Regional development does not only rely on the contribution of the economic sector in the region to the economy, but also the interaction of a sector with other sectors as well as inter-regional. The demand for goods and services outside the region has led to efforts to increase production so it encourage economic growth. In other words, economic development in one region is expected to trigger economic development in other regions. The purpose of this study is to determine the leading business sectors, the interrelationships between the business sectors, and the economic linkages of Central Kalimantan with other regions in Indonesia. Using the Input-Output Table (I-O) of Central Kalimantan in 2016, this study succeeded in identifying the leading business sectors in Central Kalimantan and the interrelationships between business sectors in Central Kalimantan. In addition, this study also uses the Inter-Regional Input-Output Table (IRIO) to determine economic linkages between Central Kalimantan and several provinces in Indonesia. The results showed that Iron Ore Mining is a leading sector and one of the leading business sectors in Central Kalimantan. In addition, in terms of regional linkages, it was found that changes in final demand in Central Kalimantan will have a major impact on output in DKI Jakarta, East Kalimantan, and South Kalimantan.
{"title":"Analisis Keterkaitan Antar Sektor dan Antar Provinsi dalam Perekonomian Kalimantan Tengah Tahun 2016 (Analisis IO dan IRIO)","authors":"S. Suryani","doi":"10.11594/jesi.03.01.01","DOIUrl":"https://doi.org/10.11594/jesi.03.01.01","url":null,"abstract":"Regional development does not only rely on the contribution of the economic sector in the region to the economy, but also the interaction of a sector with other sectors as well as inter-regional. The demand for goods and services outside the region has led to efforts to increase production so it encourage economic growth. In other words, economic development in one region is expected to trigger economic development in other regions. The purpose of this study is to determine the leading business sectors, the interrelationships between the business sectors, and the economic linkages of Central Kalimantan with other regions in Indonesia. Using the Input-Output Table (I-O) of Central Kalimantan in 2016, this study succeeded in identifying the leading business sectors in Central Kalimantan and the interrelationships between business sectors in Central Kalimantan. In addition, this study also uses the Inter-Regional Input-Output Table (IRIO) to determine economic linkages between Central Kalimantan and several provinces in Indonesia. The results showed that Iron Ore Mining is a leading sector and one of the leading business sectors in Central Kalimantan. In addition, in terms of regional linkages, it was found that changes in final demand in Central Kalimantan will have a major impact on output in DKI Jakarta, East Kalimantan, and South Kalimantan.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126242843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Desak Ari Gita Wahyuni, Masruri Muchtar, P. Sihombing
This study aims to analyze the components of the Human Development Index on Gross Regional Domestic Product (GRDP) in Bali during the 2014-2019 period. The data used are time series and cross section obtained and processed from the Central Bureau of Statistics. Through a quantitative descriptive approach, this study uses multiple linear regression methods on panel data with the selected estimation model being the Fixed Effect Model. The results showed that the dependent variable of GRDP could be explained by independent variables by 92.03 percent and 7.97 percent of it was influenced by other variables outside this research model. Mean Years School and Life Expectancy variable have a positive effect on GRDP while the Labor Force Participation Rate variable has a negative and insignificant effect on GRDP. Government policies are needed to support equitable distribution of human development in each region
{"title":"Determinan Produk Domestik Bruto di Provinsi Bali Tahun 2014-2019","authors":"Desak Ari Gita Wahyuni, Masruri Muchtar, P. Sihombing","doi":"10.11594/jesi.03.01.02","DOIUrl":"https://doi.org/10.11594/jesi.03.01.02","url":null,"abstract":"This study aims to analyze the components of the Human Development Index on Gross Regional Domestic Product (GRDP) in Bali during the 2014-2019 period. The data used are time series and cross section obtained and processed from the Central Bureau of Statistics. Through a quantitative descriptive approach, this study uses multiple linear regression methods on panel data with the selected estimation model being the Fixed Effect Model. The results showed that the dependent variable of GRDP could be explained by independent variables by 92.03 percent and 7.97 percent of it was influenced by other variables outside this research model. Mean Years School and Life Expectancy variable have a positive effect on GRDP while the Labor Force Participation Rate variable has a negative and insignificant effect on GRDP. Government policies are needed to support equitable distribution of human development in each region","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":" 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120828411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Penelitian ini bertujuan untuk mengetahui pengaruh pengaruh Altman Z-Score terhadap harga saham, pengaruh rasio-rasio pada Altman Z-score terhadap harga saham sebelum dan saat pandemi covid-19, dan mengetahui perbedaan rasio-rasio pada Altman Z- score sebelum dan saat pandemic covid-19 pada perusahaan manufaktur yang terdaftar dalam Bursa Efek Indonesia (BEI) periode 2019-2020. Jenis penelitian ini menggunakan pendekatan kuantitatif dengan metode Purposive Sampling. Terdapat 14 Sampel Perusahaan yang sesuai dengan kriteria yang ditentukan. Hasil penelitian ini menunjukkan bahwa pada regresi linier sederhana nilai Altman Z-score tidak berpengaruh terhadap harga saham sebelum pandemi covid-19 dan saat pandemi covid -19.
{"title":"Pengaruh Analisis Kebangkrutan Model Altman Z-score Terhadap Harga Saham Pada Perusahaan Manufaktur di Bursa Efek Indonesia Sebelum dan Saat Pandemi Covid -19","authors":"A. Suryana, Ayu Dila Anggraeny","doi":"10.11594/jesi.02.03.09","DOIUrl":"https://doi.org/10.11594/jesi.02.03.09","url":null,"abstract":"Penelitian ini bertujuan untuk mengetahui pengaruh pengaruh Altman Z-Score terhadap harga saham, pengaruh rasio-rasio pada Altman Z-score terhadap harga saham sebelum dan saat pandemi covid-19, dan mengetahui perbedaan rasio-rasio pada Altman Z- score sebelum dan saat pandemic covid-19 pada perusahaan manufaktur yang terdaftar dalam Bursa Efek Indonesia (BEI) periode 2019-2020. Jenis penelitian ini menggunakan pendekatan kuantitatif dengan metode Purposive Sampling. Terdapat 14 Sampel Perusahaan yang sesuai dengan kriteria yang ditentukan. Hasil penelitian ini menunjukkan bahwa pada regresi linier sederhana nilai Altman Z-score tidak berpengaruh terhadap harga saham sebelum pandemi covid-19 dan saat pandemi covid -19.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115570463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Indonesia, rice production varies from province to province, resulting in both large and small disparities between provinces. In Indonesia, East Java, Central Java and West Java Provinces have the highest rice production. In contrast to East Java and Central Java, however, the total rice consumption per year in West Java is the highest. In linear regression, the coefficients are the same for all regions, while each region sometimes has different influencing factors, resulting in spatial diversity. Consequently, the Geographically Weighted Regression (GWR) method was used to model the rice production of West Java Provincial regencies/municipalities by accounting for spatial heterogeneity. The GWR model employs the fixed bi-square kernel function as its weighting function. This model includes five explanatory variables, such as number of agricultural labor, number of used rice seed, number of two-wheel tractor, number of water pump, and number of farmer groups, with rice production as the response variable. GWR model has greater coefficient determination (96.8 percent) and smaller AIC values (920.76) than global regression. During the period of 2018-2020, the number of two-wheel tractors and the number of water pumps had the greatest impact on rice production in West Java and the number of two-wheeled tractors and the number of farmer groups variables has an effect on rice production in most regencies/municipalities in West Java. There are 11 groups of areas which has the similarity of significant predictor variables.
{"title":"Modeling Rice Production in West Java by Means Geographically Weighted Regression","authors":"Muhamad Sobari, I. Jaya","doi":"10.11594/jesi.02.03.08","DOIUrl":"https://doi.org/10.11594/jesi.02.03.08","url":null,"abstract":"In Indonesia, rice production varies from province to province, resulting in both large and small disparities between provinces. In Indonesia, East Java, Central Java and West Java Provinces have the highest rice production. In contrast to East Java and Central Java, however, the total rice consumption per year in West Java is the highest. In linear regression, the coefficients are the same for all regions, while each region sometimes has different influencing factors, resulting in spatial diversity. Consequently, the Geographically Weighted Regression (GWR) method was used to model the rice production of West Java Provincial regencies/municipalities by accounting for spatial heterogeneity. The GWR model employs the fixed bi-square kernel function as its weighting function. This model includes five explanatory variables, such as number of agricultural labor, number of used rice seed, number of two-wheel tractor, number of water pump, and number of farmer groups, with rice production as the response variable. GWR model has greater coefficient determination (96.8 percent) and smaller AIC values (920.76) than global regression. During the period of 2018-2020, the number of two-wheel tractors and the number of water pumps had the greatest impact on rice production in West Java and the number of two-wheeled tractors and the number of farmer groups variables has an effect on rice production in most regencies/municipalities in West Java. There are 11 groups of areas which has the similarity of significant predictor variables.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127144330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Sihombing, Suryadiningrat Suryadiningrat, Deden Achmad Sunarjo, Yoshep Paulus Apri Caraka Yuda
Penelitian ini bertujuan mengindentifikasi outlier (pencilan) dan kenormalan data pada univariat data. Adapun data yang digunakan berupa data persentase kemiskinan di Indonesia tahun 2022 yang berasal dari Badan Pusat Statistik. Metode pengujian outlier dilakukan dengan menggunakan grafik box plot, histrogram dan uji Grubbs. Sedangkan pengujian kenormalan data menggunkan uji SK Test dan Shapiro Wilk. Hasil penelitian menunjukkan terdapat data outlier yaitu pada observasi Provinsi Papua, dan data tidak berdistribusi normal. Selanjutnya dilakukan berbagai alternatif dalam menangani data outlier. Hasil menunjukkan menggunakan teknik tranformasi box cox, winsorizing dan trimming data, dapat menyelesaikan masalah outlier data. Metode box cox dan trimming sekaligus mampu mengatasi masalah kenormalan data, sedangkan metode winsorizing belum dapat mengatasi masalah kenormalan data.
{"title":"Identifikasi Data Outlier (Pencilan) dan Kenormalan Data Pada Data Univariat serta Alternatif Penyelesaiannya","authors":"P. Sihombing, Suryadiningrat Suryadiningrat, Deden Achmad Sunarjo, Yoshep Paulus Apri Caraka Yuda","doi":"10.11594/jesi.02.03.07","DOIUrl":"https://doi.org/10.11594/jesi.02.03.07","url":null,"abstract":"Penelitian ini bertujuan mengindentifikasi outlier (pencilan) dan kenormalan data pada univariat data. Adapun data yang digunakan berupa data persentase kemiskinan di Indonesia tahun 2022 yang berasal dari Badan Pusat Statistik. Metode pengujian outlier dilakukan dengan menggunakan grafik box plot, histrogram dan uji Grubbs. Sedangkan pengujian kenormalan data menggunkan uji SK Test dan Shapiro Wilk. Hasil penelitian menunjukkan terdapat data outlier yaitu pada observasi Provinsi Papua, dan data tidak berdistribusi normal. Selanjutnya dilakukan berbagai alternatif dalam menangani data outlier. Hasil menunjukkan menggunakan teknik tranformasi box cox, winsorizing dan trimming data, dapat menyelesaikan masalah outlier data. Metode box cox dan trimming sekaligus mampu mengatasi masalah kenormalan data, sedangkan metode winsorizing belum dapat mengatasi masalah kenormalan data.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126663879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global disruptions—the Covid-19 pandemic, financial crisis, trade tension, and geopolitical issues—led to uncertainty across the world economies. The impact either on individual emerging or advanced countries, however, remains unclear. To this end, this study is simulating a shock of a one percent increase in equity risk premium permanently in all sectors in all countries, and focusing on exploring its impact on the United States (US), the United Kingdom (UK), Australia, China, Indonesia, and India. The results reveal that no countries are immune from the short-lived synchronised nuisance. Investment plummeted massively following the profound drop in interest rate, while unemployment suddenly soars, and Gross Domestic Product (GDP) contracted dramatically. In the long run, all economies reverse and converge to the initial condition. Nevertheless, there would be persistent GDP loss and sluggish investment in all economies. Therefore, policy responses should be designed based on strong international cooperation, focusing on fiscal policy to limit the impact of global losing confidence.
{"title":"Modelling the Impact of a Rise in Global Equity Risk Premium: The G-Cubed Simulation","authors":"Realita Eschachasthi","doi":"10.11594/jesi.02.03.04","DOIUrl":"https://doi.org/10.11594/jesi.02.03.04","url":null,"abstract":"The global disruptions—the Covid-19 pandemic, financial crisis, trade tension, and geopolitical issues—led to uncertainty across the world economies. The impact either on individual emerging or advanced countries, however, remains unclear. To this end, this study is simulating a shock of a one percent increase in equity risk premium permanently in all sectors in all countries, and focusing on exploring its impact on the United States (US), the United Kingdom (UK), Australia, China, Indonesia, and India. The results reveal that no countries are immune from the short-lived synchronised nuisance. Investment plummeted massively following the profound drop in interest rate, while unemployment suddenly soars, and Gross Domestic Product (GDP) contracted dramatically. In the long run, all economies reverse and converge to the initial condition. Nevertheless, there would be persistent GDP loss and sluggish investment in all economies. Therefore, policy responses should be designed based on strong international cooperation, focusing on fiscal policy to limit the impact of global losing confidence.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127411431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sumber daya adalah hal yang tidak bisa dipisahkan dalam sebuah bisnis, baik berupa bahan baku, Sumber daya Manusia,keuangan, dsb. Sebuah bisnis dituntut untuk bisa menyediakan dan mengelolahnya secara efektif dan efisien terhadap sumber-sumber daya yang ada untuk tetap berjalannya kegiatan operasional sebuah usaha. Dibutuhkan berbagai strategi dengan melihat dua sisi, baik secara Eksternal (ekonomi makro), maupun secara internal (ekonomi mikro). Berdasarkan survey yang dilakukan oleh SBA (Small Business Administration) dikatakan bahwa ditahun ke-5 angka prosentase bisnis yang bertahan hanya sekitar 45-50% (https://www.paper.id). Kondisi-kondisi tersebut tidak terlepas dari bagaimana sebuah manajemen itu dibangun. Karena manajemen yang bagus merupakan salah satu faktor yang mengantarkan sebuah bisnis mampu bertahan dan maju, begitupun sebuah manajemen harus memperhatikan sisi ekonomi makro yaitu bagaimana lingkungan diluar perusahaan ikut mempengaruhi pengambilan keputusan bagi seorang pemimpin perusahaan, seperti kebijakan fiskal yang diterapkan oleh pemerintah, kondisi politik, dsb. Selain itu hal yang tak kalah penting yang harus diperhatikan adalah pengelolaan sumber-sumber daya yang dimiliki oleh perusahaan secara optimal. Target penjualan merupakan hal yang ingin dicapai oleh sebuah perusahaan, upaya yang bisa dilakukan adalah dengan melakukan pengelolaan/manajemen yang baik, antara lain menyiapkan tenaga penjualan yang profesional. Tenaga penjualan perlu dibangun dan ditingkatkan kinerjanya agar menghasilkan produktivitas yang optimal. Dalam membangun kinerja yang bagus, berpikir postif bukanlah hanya konsep, namun faktor yang krusial dalam meningkatkan kinerja. Pikiran positif yang dimiliki oleh karyawan akan bisa menyelamatkan keberlangsungan hidup sebuah perusahaan, sebaliknya jika tingkat berpikir positif rendah, maka karyawan bagi perusahaan bisa menjadi musuh dari dalam yang setiap saat bisa menghancurkan perusahaan. Agar karyawan tidak menjadi boomerang, maka manajemen perlu mengolah, memoles karyawan menjadi pribadi yang tangguh dalam menghadapi tantangan bisnis, salah satunya dengan memberi dukungan secara sosial, melalui appraisal, tangible, self esteem dan belonging support. Artikel ini merupakan artikel konseptual, yang menggambarkan bagaimana target penjualan bisa dicapai melalui produktivitas yang bagus,yang dibangun melalui pengoptimalan appraisal, tangible, self esteem dan belonging support dalam sebuah manajemen.
{"title":"Appraisal, Tangible, Self Esteem dan Belonging Support dalam Mempengaruhi Pencapaian Target Penjualan","authors":"Fitriana Fitriana","doi":"10.11594/jesi.02.03.03","DOIUrl":"https://doi.org/10.11594/jesi.02.03.03","url":null,"abstract":"Sumber daya adalah hal yang tidak bisa dipisahkan dalam sebuah bisnis, baik berupa bahan baku, Sumber daya Manusia,keuangan, dsb. Sebuah bisnis dituntut untuk bisa menyediakan dan mengelolahnya secara efektif dan efisien terhadap sumber-sumber daya yang ada untuk tetap berjalannya kegiatan operasional sebuah usaha. \u0000Dibutuhkan berbagai strategi dengan melihat dua sisi, baik secara Eksternal (ekonomi makro), maupun secara internal (ekonomi mikro). Berdasarkan survey yang dilakukan oleh SBA (Small Business Administration) dikatakan bahwa ditahun ke-5 angka prosentase bisnis yang bertahan hanya sekitar 45-50% (https://www.paper.id). Kondisi-kondisi tersebut tidak terlepas dari bagaimana sebuah manajemen itu dibangun. Karena manajemen yang bagus merupakan salah satu faktor yang mengantarkan sebuah bisnis mampu bertahan dan maju, begitupun sebuah manajemen harus memperhatikan sisi ekonomi makro yaitu bagaimana lingkungan diluar perusahaan ikut mempengaruhi pengambilan keputusan bagi seorang pemimpin perusahaan, seperti kebijakan fiskal yang diterapkan oleh pemerintah, kondisi politik, dsb. Selain itu hal yang tak kalah penting yang harus diperhatikan adalah pengelolaan sumber-sumber daya yang dimiliki oleh perusahaan secara optimal. \u0000Target penjualan merupakan hal yang ingin dicapai oleh sebuah perusahaan, upaya yang bisa dilakukan adalah dengan melakukan pengelolaan/manajemen yang baik, antara lain menyiapkan tenaga penjualan yang profesional. Tenaga penjualan perlu dibangun dan ditingkatkan kinerjanya agar menghasilkan produktivitas yang optimal. Dalam membangun kinerja yang bagus, berpikir postif bukanlah hanya konsep, namun faktor yang krusial dalam meningkatkan kinerja. Pikiran positif yang dimiliki oleh karyawan akan bisa menyelamatkan keberlangsungan hidup sebuah perusahaan, sebaliknya jika tingkat berpikir positif rendah, maka karyawan bagi perusahaan bisa menjadi musuh dari dalam yang setiap saat bisa menghancurkan perusahaan. Agar karyawan tidak menjadi boomerang, maka manajemen perlu mengolah, memoles karyawan menjadi pribadi yang tangguh dalam menghadapi tantangan bisnis, salah satunya dengan memberi dukungan secara sosial, melalui appraisal, tangible, self esteem dan belonging support. Artikel ini merupakan artikel konseptual, yang menggambarkan bagaimana target penjualan bisa dicapai melalui produktivitas yang bagus,yang dibangun melalui pengoptimalan appraisal, tangible, self esteem dan belonging support dalam sebuah manajemen.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"726 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133283742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Penelitian ini bertujuan mengetahui dampak dari Program Indonesia Pintar (PIP) terhadap Status Sekolah Anak di Indonesia. Data yang digunakan bersumber dari Survei Sosial Ekonomi Nasional (SUSENAS) Badan Pusat Statistik tahun 2013-2019. Model yang digunakan adalah regresi binomial logistik. Selain itu dalam pemodelan ditambahkan efek Diffence in Difference untuk melihat dampak kebijakan dari PIP. Hasil yang didapat keikutsertaan PIP meningkatkan peluang anak untuk bersekolah. Selain itu, anak yang berada di kota dan Kepala Rumah Tangga berstatus kawin memiliki peluang sekolah yang lebih tinggi. Di sisi lain anak dengan status kawin, jenis kelamin laki-laki, sedang bekerja dan berada pada keluarga dengan ukuran angota keluarga yang besar memiliki peluang untuk sekolah yang lebih rendah. Oleh karena pemerintah lebih mengintensifkan lagi program-program bantuan Pendidikan agar semakin besar peluang anak-anak terus bersekolah sehingga menghasilkan sumber-sumber daya berkualitas dimasa depan.
{"title":"Aplikasi Model Diffence in Difference Pada Regresi Binomial Logistik","authors":"P. Sihombing, Wisnu Pratiko","doi":"10.11594/jesi.02.03.01","DOIUrl":"https://doi.org/10.11594/jesi.02.03.01","url":null,"abstract":"Penelitian ini bertujuan mengetahui dampak dari Program Indonesia Pintar (PIP) terhadap Status Sekolah Anak di Indonesia. Data yang digunakan bersumber dari Survei Sosial Ekonomi Nasional (SUSENAS) Badan Pusat Statistik tahun 2013-2019. Model yang digunakan adalah regresi binomial logistik. Selain itu dalam pemodelan ditambahkan efek Diffence in Difference untuk melihat dampak kebijakan dari PIP. Hasil yang didapat keikutsertaan PIP meningkatkan peluang anak untuk bersekolah. Selain itu, anak yang berada di kota dan Kepala Rumah Tangga berstatus kawin memiliki peluang sekolah yang lebih tinggi. Di sisi lain anak dengan status kawin, jenis kelamin laki-laki, sedang bekerja dan berada pada keluarga dengan ukuran angota keluarga yang besar memiliki peluang untuk sekolah yang lebih rendah. Oleh karena pemerintah lebih mengintensifkan lagi program-program bantuan Pendidikan agar semakin besar peluang anak-anak terus bersekolah sehingga menghasilkan sumber-sumber daya berkualitas dimasa depan.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124735561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The case of the Covid-19 pandemic was first detected in Indonesia on March 2, 2020 and is still ongoing. The COVID-19 pandemic has had many social and economic impacts. The impact will be very widespread, starting from politics, economy, social, culture, defense, and security, as well as community welfare. This unstable economy also has an effect on labor conditions in Indonesia, such as the rising unemployment rate. This study aims to determine the effect of the pandemic on unemployed or temporarily unemployed workers based on the classification of place of residence, gender, age, last completed education, expertise, and business field. This study uses the August 2021 National Manpower Survey (SAKERNAS) dataset with the enter method binary logistic regression method. The results showed that the classification of residence. Age, last education completed, expertise, and business field affect the temporary unemployed condition due to COVID-19, while the classification of residence, gender, age, and the last education completed affect the unemployment condition due to COVID-19.
{"title":"Dampak Pandemi Covid-19 terhadap Tenaga Kerja di Indonesia","authors":"May Friska","doi":"10.11594/jesi.02.03.02","DOIUrl":"https://doi.org/10.11594/jesi.02.03.02","url":null,"abstract":"The case of the Covid-19 pandemic was first detected in Indonesia on March 2, 2020 and is still ongoing. The COVID-19 pandemic has had many social and economic impacts. The impact will be very widespread, starting from politics, economy, social, culture, defense, and security, as well as community welfare. This unstable economy also has an effect on labor conditions in Indonesia, such as the rising unemployment rate. This study aims to determine the effect of the pandemic on unemployed or temporarily unemployed workers based on the classification of place of residence, gender, age, last completed education, expertise, and business field. This study uses the August 2021 National Manpower Survey (SAKERNAS) dataset with the enter method binary logistic regression method. The results showed that the classification of residence. Age, last education completed, expertise, and business field affect the temporary unemployed condition due to COVID-19, while the classification of residence, gender, age, and the last education completed affect the unemployment condition due to COVID-19.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129986366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pembangunan suatu wilayah dapat diukur dari sisi obyektif maupun subyektif. Kebahagiaan merupakan salah satu indikator kesejahteraan masyarakat dari sisi subyektif.. Berdasarkan data BPS pada tahun 2014, PDRB per kapita di Propinsi Yogyakarta merupakan terendah di Pulau Jawa, akan tetapi berdasarkan indeks kebahagiaan Propinsi Yogyakarta merupakan propinsi dengan indeks kebahagiaan tertinggi. Oleh karena itu, perlu dikaji lebih lanjut determinan apa yang mempengaruhi tingkat kebahagiaan di Propinsi Yogyakarta. Ukuran kebahagian seseorang biasanya diukur dengan tingkatan dari mulai tidak bahagia, bahagia, sangat bahagia. Dalam analisis statistik, ukuran bertingkat ini merupakan skala pengukuran ordinal. Model yang umum digunakan dalam regresi logistik ordinal adalah Proportional Odds Model. Dengan menggunakan data IFLS5 tahun 2014-2015 dilakukan pemodelan regresi logistik ordinal pada determinan tingkat kebahagiaan di Propinsi Yogyakarta. Hasil dari model yang diperoleh variabel yang signifikan mempengaruhi tingkat kebahagiaan di Propinsi Yogyakarta yaitu variabel usia, status perkawinan dan pendidikan. Berdasarkan nilai odds rasio dapat disimpulkan bahwa semakin tinggi usia individu di Propinsi Yogyakarta cenderung lebih tidak bahagia Sedangkan jika dilihat dari status perkawinan individu dengan status kawin cenderung lebih bahagia dibandingkan dengan individu yang tidak kawin. Begitu juga untuk variabel pendidikan, individu dengan kategori pendidikan tertinggi perguruan tinggi cenderung lebih bahagia dibandingkan dengan individu dengan kategori pendidikan tertinggi sekolah dasar.
{"title":"Penerapan Proportional Odds Model pada Regresi Logistik Ordinal Determinan Tingkat Kebahagiaan di Provinsi Yogyakarta","authors":"Nur Azizah, D. Yanti","doi":"10.11594/jesi.02.03.06","DOIUrl":"https://doi.org/10.11594/jesi.02.03.06","url":null,"abstract":"Pembangunan suatu wilayah dapat diukur dari sisi obyektif maupun subyektif. Kebahagiaan merupakan salah satu indikator kesejahteraan masyarakat dari sisi subyektif.. Berdasarkan data BPS pada tahun 2014, PDRB per kapita di Propinsi Yogyakarta merupakan terendah di Pulau Jawa, akan tetapi berdasarkan indeks kebahagiaan Propinsi Yogyakarta merupakan propinsi dengan indeks kebahagiaan tertinggi. Oleh karena itu, perlu dikaji lebih lanjut determinan apa yang mempengaruhi tingkat kebahagiaan di Propinsi Yogyakarta. Ukuran kebahagian seseorang biasanya diukur dengan tingkatan dari mulai tidak bahagia, bahagia, sangat bahagia. Dalam analisis statistik, ukuran bertingkat ini merupakan skala pengukuran ordinal. Model yang umum digunakan dalam regresi logistik ordinal adalah Proportional Odds Model. Dengan menggunakan data IFLS5 tahun 2014-2015 dilakukan pemodelan regresi logistik ordinal pada determinan tingkat kebahagiaan di Propinsi Yogyakarta. Hasil dari model yang diperoleh variabel yang signifikan mempengaruhi tingkat kebahagiaan di Propinsi Yogyakarta yaitu variabel usia, status perkawinan dan pendidikan. Berdasarkan nilai odds rasio dapat disimpulkan bahwa semakin tinggi usia individu di Propinsi Yogyakarta cenderung lebih tidak bahagia Sedangkan jika dilihat dari status perkawinan individu dengan status kawin cenderung lebih bahagia dibandingkan dengan individu yang tidak kawin. Begitu juga untuk variabel pendidikan, individu dengan kategori pendidikan tertinggi perguruan tinggi cenderung lebih bahagia dibandingkan dengan individu dengan kategori pendidikan tertinggi sekolah dasar.","PeriodicalId":136508,"journal":{"name":"Jurnal Ekonomi Dan Statistik Indonesia","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121376839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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