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Journal : PROSIDING SEMINAR NASIONAL

PERBANDINGAN METODE ORDINARY LEAST SQUARE (OLS) DAN REGRESI ROBUST PADA PRODUK DOMESTIK REGIONAL BRUTO (PDRB) DI JAWA TENGAH TAHUN 2013 Muhammad Nasihin; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

High economic growth is a key condition for the sustainability of regional economic development. To measure the local economy by observing how much economic growth rate the region achieved as reflected by the increase of Gross Regional Domestic Product (GRDP). PDRB is one of the common indicators used to measure the success rate of economic development in a region / region, because thesuccess of a development depends on the ability of the region to mobilize limited resources so as to make changes in a skruktural that can encourage the overall economic growth and balanced. This study aims to analyze how big these factors affect the level of GDP of regencies / cities in Java Tengan in the period2013. Sources of data used in this study are secondary data in Central Java Central obtained from the Central Bureau of Statistics of Central Java Province in 2013. The variables used in this research are endogenous (Y) and exogenous (X) variables. Endogenous variables (Y) in the research is PDRB Agriculture while the variable (X) in the study there are 2 namely AngkaTPAK, and Wages. Using OLSmethod and ROBUST method of both methods is the best model that is on robus method. Keywords: OLS, Robust Regression,Gross Regional Domestic Product
SPATIAL AUTOCORRELATION UNTUK DETEKSI DATA KEWILAYAHAN PRODUK DOMESTIK REGIONAL BRUTO PROVINSI JAWA TENGAH Muhammad Saifudin Nur; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Spatial Autocorrelationl is one of the method that can determined spatial characteristic in data variables. Sparial Autocorrelation is able to define whether there is spatial characteristic ineach variables at regression models. The purpose of this study is to map and Detecting the Spatial Autocorrelation  for Gross Regional Domestic Product (GDRP) data in Central Java province with appropriate spatial weighting. The data used is the GDRP data and the factors that affect the GDRPie labor, human capital, roads infrastructure in 2015. Based on the results, the spatial efect on GDRP data is significanly occurs. Keywords : Spatial Autocorrelation, Ordinary Least Square, GDRP
MODELLING GROSS DOMESTIC REGIONAL BRUTO IN CENTRAL JAVA PROVINCEUSING SPATIAL REGRESSION Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Proceeding 3rd ISET 2017 | International Seminar on Educational Technology 3rd 2017
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Central Java is considered potential to trigger an increase in national economic growth, the economic characteristics of Central Java is determined by agriculture, industry and trade, hotels and restaurants (PHR).Each region in Central Java has different characteristics, the western and southern regions are dominated by the agricultural sector, the northern region is dominated by PHR, while the east is dominated by the industrial sector.Based on these characteristics, it is necessary to do a spatial data-based analysis on GRDP data so that the abovephenomena are modeled based on the economic characteristics of each region and know the relation of theregion to each other in the context of the growth of Gross Regional Domestic Product (GRDP). Spatial regression is one of the solutions of the above problems, this method of development of regression analysis, spatial regression not only see the global effect also see the local effect. In this study using spatial regression with lag in independent variables, this model is called spatial lag X (SLX). Data used in this research is data obtained from Central Bureau of Statistics (BPS) in 2015, including data of GRDP price applies to 35 districts and cities in Central Java Province for the year 2015. Besides data of GRDP, data of factors influencing GRDP price Such as Road infrastructure data, Human Capital, and Manpower, are also used in this study. Based on the analysis result, it can be concluded that the human capital parameters give significant influence on OLS and SLX model. While in the SLX model only the weighted variable of labor has significant effect. Furthermore thebest model is shown with the highest R2 value, the SLX model produces R2 of 0.64, so the best model obtainedis the SLX model. Thus, it can be concluded that the GRDP value in a region in Central Java is influenced by the value of the human capital of the region as well as the labor of the nearest region.Keywords: Spatial Regression, Moran’s I, Gross Domestic Regional Bruto
Autocorrelation Spatial Program Swasembada Padi di Jawa Tengah Abdul Karim; Rochdi Wasono
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: PROSIDING IMPLEMENTASI PENELITIAN PADA PENGABDIAN MENUJU MASYARAKAT MANDIRI BERKEMAJUAN
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Salah satu peran penting Provinsi Jawa Tengah bagi perekonomian wilayah dan nasional adalah sebagai penghasil tanaman pangan. Produksi padi di daerah ini memiliki surplus yang berpotensi mendukung ketahanan pangan wilayah. Menurut Badan Pusat Statistik (BPS), pada tahun 2013 secara nasional Jawa Tengah termasuk penghasil padi terbesar ketiga setelah Jawa Barat dan Jawa Timur, dengan produksi mencapai 10,34 juta ton padi kering giling. Sejalan dengan produksi yangtinggi, tingkat produktifitas padi di Jawa Tengah adalah sebesar 56,06 kwintal per hektar, lebih tinggi dari rata-rata nasional (BPS, 2013). Penelitian ini ingin mengetahui dependensi spasialmenggunakan pendekatan global morans. Berdasarkan analisis global morans, produksi, luas panen, jumlah petani dan luas panen padi terdapat dependensi spasial dengan alfa 5 persen. Jadi dapat disimpulkan bahwa terdapat keterkaitan spasial antar kabupaten dan kota di Jawa Tengah untuk produksi, luas panen, jumlah petani dan luas panen padi. Kata Kunci : Autocorrelation spatial, Morans I, Dependensi Spasial, Produksi Padi.
PEMODELAN PRODUK DOMESTIK REGIONAL BRUTO PROVINSI JAWA TENGAH DENGAN PENDEKATAN SPATIAL AUTOREGRESSIVE CONFUSED (SAC) Haznam Prabowo; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Economic growth becomes one indicator of the state's economic condition.Increased economy is done by increasing development in various economicsectors and equitable economic development to the regions. Therefore, with theequalization of economic development will provide an increase in the value ofgross domestic product of a region. In this research, the description of grossregional domestic product and influencing factors from the territorial point ofview with costumaize weighting matrix, and spatial autoregressive confusedPDRB modeling using spatial effect on response and residual variables. Theresults showed that the spread of GRDP in Central Java Province has a patternthat clustered between adjacent areas. Based on the GRDP relationship withthe variables that affect the workforce (TK), human capital (HC), roadinfrastructure (INF), it can be interpreted that the similarities and differences incharacteristics of each district that close together cause increase or decreaseGDP Central Java Province. This study was conducted with the aim ofdetermining the weighting matrix and modeling the Central Java GRDP withthe appropriate weighting matrix. Based on SAC model analysis results aresignificantly better than OLS model with AIC value. The significant variablesdirectly affect human capital. While the indirect effect occurs on residuals.Keywords: GRDP, Spatial autoregressive confused (SAC), Spatial Econometrik
PERBANDINGAN METODE ORDINARY LEAST SQUARE (OLS) DAN REGRESI ROBUST Ibnu Dharma Syahputra; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Human Development Index (HDI) is a comparative measurement of life expectancy, literacy, education. A country that is said to be advanced can be reflected if one of its reference is the Human Development Index (HDI), which of course explains how much human development in a country. Indonesia has human resources that can be explored and explored to show a significant index of human development. The Human Development Index (IPM) is a composite index that is influenced by health indicators represented by life expectancy (AHH), education indicators represented by the average school length (RLS) and economic indicators represented by public purchasing power (PPP) . Decentralization of Central Kalimantan Province is expected to make arrangements that can realize the life of the people of Central Kalimantan to be more prosperous and healthy. One of the elements in human development is to make the people to live longer and healthier lives. Data source used in this research is secondary data of HDI in Central Kalimantan obtained from Central Bureau of Statistics of Central Kalimantan Province 2014. Variable used in this research is endogenous variable (Y) and exogenous variable (X). Variable endogenus (Y) in the research that is HDI (percent) while the variable (X) in the study there are 3 that is Life Expectancy Numbers, Perkapita Revenue, Average Learning Length.Using OLS method and ROBUST method of both methods the best model that is on robotic methodKeywords: HDI, OLS, ROBUST
Pelatihan Pengembangan Keprofesian Berkelanjutan (PKB) untuk Meningkatkan Kompetensi Profesional bagi Guru SD Muhammadiyah 8 Dan SD Islam Nu Pungkuran Kota Semarang melalui Workshop, Klinik, Dan Pendampingan Abdul Karim; Iswahyudi Joko S
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Tujuan khusus dari program ini terhadap mitra adalah memberikan motivasi guru untuk melaksanakan program pengembangan keprofesian berkelanjutan,meningkatkan kualitas dan kuantitas program pengembangan keprofesian berkelanjutan, meningkatkan kualitas dan kuantitas karya khususnya karya pengembangan penelitian tindakan kelas hingga berbentuk pelaporan hasil,meningkatnya kemampuan pemilihan kesesuaian metode statistik dalamevaluasi pembelajaran dan penelitian tindakan kelas dengan penggunaankomputer serta adanya sarana promosi mitra ke masyarakat umum. Tujuan tersebut diselesaikan menggunakan metode workshop dengan teknik presentasimateri dilanjutkan dengan diskusi, teknik klinik, sedangkan masalah terbatasnya kegiatan promosi dilakukan dengan pembuatan website dan mediasosial sekolah mitra, selanjutnya pendampingan.Hasil capaian dari kegiatan program kemitraan masyarakat bagi guru SDMuhammadiyah 08 dan SD Islam NU Pungkuran yaitu; 1) adanya peningkatanpengetahuan tentang jenjang karir guru, program keprofesian berkelanjutan,memahami lebih lanjut tentang penelitian tindakan kelas dan evaluasipembelajaran, serta tersedianya sarana promosi untuk masing-masing sekolah;2) adanya pendampingan dalam kegiatan-kegiatan tersebut.Keywords: pengembangan keprofesian berkelanjutan, penelitian tindakan kelas
PERBANDINGAN REGRESI ROBUST DENGAN OLS PADA PRODUKSI UBI JALAR PROVINSI JAWA TENGAH TAHUN 2015 Endah Suryaningsih Utami; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Ordinary Least Square (OLS) or Method of Least Squares (MKT) is one of the methods used to get the estimator parameter values of the regressionmodel, but the resultant estimator is strongly influenced by the outlier data.Although the parameter estimator results are strongly influenced by the data,it can use Robust Regression method to handle it so it is not necessary tothrow out the data, as it may be enough to provide information. The application of the two methods is on the production of sweet potato data per regency and city in Central Java province in 2015. The results showed that the data is not normally distributed, both OLS and robust model. Keywords: OLS, Robust Regression, Sweet Potato Production
PERBANDINGAN METODE ORDINARY LEAST SQUARE (OLS) DAN METODE REGRESI ROBUST PADA HASIL PRODUKSI PADI DI KABUPATEN INDRAMAYU Prichilia Putu Makarti; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

One of the goals of SDGs (Sustainable Devloment Goals) on food security is to end hunger, achieve food security, improve nutrition and promote sustainable agriculture. So that food security is an important concern for the government, especially on rice commodities. In 2013 West Java became the largest producer of production in Indonesia and one district which became the largest rice producing center in West Java is Indramayu District with total production of 1,435,938 tons. OLS (Ordinary Least Square) is a regression method that minimizes the number of quadratic errors. While robust regression is a regression method used when the distribution of the error is not normal or the existence of the influence of the model. In this research, it is found that robust method is better than OLS method. Keywords: Rice, OLS, Robust
EFFECT OF SPATIAL AUTOCORRELATION STRUCTURE OF EMPLOYMENT IN CENTRAL JAVA Devi Sumayya Sara; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Proceeding 3rd ISET 2017 | International Seminar on Educational Technology 3rd 2017
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Industry, agriculture and THR sectors are some of the leading sectors in Central Java . Central Java with thecapital city of Semarang City, is the third in Indonesia with the highest population in addition to West Java and East Java. Given the high population density and economic growth rate, it should also be followed by the sector's ability to absorb the available employment. Whereas in reality, the world of work or industry and professional associations often complain that the quality of staff (graduates) has not yet met the required skills demands (competencies). So the need for assessment of the absorption of employment from elementary school to upper for the planning of education system, so that education is more directed to education system oriented to the world of work appropriately and more efficiently with adequate amount and quality can absorbed. Data used in this research is observation data to Central Statistics Agency of Central Java and Ministry of Education and Culture of Central Java for the period of 2015. Observation unit in this research is cities in Central Java , the data used among others the amount of absorption Workforce in general with basic education background  toupper. In addition to employment data, data supporting factors such as workforce, industrial GDP value, agricultural GDP value, THR GDP value, and wage employment is also a research variable. The results of this study are the variables that significantly influence the model are the variables workforce, agricultural GDP value, THR GDP value, and wage employment. While significant variables have significant and significant influence in the spatial model are the variables workforce, industrial GDP value, agricultural GDP value, andTHR GDP value. Keywords: Employment, Spatial Autocorrelation