No 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.

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.

An intervention model is an analytical method for evaluating or measuring the impact of an external event called intervention, such as a natural disaster, holidays, sales promotions, and other policy changes. Two types of intervention variables will be used to represent the presence or absence of the event, i.e., a pulse or step. The pulse function is used to represent a temporary intervention, whereas the step function shows a long-term intervention. This study aims to develop a time series model with an intervention of step function for measuring the impact of two policies related to the prohibition of fishing and the export of lobster seeds on the export value of Indonesian lobster. These policies are the Ministerial Regulation No.1 of 2015 since January 2015 related banning of lobster seeds fishing (called first intervention) and the Ministerial Regulation No. 56 of 2016 since January 2017 related lobster seeds fishing and export ban policy (called second intervention). These regulations are designed to ensure lobster sustainability and add value to lobsters that are currently overfished. The results show that both policies significantly affect the export value of lobster in Indonesia, and the interventions have a permanent impact.

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.