of 6325,406. The comparison results show that the Weighted Moving Average method is used because with the 2019 IHSG MAPE value of 0.844287 the 2020 IHSG MAPE value is 3.489167 which is smaller than the Simple Moving Average method. As well as the results of the comparison of the impact of the JCI from before the pandemic occurred with data where the pandemic was occurring was very influential and the JCI decreased when it was declared that Indonesia was infected with Covid-19.]]>
<![CDATA[FAKTOR YANG BERPENGARUH TERHADAP KEPATUHAN MASYARAKAT PADA PROTOKOL KESEHATAN DALAM MENCEGAH PENYEBARAN COVID-19 ]]>
<![CDATA[Riyadi Riyadi]]>;
<![CDATA[Putri Larasaty]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.431
<![CDATA[The Covid-19 pandemic is one of the events threatening all around the world particularly in health sector. The widespread of this virus causes the most crucial issue to stop it immediately. Various kinds of policies have been made by the government to end the spread. However, on the other hand, the community is critically required to comply with health protocols as a serious effort to stop it. This study aims to analyze the level of community compliance in implementing health protocols in their daily lives, as well as to determine the socio-demographic factors that affect compliance with health protocols in society in Indonesia. The data used in this study is derived from the 2020 Social Demographic Impact of Covid-19 Survey from BPS. This analysis uses descriptive and regression analysis. The empirical results show that the average adherence index of male respondents is lower than that of female respondents, and there is a tendency that young people are more disobeying about health protocols with a relatively lower average adherence score compared to the older people. In addition, the socio-demographic characteristics that affect the level of community compliance with health protocols are respondent reaction status, perceptions of the effectiveness of independent isolation, level of concern about Covid-19 news, level of concern about traveling outside the home, gender, education level, marital status, health status, and age.]]>
<![CDATA[PERBANDINGAN METODE SARIMA DAN METODE TRANSFER PADA PRODUKSI PADI DI KABUPATEN KENDAL ]]>
<![CDATA[Safa'at Yulianto]]>;
<![CDATA[Ahmad Jauharudin Najib]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.433
<![CDATA[Indonesia is an agrarian country, meaning that agriculture holds an important role for the national economy. Based on data from the Central Statistics Agency in 2017 which states agriculture is one of the sectors that most contribute to the national economy with a contribution of 13.14 percent. In this agricultural sector, rice is the largest producer of production compared to other commodities with a production of 79 million tons in 2016. As a country with a large population, Indonesia faces challenges in meeting the needs of rice, but shifting the function of agricultural land to non-agriculture is very influential on yield rice production, the less land area, the less rice production is produced. No exception in Kendal Regency which has an agrarian area with the main commodity, rice, rice production in this Regency tends to decrease in 2016 and 2017. To assist the government in setting policies in food availability, forecasting analysis is used. The method most often used in forecasting is the ARIMA method. This method is actually quite good, but because rice production is also influenced by the area of harvested land, a transfer function method is proposed that can include the harvested area variable in the forecasting model. The data used in this study are data on rice production and harvested area in Kendal Regency from January 2013 to December 2017. The test results using the transfer function forecasting method produce the best model]]>
<![CDATA[PENGUMPULAN DATA PRODUKTIVITAS TANAMAN PANGAN PADA MASA PANDEMI COVID-19 ]]>
<![CDATA[Nialita Rahmadhani]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2020i1.440
<![CDATA[The Covid-19 has had an impact not only on the world of health, but also other sectors including the food and agriculture sectors. Food and Agriculture Organization (FAO) regarding the potential of world food scarcity, president Joko Widodo instructed to ensure the availibility of food accurately based on valid data. This is a challenge for BPS to make methodological adjustments so that it can still provide food data, which is crop cutting survey. The purpose of this study is to explain the mitigation and adaptation of the methodology of crop cutting survey, and to provide an evaluation of the impact of these changes. Data used were the subround 1 2019 and Subround 1 2020 of crop cutting survvey collected by BPS and then analyzed using the descriptive method and further analyzed using paired samples t-test analysis. The results showed that the data entry (response rate) for paddy commodities in subround 1 2020 only reached 65,10%, as many as 70,49% of officers still used the measurement and interview method and ther was no difference inthe results of crop cutting survey before the covid-19 pandemic (Subround 1 2019) with the time covid-19 pandemic (subround 1 2020). So it can be concluded that the interview method without measurement can be an alternative because there is no significant difference between the paddy productivity of the measurement method and interviews with the interview without measurement.]]>
