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"Penelitian ini bertujuan untuk mengetahui faktor-faktor dan sektor lapangan usaha yang menyerap angkatan kerja muda umur 18-24 tahun lulusan SLTA yang meliputi jenis kelamin, tempat iinggal, status perkawinan, status pekerjaan, pelatihan dan sektor lapangan kerja (pertanian, manufaktur dan jasa). Data yang digunakan adalah data SAKERNAS bulan Agustus tahun 2007 dengan analisis diskriptif dan inferensial. Tahapan pertama penelitian adalah estimasi upah angkatan kerja dengan regresi linier. Selanjutnya dengan regresi linier menghitung probabilitas bekerja untuk menganalisis penyerapan angkatan kerja muda umur 18-24 tahun lulusan SMA dan lulusan SMK. Hasil penelitian menunjukkan bahwa jumlah penduduk umur 15 tahun ke atas sebanyak 164.118.3224 orang, dimana 29.284.l88 orang adalah angkatan kerja muda umur 18-24 tahun. Mereka merupakan 68,01 persen angkatan kerja muda (15-24 tahun) serta 17,84 persen dari jumlah penduduk usia kerja (15-64 mhun) dengan karakteristik 50,08 persen laki-laki, 70,70 persen berstatus tidak kawin, 47,73 persen bertempat tinggal di perkotaan dan 38,00 persen berpendidikan tamat SLTA. Pada penduduk umur 18-24 tahun tamat SLTA, berdasarkan kegiatannya 37,69 persen berstatus bekerja, 19,98 persen mencari kerja, 25,05 persen sekolah dan 17,28 persen lainnya. Hasil deskriptif upah menunjukkan bahwa upah angkatan kerja muda umur 18-24 tahun lulusan SMK lebih besar dibanding upah lulusan SMA. Hasil analisis inferensial probabilitas bekerja angkatan kerja muda umur 18-24 lulusan SLTA menunjukkan lulusan SMK lebih besar dibanding lulusan SMA. Sektor lapangan usaha yang banyak menyerap lulusan SMA adalah sektor pertanian, sektor manufaktur untuk lulusan SMK, sedangkan probabilitas bekerja Iulusan SMA dan lulusan SMK kurang pada sektor jasa.

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This research to know the factors and working field sectors that absorb the young labor forces ages 18~24 years old which graduated from SLTA that involve sex, residence, marital status, training and working Held sectors (Agriculture, manufactory, and service) and taining The data which is used is Sakernas data on august 2007 by descriptive and inferential analysis. The first step of research is wage estimation of labor forces with linier regression. Secondy by linier regression to count work probability to analyze absorb1ion of labor forces Hom 18-24 years old of SMA and SMK graduations.

The result of this reseach explains that sum of people up to 15 years old are 164.118.1323 people, where 29.284.188 people are labor force of 18-24 years old. They are 68,01 percent from young labor force (15-24 years old) and 17,84 percent from sum of 15-64 years old. Their characteristics are 50,08 percent male, 70,70 percent unmarried yet status, 47,73 percent who live in the city and 38,00 percent of SLTA graduation. Based on its activity 37,69 percent is working, 19,98 percent is seeker, 25,05 percent school age and 17,28 percent the others.

The result of wage descriptive analisis shown that wage at the youngs of SMK are bigger than the of wage SMA graduation. The result of inferensial analysis from working probability at young labor forces age 18-24 years old which graduated from SLTA shown that SMK graduations are bigger than SMA graduations. SMA -graduations are absorted at agriculture sector, manufacture sector for SMK graduations, meanwhile SMA and SMK graduations are not absorted in service sector."

"Penelitian ini bertujuan untuk menganalisis hubungan antara status ketenagakerjaan suami yang terdampak pandemi covid-19 dengan status angkatan kerja istri yang baru masuk ke pasar kerja melalui mekanisme “added worker effect/AWE”. Hasil analisis deskriptif menggunakan data Sakernas Agustus 2020 menunjukkan bahwa terdapat perbedaan persentase AWE yang berasal dari istri bila dilihat berdasarkan pendapatan suaminya. Berdasarkan model probit tahap pertama two step heckman ditemukan bahwa istri suaminya mengalami penurunan pendapatan memiliki probabilitas 5,78 persen poin lebih rendah dan istri yang pendapatan suaminya tetap memiliki probabilitas 6,49 persen poin lebih rendah untuk masuk ke pasar kerja daripada tetap mengurus rumah tangga dibandingkan istri yang suaminya tidak ada pendapatan. Hasil regresi multinomial pada tahap kedua two step heckman menunjukkan bahwa istri yang suaminya mengalami penurunan pendapatan atau pendapatan suaminya tetap cenderung untuk menjadi pekerja informal daripada pekerja formal, dibandingkan dengan istri yang suaminya tidak memiliki pendapatan.

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This study aims to analyze the relationship between the employment status of husbands affected by the covid-19 pandemic and wife’s labor force status who have just entered the labor market through the "added worker effect/AWE" mechanism. The results of a descriptive analysis using Sakernas August 2020 data show that there is a difference in the percentage of AWE originating from the wife when viewed based on her husband's income. Based on probit model in the first stage of Two Step Heckman, it was found that the husband's wife experiencing a decrease in income has a 5.78 percentage point lower probability and a wife whose husband's income is fixed has a 6.49 percentage point lower probability of entering the labor market than continuing to take care of the household compared with wife whose husband has no income. The results of the multinomial regression in the second stage of Two Step Heckman show that wives whose husbands experience a decrease in their husband's income or income is fixed tend to become informal workers rather than formal workers, compared to wives whose husbands have no income.

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"Penelitian ini bertujuan untuk menghitung kontribusi pertumbuhan tenaga kerja dan kapital UMKM dari sektor Pertanian, Pertambangan dan sektor Industri Pengolahan terhadap pertumbuhan PDB non migas menggunakan Solow Growth Accounting. Data yang digunakan bersumber dari Kementrian Koperasi dan UMKM yang bekerja sama dengan BPS. Dengan menggunakan model pertumbuhan Solow dan regresi model efek tetap, diperoleh hasil bahwa dampak pertumbuhan tenaga kerja dan kapital UMKM berbeda antar sektor. Dampak positif signifikan pertumbuhan tenaga kerja UMKM terjadi pada sektor Industri Pengolahan, sedangkan untuk kapital terjadi pada sektor Pertanian. Sumber pertumbuhan ekonomi masih didominasi oleh pertumbuhan kapital usaha besar.

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The objectives of this study are to count the contribution of labor growth and capital growth of Micro, Small and Medium Enterprises (MSMEs) from Agriculture, Mining and Manufacture sector to GNP growth using Solow Growth Accounting. Data in this study are from Cooperative and Micro, Small and Medium Enterprises Department and Central Bureau of Statistic (BPS). Using the Solow growth model and fixed effect model regression, was found that impact of labor growth and capital growth of MSMEs are different on each sector. The significant positif impact of labor growth was found on Manufacture sector, while for capital growth was found on Agriculture sector. The source of economic growth was dominated by capital growth of big firm."

"[ABSTRAKStudi ini bertujuan untuk mengetahui faktor faktor yang memengaruhi lansia bekerja menurut lapangan pekerjaan di Indonesia dengan menggunakan data Susenas kor 2013 Hasil regresi multinomial logit menunjukkan bahwa tempat tinggal upah dan pendidikan merupakan faktor paling berpengaruh terhadap keputusan bekerja di sektor pertanian sedangkan keberadaan jaminan kesehatan tidak memiliki pengaruh signifikan Sementara itu variabel upah pendidikan dan status sebagai kepala rumah tangga merupakan faktor yang paling berpengaruh bagi lansia untuk bekerja di sektor non pertanian

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ABSTRACT

This study aims to find out factors those affect elderly to work by sector in Indonesia using the 2013 Susenas core data The result of multinomial logistic regression shows that place of living wage and level of education are the most influential factors for the elderly to work in the agricultural sector while availability of health insurance does not have significant effect For comparison wage level of education and the status as a head of household are the influential factors behind decision of elderly to work in non agricultural sector ;This study aims to find out factors those affect elderly to work by sector in Indonesia using the 2013 Susenas core data The result of multinomial logistic regression shows that place of living wage and level of education are the most influential factors for the elderly to work in the agricultural sector while availability of health insurance does not have significant effect For comparison wage level of education and the status as a head of household are the influential factors behind decision of elderly to work in non agricultural sector , This study aims to find out factors those affect elderly to work by sector in Indonesia using the 2013 Susenas core data The result of multinomial logistic regression shows that place of living wage and level of education are the most influential factors for the elderly to work in the agricultural sector while availability of health insurance does not have significant effect For comparison wage level of education and the status as a head of household are the influential factors behind decision of elderly to work in non agricultural sector ]"