scholarly journals Kluster Tanaman Pangan Unggulan di Provinsi Jawa Tengah

2021 ◽  
Vol 21 (1) ◽  
pp. 55-68
Author(s):  
Choiroel Woestho ◽  
Milda Handayani ◽  
Adi Wibowo Noor Fikri
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Food Plants ◽  
Series Data ◽  
Food Crops ◽  
Food Crop ◽  
Land Area ◽  
Location Quotient ◽  
Central Java ◽  
Central Java Province

The food crop sector has an important role for regions in Indonesia. Food plants can be a determinant for an area in meeting the needs of the people in that area. In addition, the food crop sector, if developed, can become revenue for the region. This study aims to analyze the leading food plants in 35 districts / cities in Central Java Province. By using the location quotient (LQ) method and the Regional Specialization Index. The data used is time series data from 2014 to 2019 in 35 districts / cities in Central Java Province for food crops based on land area and production. The results obtained for the average LQ value of food crops based on land area, there are only 12 districts / cities which are the basis for superior food crops with Wonogiri Regency at the top. Meanwhile, based on the average LQ value based on production, only 11 districts / cities are the basis for superior food crops with Semarang Regency being the top. For the specialization index based on both land area and production, there is no Regency / City that specializes in Central Java Province.   Keywords: Foodcrop Sector, Location Quotient, Specialization Index, Central Java   Abstrak   Sektor tanaman pangan mempunyai peranan penting bagi daerah di Indonesia. Tanaman pangan dapat menjadi penentu bagi suatu daerah dalam memenuhi kebutuhan masyarakat yang ada di daerah tersebut. Selain itu, sektor tanaman pangan jika dikembangkan dapat menjadi pendapatan bagi daerah. Penelitian ini bertujuan untuk menganalisis tanaman pangan unggulan yang ada di 35 Kabupaten/Kota pada Provinsi Jawa Tengah. Dengan menggunakan metode location quotient (LQ) dan Indeks Spesialisasi Regional. Data yang digunakan adalah data time series selama tahun 2014 hingga tahun 2019 pada 35 Kabupaten/Kota di Provinsi Jawa Tengah untuk tanaman pangan berdasarkan luas lahan dan produksi. Hasil yang diperoleh untuk nilai rata – rata LQ tanaman pangan berdasarkan luas lahan, hanya terdapat 12 Kabupaten/Kota yang menjadi basis bagi tanaman pangan unggulan dengan Kabupaten Wonogiri berada di urutan teratas. Sementara berdasarkan nilai rata – rata LQ berdasarkan produksi, hanya 11 Kabupaten/Kota yang menjadi basis tanaman pangan unggulan dengan Kabupaten Semarang menjadi urutan teratas. Untuk indeks spesialisasi baik berdasarkan luas lahan dan produksi, tidak ada Kabupaten/Kota yang mempunyai spesialisasi terhadap Provinsi Jawa Tengah.   Kata kunci: Tanaman Pangan, Indeks Lokalisasi, Indeks Spesialisasi, Jawa Tengah

scholarly journals Information Systems of Forecasting Incidence Rates of Dengue Fever Disease Using Multivariate Fuzzy Time Series

2020 ◽  
Vol 202 ◽  
pp. 14005
Author(s):  
Ardian Fakhru Rosyad ◽  
Farikhin ◽  
Jatmiko Endro Suseno
Keyword(s):  
Time Series ◽  
Dengue Fever ◽  
Time Series Data ◽  
Incidence Rates ◽  
Fuzzy Time Series ◽  
Series Data ◽  
Central Java ◽  
Time Series Method ◽  
Low Incidence ◽  
Central Java Province

Demak Regency is one of the regions in Central Java Province with a low incidence of Dengue Fever compared to other cities and districts. Even so, DHF control needs to be done to minimize the occurrence of dengue fever, because DHF is a fairly dangerous disease. One form of controlling the number of DHF events that is widely used is using forecasting models, one of them is using Fuzzy Time Series. The Multivariate Fuzzy Time Series (MFTS) model is a development of the Fuzzy Time Series model that can be used to forecast using time series data by using more than one variable for forecasting, compared to the Fuzzy Time Series method that usually using only one variable. Based on the research results obtained, the MFTS model has a fairly accurate MAPE value, wherein the best MAPE was at 3 years scenario with MAPE 10,728%.

scholarly journals The Effect of PAD, DAU and DAK on Poverty Rates in Java

2021 ◽  
Vol 2 (5) ◽  
pp. 1668-1683
Author(s):  
Suryani Yuli Astuti ◽  
Muhammad Ali Basyah ◽  
Farokhah Muzayinatun Niswah
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Method ◽  
Simultaneous Effect ◽  
Central Java ◽  
Negative Effect ◽  
The Relationship ◽  
Central Java Province

This study was made to determine the extent of the influence of Regional Original Income (PAD), General Allocation Funds (DAU) and Special Allocation Funds (DAK) on poverty through Regional Expenditures in Bitung City. Based on the time series data for 2016-2018 and processed based on the multiple regression analysis method for testing the path analysis used, it can be seen that the relationship between PAD, DAU, DAK and poverty rates on the island of Java. The results showed that the province of West Java on PAD, DAU and DAK had a partial effect on poverty rates and PAD, DAU and DAK had a simultaneous effect on poverty rates. Central Java Province on PAD has a negative effect on poverty rates, DAU and DAK have a partial effect on poverty rates and PAD, DAU and DAK have a simultaneous effect on poverty rates. DIY Province, although PAD has a negative effect on poverty rates, DAU has an effect on poverty and DAK has no partial effect on poverty rates and PAD, DAU and DAK have a simultaneous effect on poverty rates. East Java Province, Partially PAD has no effect on poverty rates, DAU has no effect on poverty rates and DAK has no effect on poverty rates and the influence of PAD, DAU and DAK simultaneously affects poverty rates.

scholarly journals FAKTOR - FAKTOR YANG MEMPENGARUHI PDRB KABUPATEN / KOTA JAWA TENGAH TAHUN 2008-2012

JEJAK ◽  
2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Yozi Aulia Rahman ◽  
Ayunda Lintang Chamelia
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data ◽  
Main Condition ◽  
Independent Variables ◽  
Central Java ◽  
Central Java Province

<p>Pertumbuhan ekonomi yang tinggi merupakan kondisi utama bagi kelangsungan pembangunan ekonomi daerah. Untuk mengukur kemajuan perekonomian daerah dengan mengamati seberapa besar laju pertumbuhan ekonomi yang dicapai daerah tersebut yang tercermin dari kenaikan Produk Domestik Regional Bruto (PDRB). PDRBKabupaten/Kota di Jawa Tengah selama tahun 2008- 2012 mengalami pertumbuhan karena banyak yang mempengaruhinya, seperti: Tabungan, Kredit, PAD dan Belanja Daerah. Penelitian ini bertujuan untuk menganalisis seberapa besar faktor-faktor tersebut mempengaruhi tingkat PDRB kabupaten/Kota di Jawa Tengah selama tahun 2008-2012. Variabel dependen yang digunakan dalam penelitian ini adalah PDRB, sedangkan variabel-variabel independen yaitu Tabungan, Kredit, Pendapatan Asli Daerah (PAD) dan Belanja Daerah. Penelitian ini menggunakan analisis regresi linear berganda melalui metode OLS dengan menggunakan data    time series 2008  –2012 dan data crosssection 35 kabupaten/kota di Provinsi Jawa Tengah atau yang dimaksud dengan data panel. Pengujian model dalam penelitian ini menggunakan metode FixedEffect. Hasil estimasi menunjukkan bahwa hasil analisis regresi pada α=5%menunjukkan bahwa secara parsial  variabel tabungan   dan kredit berpengaruh signifikan, sedangkan variabel PAD, dan Belanja Daerah tidak signifikan terhadap PDRB kabupaten/kota di Provinsi Jawa Tengah tahun 2008–2012. </p><p>High economic growth is the main condition for the continuation of regional economic development. To measure the progress of the regional economy, observation on the economyc growth rate in each area can be conducted. It is reflected in the increase of Gross Regional Domestic Product (GDP). The increase of GDP of regency/city in Central Java during the year of 2008- 2012 was influenced by several factors such as savings, credit, local generated revenue (PAD), and Expenditure. This study intends to analyze the affect of these factors to the level of GDP on districts / cities in Central Java during the years 2008-2012. The dependent variable used in this study is GDP. Meanwhile, the independent variables are savings, credit, revenue (PAD) and expenditure. This study uses multiple linear regression analysis by the OLS method using time series data in 2008 -2012 and data crosssection of 35 districts / cities in Central Java province which are often called as the data panel. The model is tested by using Fixed Effect. The result indicates that the results of the regression analysis on the α = 5% shows that in partial,  saving and loan have significant effect on GDP.  Meanwhile,  PAD variable and expenditurehave no significant effect on GDP districts / cities in Central Java province in 2008-2012.</p>

scholarly journals The Effect of Inequality of Educational Facilities, Health, and Road Conditions toward Income Distribution in Central Java Province, Indonesia

2018 ◽  
Vol 73 ◽  
pp. 10014
Author(s):  
Antono Herry ◽  
Purnomo Adhi ◽  
Firmansyah
Keyword(s):  
Income Distribution ◽  
Gini Index ◽  
Time Series Data ◽  
Series Data ◽  
Educational Facilities ◽  
Public Facilities ◽  
Central Java ◽  
Road Condition ◽  
The Relationship ◽  
Central Java Province

This study examines the effect of inequality of public facilities, namely education, health, and road condition, on the income inequality in Central Java Province, Indonesia. By employing the time-series data of 15 years, this study analyzes the Gini index and the relationship between the Gini index and Index of public facilities by the regression model. The study finds that the inequality of the provision of public facilities affects the income distribution in Central Java, Indonesia

PERBANDINGAN FUZZY TIME SERIES DENGAN METODE CHEN DAN METODE S. R. SINGH (Studi Kasus : Nilai Impor di Jawa Tengah Periode Januari 2014 – Desember 2019)

2020 ◽  
Vol 9 (3) ◽  
pp. 306-315
Author(s):  
Febyani Rachim ◽  
Tarno Tarno ◽  
Sugito Sugito
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Fuzzy Time Series ◽  
Series Data ◽  
Percentage Error ◽  
Series Method ◽  
Fuzzy Variables ◽  
Central Java ◽  
Time Series Method ◽  
Fuzzy Logical

Import is one of the efforts of an area to meet the needs of its population in order to stabilize prices and maintain stock availability. The value of imports in Central Java throughout 2016 amounted to 8811.05 Million US Dollars. The value of imports in Central Java is the top 10 in all provinces in Indonesia with a percentage of 6.50%. Import data in Central Java is included in the time series data category. To maintain the stability of imports in Central Java, it is deemed necessary to make a plan based on a statistical model. One of the time series models that can be applied is the fuzzy time series model with the Chen method approach and the S. R. Singh method because the method is suitable for cyclical patterned data with monthly time periods such as Import data in Central Java. Important concepts in the preparation of the model are fuzzy sets, membership functions, set basic operators, fuzzy variables, universe sets and domains. The fuzzy time series modeling procedure is carried out through several stages, namely the determination of universe discourse which is divided into several intervals, then defines the fuzzy set so that it can be performed fuzzification. After that the fuzzy logical relations and fuzzy logical group relations are determined. The accuracy calculation in both methods uses symmetric Mean Absolute Percentage Error (sMAPE). In this study the sMAPE value obtained in the Fuzzy Time Series Chen method of 10.95% means that it shows good forecasting ability. While the sMAPE value on the Fuzzy Time Series method of S. R. Singh method by 5.50% shows very good forecasting ability. It can be concluded that the sMAPE value in the S. R. Singh fuzzy time series method is better than the Chen method.Keywords: Import value, fuzzy time series , Chen, S. R. Singh, sMAPE

scholarly journals Analisis Potensi Gempa di Selatan Pulau Jawa Berdasarkan Pengamatan GPS

2020 ◽  
Vol 11 (3) ◽  
pp. 151
Author(s):  
Irwan Meilano ◽  
Agidia L. Tiaratama ◽  
Dudy D. Wijaya ◽  
Putra Maulida ◽  
S. Susilo ◽  
...  
Keyword(s):  
Time Series ◽  
Subduction Zones ◽  
Velocity Vector ◽  
Time Series Data ◽  
Principal Component ◽  
Reference Station ◽  
Tectonic Activity ◽  
Series Data ◽  
Local Data ◽  
Central Java

ABSTRAKPulau Jawa merupakan salah satu pulau yang memiliki kepadatan penduduk tinggi dengan aktivitas tektonik yang sangat aktif. Hal ini dikarenakan Pulau Jawa terletak di zona konvergensi Lempeng Indo-Australia dan Lempeng Eurasia. Aktivitas tektonik ini menghasilkan kegempaan di zona subduksi dan sesar di daratan Penelitian ini menganalisis pola vektor kecepatan yang dihasilkan melalui pengolahan data stasiun pengamatan GPS (Global Positioning System) CORS (Continuously Operating Reference Station) BIG (Badan Informasi Geospasial) di wilayah Pulau Jawa bagian selatan. Data koordinat harian dianalisis dengan metode PCA (Principal Component Analysis) untuk memisahkan sinyal tektonik berupa data deret waktu global dan non-tektonik berupa data deret waktu lokal dengan penerapan aturan pemilihan varian dominan nilai eigen dalam pembetukan PC (Principal Component) dan orthogonal vektor eigen sebagai bobot dalam meminimalkan korelasi. Hasil dari data deret waktu global dan lokal digunakan untuk menghitung besar kecepatan pergeseran dari tahun 2011 sampai 2018. Hasil pengolahan menunjukkan besar resultan vektor kecepatan pada data awal berselang 0,06 sampai 10,46 mm/tahun, pada data global antara 0,06 mm/ tahun sampai 10,39 mm/tahun, dan data lokal sebesar 0,0037 sampai 1,99 mm/tahun. Variasi spasial vektor kecepatan pengamatan GPS data domain PCA menunjukkan variasi pergeseran horizontal di wilayah Banten bergerak ke arah timur laut; Jawa Barat, Daerah Istimewa Yogyakarta, dan Jawa Tengah bergerak ke arah tenggara; dan Jawa Timur bergerak ke arah timur laut. Hasil dari inversi data pergeseran terhadap slip pada zona subduksi, menunjukkan terjadinya kekurangan slip atau terjadi coupling pada zona subduksi Jawa bagian timur dan barat, sementara terjadi kelebihan slip pada bagian tengah yang merupakan efek postseismic dari gempa Pangandaran 2006.Kata kunci: GPS, PCA, potensi gempa, vektor kecepatanABSTRACTJava is one of the island that has a high population density with very active tectonic activity. This is because Java Island is located in the convergence zone of the Indo-Australian Plate and the Eurasian Plate. This tectonic activity produces seismicity in subduction zones and inland faults. This study analyzes the velocity vector patterns generated through data processing of the GPS (Global Positioning System) CORS (Continuously Operating Reference Station) BIG (Geospatial Information Agency) observation station in the southern part of Java. Daily coordinate data were analyzed using PCA (Principal Component Analysis) method to separate time series of tectonic signals as global data and non-tectonic time series data as local data by applying the rules for selecting dominant variants of eigen values for PC formation and orthogonal eigen vectors as weights in minimizing correlations. The results from global and local time series data were used to calculate the magnitude of the displacement velocity from 2011 until 2018. The processing results show the resultant velocity vector in the initial data intermittent 0.06 to 10.46 mm/year, global data from 0.06 to 10.39 mm/year, and local data of 0.0037 to 1.99 mm/year. The spatial variation of the velocity vector in PCA domain data shows the horizontal displacement in the Banten region to the northeast; West Java, Yogyakarta Special Region, Central Java to southeast; and East Java moving to northeast. The results of the inversion of the surface displacement to slip data in the subduction zone show that there is a slip deficiency or coupling occurs in the subduction zones of Eastern and Western Java, while there is excess slip in the Central Java which is a post-seismic effect of the 2006 Pangandaran earthquake.Keywords: earthquake potential, GPS, PCA, velocity vector

scholarly journals Persepsi Kualitas Mahasiswa Program Studi DIII Akuntansi Polines Selama Praktek Kerja Lapangan (PKL) di Industri

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Moh.Hasanudin Marliyati ◽  
Sri Murtini ◽  
Resi Yudhaningsih ◽  
Retno Retno
Keyword(s):  
Information Technology ◽  
Time Series ◽  
Communication Skills ◽  
Time Series Data ◽  
Soft Skills ◽  
Series Data ◽  
Central Java ◽  
Hard Skills ◽  
Main Components

<p>This research aimed at exploring the quality of accounting diploma <br />students during their internship program in industries. The term of student’s <br />quality described in this research isexplained using 5 main components as follows: (1) communication skills (2) teamwork (3) independence (4) creativity (5) accounting and information technology (IT)-related skills. The research’s sample is industries where students of Diploma in Accounting of State Polytechnic of Semarang (SPS) took their intership and the students themselves whom have completed their internship program for three months in various institutions such as private enterprises, state owned enterprises, local government offices spread out around Central Java. The data on this research is time series data taken from 2015 to 2016 and was collected using questionnaires from the corresponding industries about the students competencies both hard skills and soft skills. <br />Data was scored using Likert scale, ranges from Poor (1) to Excellent (5) and <br />analyzed using statistic descriptive. The result showed that average students’ <br />quality during their internship was good. Among the 5 skills observed, the <br />corresponding industries ranked teamwork skills as the highest, followed by <br />independence, creativity, communication skills and the accounting and IT -related skills. It is expected that the result can be used for future development of Accounting Program Study of SPS.</p>

scholarly journals The Effect of General Allocation Funds and Local Own-Revenue on Regional Government Expenditure in Central Java Province

2021 ◽  
Vol 2 (1) ◽  
pp. 257-266
Author(s):  
Samsul Afif Rahula ◽  
Prasetyo Ari Bowo
Keyword(s):  
Central Government ◽  
Time Series Data ◽  
Government Expenditure ◽  
Series Data ◽  
Regional Government ◽  
Significant Positive Effect ◽  
Central Java ◽  
High Dependency ◽  
Positive Effect ◽  
Central Java Province

The implementation of regional autonomy indirectly requires regions to be independent, the level of independency in Central Java which is measured by the ratio of Local Own-source Revenue to total regional revenue of 18.2%, which is the lowest compared to other regions in Java in the 2015-2018 period. Central Java's low independency is in line with its dependency on transfers from the central government, particularly the general allocation fund of 40%. Low independency and high dependency is due to the lack of ability of Local Own-source Revenue to meet regional expenditures and the large role of general allocation fund in meeting these shortages. This study aims to analyze the effect of general allocation funds and local own-source revenue on regional expenditures. This study uses a quantitative method with panel data combination of cross-section data from 35 districts/cities in Central Java Province and time-series data for the period 2016-2018. The analytical method used is multiple linear regression. The results of this study indicate that the general allocation fund has a significant and more dominant positive effect on regional expenditures and also local own-source revenue shows a significant positive effect on regional expenditures, which means that the greater the value of local own-source revenue and general allocation fund, the greater the value of regional expenditures. Simultaneously, general allocation funds and local own-source revenue have a significant positive effect on regional expenditures.

Extraction of Paddy Land Area Based on NDVI Time-series Data: Taking Jiangsu Province as an Example

2011 ◽  
Vol 13 (2) ◽  
pp. 273-280 ◽  
Author(s):  
Cuicui MIAO ◽  
Nan JIANG ◽  
Shikui PENG ◽  
Heng LV ◽  
Yang LI ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Jiangsu Province ◽  
Series Data ◽  
Land Area ◽  
Ndvi Time Series ◽  
Paddy Land

scholarly journals ANALISIS ARIMA DAN WAVELET UNTUK PERAMALAN HARGA CABAI MERAH BESAR DI JAWA TENGAH

2020 ◽  
Vol 9 (3) ◽  
pp. 247-262
Author(s):  
Chrisentia Widya Ardianti ◽  
Rukun Santoso ◽  
Sudarno Sudarno
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Parametric Method ◽  
Haar Wavelet ◽  
Time Span ◽  
Series Data ◽  
Central Java ◽  
The One ◽  
Better Than ◽  
Analysis Of Time Series

Time series is a type of data collected according to the sequence of times in a certain time span. Time series data can be used as a predictor of future conditions. Analysis of time series data, one of the ARIMA units, is a parametric method that requires an assumption to get valid results. Data stationarity is one of the factors that must be fulfilled. Wavelet is a non-parametric method that is able to represent time and frequency information simultaneously, so that it can analyze non-stationary data. This research presents forecasting the price of red chili in Central Java using ARIMA and wavelet with the approach of the Multiscale Autoregressive (MAR) model. The best model is the one with the smallest MSE value. The results showed that the ARIMA(0,1,1) model was said to be the best model with MSE = 2252142. However, because the assumption of normality is not fulfilled, an alternative process is done with wavelet. Wavelet approach results show that the MAR model Haar filter level (j) = 4 with MSE = 2175906 is better than Daubechies 4 filter 4 level (j) = 1 with MSE = 3999669. Therefore, the Haar wavelet is considered better in the time series analysis. Keyword : ARIMA, wavelet, MAR, forecasting, MSE

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