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Determinan Produktivitas Tenaga Kerja Industri Manufaktur Besar dan Sedang di Pulau Jawa Sari, Rika Dwi Puspita; Oktora, Siskarossa Ika
Jurnal Ekonomi dan Pembangunan Indonesia Vol 21 No 2 (2021): Juli 2021
Publisher : Department of Economics-FEB UI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21002/jepi.v21i2.1298

Abstract

Industrialization is one of the government’s focuses on development. Java is an area focused on the industry. However, the labor productivity of large and medium manufacturing industries in Java is lower than regions outside Java and national level of productivity. This study aims to analyze determinants of labor productivity in large and medium manufacturing industries in all provinces in Java from 2010 to 2015 using panel data regression. As the best model, fixed effect model showed that HDI, real wages, and vehicle PMTB has a positively significant effect on labor productivity. -------------------------------------- Industrialisasi merupakan salah satu fokus pemerintah dalam pembangunan. Pulau Jawa merupakan wilayah yang difokuskan untuk industri. Namun, produktivitas tenaga kerja Industri Besar dan Sedang (IBS) di Pulau Jawa lebih rendah dibandingkan daerah di luar Pulau Jawa dan tingkat produktivitas nasional. Penelitian ini bertujuan untuk menganalisis determinan produktivitas tenaga kerja IBS seluruh provinsi di Pulau Jawa periode 2010–2015 dengan menggunakan metode regresi data panel. Hasil analisis menunjukkan Fixed Effect Model merupakan model terbaik untuk penelitian ini, dengan Indeks Pembangunan Manusia (IPM), upah riil, dan Pembentukan Modal Tetap Bruto (PMTB) kendaraan berpengaruh secara signifikan positif terhadap produktivitas tenaga kerja.
DETERMINAN PENGANGGURAN TERDIDIK DI PROVINSI NUSA TENGGARA TIMUR (NTT) TAHUN 2018 MENGGUNAKAN REGRESI LOGISTIK BINER Maria Valentina Makung; Ristanto Hadi; Yohana Rosaripatria; Siskarossa Ika Oktora
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 2 (2021): Jurnal Statistika
Publisher : Department Statistics, Faculty Mathematics and Natural Science, Universitas Muhammadiyah S

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.2.2021.64-78

Abstract

Pengangguran telah menjadi masalah serius yang harus diselesaikan di NTT. Tingkat pengangguran di NTT telah meningkat dari tahun ke tahun. Ironisnya, tingkat pengangguran ini didominasi oleh pengangguran terdidik. Berdasarkan data dari BPS, tingkat pengangguran di NTT tahun 2018 cenderung menurun, tetapi pengangguran yang berpendidikan meningkat. Dengan menggunakan data Sakernas Agustus 2018, penelitian ini bertujuan untuk melihat faktor-faktor yang mempengaruhi pengangguran terdidik di NTT yang dilihat berdasarkan karakteristik individualnya. Karakteristik individu yang digunakan adalah jenis kelamin, usia, status rumah tangga, status perkawinan, pelatihan kerja, pengalaman kerja, dan daerah tempat tinggal. Metode analisis yang digunakan dalam penelitian ini adalah analisis deskriptif dan regresi logistik biner. Hasil analisis deskriptif menunjukkan karakteristik tenaga kerja terdidik di NTT tahun 2018 mayoritas memiliki usia 15-24 tahun, jenis kelamin perempuan, tidak berstatus kepala rumah tangga, tidak pernah menikah, tidak pernah berpartisipasi dalam pelatihan kerja, memiliki pengalaman kerja dan tinggal di wilayah perkotaan. Hasil inferensia menunjukkan bahwa variabel yang mempengaruhi pengangguran berpendidikan adalah variabel umur, status rumah tangga, status perkawinan, pengalaman kerja dan daerah tempat tinggal. Sementara jenis kelamin dan pelatihan kerja tidak memengaruhi tenaga kerja terdidik untuk menjadi pengangguran. Hasil penelitian ini sangat penting bagi pemerintah NTT untuk mengambil kebijakan yang tepat untuk menyelesaikan pengangguran terdidik.
DETERMINAN TRANSAKSI NONTUNAI DI INDONESIA DENGAN PENDEKATAN ERROR CORRECTION MECHANISM (ECM) MODEL Zulfa Nur Fajri Ramadhani; Siskarossa Ika Oktora; Indonesian Journal of Statistics and Its Applications IJSA
Indonesian Journal of Statistics and Applications Vol 3 No 1 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i1.190

Abstract

Consumption is an activity that must be done by everyone. In order to consume something, a transaction is needed to get the goods or services desired. One kind of transaction that is used by many people nowadays is non-cash transaction. Since Bank Indonesia established Gerakan Nasional Non Tunai (GNNT) in August 2014, the value of non-cash transactions exceeds the value of cash transactions. It happenned because people prefer non-cash to cash transaction which is easier, safer, more practical, and more economical. Besides, an increase in non-cash transactions can also be influenced by other factors. Therefore, a study is conducted to analyze the determinants of non-cash transactions from the macro side by using Error Correction Mechanism (ECM). The data used in this study are secondary data from Bank Indonesia and Badan Pusat Statistik with monthly period from January 2010 until December 2017. The results showed that in the long run, private savings and BI rate have positive effect on non-cash transactions. In the short run, private savings and money supply have positive effect on non-cash transactions. While inflation does not affect non-cash transactions, both in the short and long run.
ANALISIS KURVA ROC PADA MODEL LOGIT DALAM PEMODELAN DETERMINAN LANSIA BEKERJA DI KAWASAN TIMUR INDONESIA Muhammad Rizqi Fachrian Nur; Siskarossa Ika Oktora
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (964.939 KB) | DOI: 10.29244/ijsa.v4i1.524

Abstract

Binary logistic regression is used for probability modeling or to predict binary response variables (Success / Failure) from one or more explanatory variables that are continuous or categorical. In carrying out this analysis, there are several ways to test the suitability of the resulting model, and one of them is the area under the ROC curve. The application of the analysis method in this study is the determinant of the elderly population to work. The population of the elderly in Indonesia is increasing every year. Many views that the elderly depend on other residents, especially in terms of the economy. However, if seen from the percentage of elderly working in Indonesia, it is increasing, including the elderly in KTI. The purpose of this study is to determine the characteristics of the elderly in KTI, know the factors that influence the decision of the elderly population to work in KTI and find out the tendency of variables that affect the decision of the elderly to work in KTI. The data used are raw data from Badan Pusat Statistik (BPS) was Survei Sosial Ekonomi Nasional (Susenas) Kor March 2018. This study using descriptive analysis methods and binary logistic regression. The results are that the variables that significantly influence the decisions of the elderly to work are residence, gender, age, education, family status, marital status, health complaints, and health insurance. Elderly who has characteristics residing in rural, male sex, classified as young elderly (60-69 years old), has the highest level of elementary school education, has the status of KRT in his family, is married, has no complaints health, and not having health insurance will have a greater tendency to decide to work.
ANALISIS SPASIAL KETERTINGGALAN DAERAH DI INDONESIA TAHUN 2018 MENGGUNAKAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION Tata Pacu Maulidina; Siskarossa Ika Oktora
Indonesian Journal of Statistics and Applications Vol 4 No 3 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i3.690

Abstract

Development inequality in Indonesia has led the developed and underdeveloped regions. Regional backwardness caused by high inequality must be handled properly to prevent negative impacts on national stability. But in fact, the handling of underdeveloped regions is only effective in Western Indonesia, while in Eastern Indonesia tends to be not optimal. This study aims to explore regional backwardness in Indonesia and examines the factors that influence it. Based on data, underdeveloped regions tend to cluster in eastern Indonesia, and the independent variables have large variations between regions. This indicates dependence and spatial heterogeneity. Therefore, this study applies spatial analysis using the Geographically Weighted Logistic Regression (GWLR) method. GWLR shows better performance in modeling the regional backwardness in Indonesia compared to its global model (binary logistic regression). This study provides a local model for each district/city that can be used by local governments to implement more effective policies based on factors that do have significant effects on regional backwardness.
Determinants of Male Adolescents Smoking Behavior in Indonesia using Negative Binomial Regression Angel Zushelma Hartono; Siskarossa Ika Oktora
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p182-194

Abstract

Adolescent smoking habits have become the Ministry of Health's major program associated with tobacco consumption. In 2016, the prevalence of adolescent smoking aged 10-18 years reached 8.8% and were rate increasingly against the Strategic Planning Ministry of Health 2015-2019 target to lower adolescent smoking prevalence to 5.4%. Male adolescents consuming cigarettes are higher than females. Whereas, high consumption of cigarettes in men will increase the risk of impotence and decrease reproductive health quality to affect future generations' quality. This study aims to determine the general picture of smoking behavior in Indonesia's male adolescent in 2018 and any variables that affect the number of cigarettes consumed. The analytical method used is Poisson Regression and Negative Binomial Regression. The data source used is raw data Riskesdas 2018 with the unit of analysis are male adolescent smokers aged 10-18 years. Research indicates that most male adolescents are light smokers. Heavy smokers were dominated by older age, living in a rural area, poorly educated, employed, lived with a household head who was a smoker, and had low education. Age, location of residence, education level, working status, smoking status, and household head education level significantly affect male adolescents' smoking behavior.
Determinants of Leprosy Prevalence in Sulawesi Island Using Spatial Error Model Geraldi Putra P Balebu; Siskarossa Ika Oktora
Jurnal Varian Vol 5 No 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i2.1632

Abstract

Leprosy is one of the infectious diseases and has become a serious health problem in Indonesia. Based on the publication of the Health Ministry of Republik Indonesia, there are still many areas in Indonesia that have not reached the leprosy elimination status, one of which is Sulawesi Island. The condition of leprosy prevalence in Sulawesi Island is still fluctuating and tends to be high. In addition, leprosy can also be spread across regions. This study aims to analyze whether a spatial effect is present on leprosy prevalence and determine the variables that possibly affect leprosy prevalence. Data used are from Health Profile and Province in Figure publications with an analysis unit consisting of 81 districts/cities. The results show that there is a spatial effect on leprosy prevalence in Sulawesi Island. Queen contiguity-based spatial weights are also considered while performing the spatial analysis. Based on the results of Spatial Error Models can be concluded that population density, the number of multibacillary (MB) leprosy cases, and spatial effect significantly affect the leprosy prevalence. In contrast, a clean and healthy lifestyle, proper water access, and proper sanitation access do not significantly affect the leprosy prevalence.
Analisis Multivariate Adaptive Regression Splines (MARS) pada Prediksi Ketertinggalan Kabupaten Tahun 2014 Siskarossa Ika Oktora
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 7 No 2 (2015): Journal of Statistical Aplication and Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (670.814 KB) | DOI: 10.34123/jurnalasks.v7i2.26

Abstract

The purposes of this research are to build underdeveloped regency model and make a prediction in 2014 based on economic categories, Human Resources (HR), infrastructures, fiscal capacity, accessibility, and regional characteristics with MARS method. MARS is a classification method which can handle highdimensional data with unknown pattern in advance, and can be applied to see the interaction between variables. MARS is an alternative method when the data doesn’t fulfil the parametric statistics assumptions. From MARS model, there are three variables that affect underdeveloped regency, they are consumption expenditure per capita, life expectancy, and percentage of household electricity users. The accuracy of MARS model is very high, 97.83 percent and can be used to make a prediction. Based on MARS model, at the end of the National Development Plan 2010-2014 is predicted a significant transitions in regency’s status. This model can also be used to predict the condition of new regency based on empirical data, because in the earlier classification, the status of regency just follows the status of parent region.
DETERMINAN STATUS UNMET NEED FOR LIMITING BIRTH PADA WANITA USIA SUBUR BERSTATUS KAWIN DI JAWA BARAT TAHUN 2017 Valencia Shabrina Putri; Siskarossa Ika Oktora
Jurnal Kependudukan Indonesia Vol 15, No 1 (2020)
Publisher : Research Centre for Population, Indonesian Institute of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jki.v15i1.449

Abstract

Rapid annual population growth in West Java, the province with the highest population in Indonesia, is concerning due to its effect that could lead to population explosion in the future. One of the reasons for this rapid growth is caused by a high birth rate. However, the implementation of the family planning program to control the birth rate faced a challenge in terms of unmet need for family planning in women of reproductive age. Unmet need for limiting birth has a more critical role in total unmet birth control need. This study aims to determine factors that affect the unmet need for limiting birth at married women of reproductive age in West Java Province in 2017 using binary logistic regression. Results indicated that women's age, women's education level, husband's education level, and residence significantly affected unmet need status for limiting birth. Also, the tendency of unmet need for limiting birth is greater for women aged 35-49 years, has education junior high school and above, the husband has under junior high school education and living in the rural area.
Pemodelan Determinan Pernikahan Dini di Daerah Pedesaan dengan Pendekatan Regresi Logistik Biner Aloysius Bela Boro; Siskarossa Ika Oktora
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.46865

Abstract

Abstract. The behavior of early marriage in Indonesia is still high and most prevalent in rural areas. In addition to violating the law, a marriage performed before reaching 19 years also has many negative effects. One of them is the death of the mother and the baby. Using data from the Demographic and Health Survey 2017, this study aims to analyze the determinants of early marriages in rural areas in Indonesia. The response variable used is binary categorical data, namely the status of early marriage and not early marriage, so we use a binary logistic regression. The steps performed on this model include estimates of parameters, parameter testing either simultaneously or partially, and a test of the goodness of fit. The results show that the variables of education level, internet access, and wealth index significantly affected early marriage status in rural areas in Indonesia in 2017. Based on the goodness of fit result, this model is proper for modeling early marriage behavior in Indonesia. The study results can be used as a reference for the government in formulating policies to overcome the problem of early marriage in rural areas in Indonesia. Keywords: early marriage, rural area, categorical response variable, binary logistic regression