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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Ekonomi & Kebijakan Publik BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Jurnal Ketenagakerjaan Prosiding Seminar Nasional Official Statistics Jurnal Kebijakan Pembangunan Daerah (JKPD)
Siagian, Tiodora Hadumaon
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation

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PENERAPAN REGRESI LOGISTIK BINER DALAM MENENTUKAN DETERMINAN PENGANGGURAN USIA MUDA TERDIDIK DI PROVINSI BANTEN Hakim, Syifa Rahmawati; Apriliansyah, Apriliansyah; Fitri, Muti Nurjannah; Sofyan, Sabiq; Siagian, Tiodora Hadumaon
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 9 No 2 (2021): VOLUME 9 NOMOR 2 TAHUN 2021
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v9i2.21370

Abstract

Pemanfaatan era bonus demografi tidak bisa tercapai jika tidak diimbangi dengan peningkatan kualitas dan pemberdayaan sumber daya manusia yang tersedia. Salah satu indikator yang seringkali digunakan dalam mengukur pemberdayaan sumber daya manusia, yaitu TPT (Tingkat Pengangguran Terbuka). Provinsi Banten menempati posisi pertama dengan TPT tertinggi di Indonesia pada tahun 2019 sebesar 8,11 persen. Selain itu, sebagian besar pengangguran di Banten memiliki pendidikan terakhir SMA/sederajat yakni sebesar 65,15 persen. Selain pemberdayaan SDM terdidik yang kurang optimal, potensi sumber daya manusia usia muda (15-29 tahun) juga belum sepenuhnya terserap dalam pasar kerja. Persentase pemuda yang menganggur di Banten menempati posisi kedua tertinggi, yaitu sebesar 11,45. Oleh karena itu, penelitian ini bertujuan untuk mengetahui faktor-faktor yang memengaruhi pengangguran terdidik di kalangan pemuda di Provinsi Banten menggunakan analisis regresi logistik biner. Data penelitian bersumber dari data sekunder BPS, yaitu Survei Angkatan Kerja Nasional (Sakernas) Agustus 2019 untuk mengetahui faktor-faktor yang memengaruhi pengangguran terdidik di kalangan pemuda. Hasil penelitian menunjukkan variabel wilayah tempat tinggal, jenis kelamin, umur, dan status perkawinan berpengaruh signifikan terhadap status bekerja angkatan kerja usia muda terdidik di Provinsi Banten pada tahun 2019.
TINGKAT AKURASI PENERIMA PROGRAM PERLINDUNGAN SOSIAL PADA RUMAH TANGGA PERTANIAN DI INDONESIA Tusianti, Ema; Siagian, Tiodora Hadumaon
Jurnal Ekonomi & Kebijakan Publik Vol 14, No 2 (2023)
Publisher : Pusat Penelitian, Badan Keahlian DPR RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22212/jekp.v14i2.3367

Abstract

The majority of poor households in Indonesia depend on agriculture for their livelihoods. Poverty alleviation can be focused on agricultural households (RTPs). This study aims to analyze the accuracy of social protection program beneficiaries for poor RTPs based on 2021 National Socio-Economic Survey. Poverty is measured by the multidimensional approach. The accuracy is measured by distribution of beneficiaries and counted by a confusion matrix. The results found that the percentage of severely poor RTPs receiving Prosperous Family Cards (KKS), Family Hope Program (PKH), or Non-Cash Food Assistance (BPNT), routine and non-routine local government is only less than 30 percent, respectively. Surprisingly, it is also found that many non-poor RTPs received the KKS, PKH, BPNT, routine and non-routine local government aid, by 15 percent, 18 percent, 23 percent, 7 percent, and 16 percent respectively. The accuracy rate of social protection program beneficiaries is varied, but the lowest rate is the BPNT beneficiaries, namely 76 percent. The accuracy rate of social protection program distribution tended to be lower for RTP than the total households, indicating a case of inaccuracy distribution in rural areas.Keywords: agricultural households, social protection program, multidimensional poverty, accuracy rateAbstrakMayoritas rumah tangga miskin di Indonesia menggantungkan hidupnya dari sektor pertanian. Pengentasan kemiskinan utamanya dapat difokuskan pada Rumah Tangga Pertanian (RTP). Penelitian ini bertujuan menganalisis ketepatan penerima program perlindungan sosial pada RTP berdasarkan data Survei Sosial Ekonomi Nasional 2021. Dalam penelitian ini kemiskinan diukur dengan pendekatan multidimensi. Ketepatan pemberian bantuan dilihat dari sebaran data penerima perlindungan sosial dan dihitung dari matriks konfusi. Hasil penelitian menemukan bahwa persentase RTP sangat miskin yang memiliki Kartu Keluarga Sejahtera (KKS), menerima manfaat Program Keluarga Harapan (PKH), menerima Bantuan Pangan Non Tunai (BPNT), bantuan rutin dan tidak rutin pemerintah daerah (pemda), masing-masing kurang dari 30 persen. Temuan mengejutkan adalah banyak RTP tidak miskin menerima program KKS, PKH, BPNT, bantuan rutin, dan bantuan non rutin pemda, masing-masing sebesar 15 persen, 18 persen, 23 persen, 7 persen dan 16 persen. Tingkat akurasi penerima perlindungan sosial bervariasi, namun paling rendah adalah pada distribusi BPNT, yaitu sebesar 76 persen. Tingkat akurasi penerima perlindungan sosial pada RTP lebih rendah dari penerima bantuan rumah tangga keseluruhan. Dengan lebih banyaknya RTP yang tinggal di pedesaan, hal tersebut memperkuat dugaan ketidakakuratan penerima perlindungan sosial di pedesaan.Kata kunci: rumah tangga pertanian, bansos, kemiskinan multidimensi, tingkat akurasi
Kesenjangan Kondisi Pengangguran Lulusan SMK/MAK di Indonesia: Analisis Antargender dan Variabel-Variabel yang Memengaruhinya Hermawan, Arif; Mufiedah, Maziyyatul; Madina, Virginia; Santika, Zukhrufiyah Mei; Kasim, Muhammad Faturahman; Siagian, Tiodora Hadumaon
Jurnal Ketenagakerjaan Vol 18 No 3 (2023)
Publisher : Pusat Pengembangan Kebijakan Ketenagakerjaan Kementerian Ketenagakerjaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47198/jnaker.v18i3.246

Abstract

Indonesia masih memerlukan usaha yang cukup besar untuk mengatasi pengangguran, terutama bagi lulusan SMK/MAK. Menurut Badan Pusat Statistik (BPS), lulusan Sekolah Menengah Kejuruan (SMK)/Madrasah Aliyah Kejuruan (MAK) merupakan kontributor terbesar Tingkat Pengangguran Terbuka (TPT) Indonesia pada Agustus 2021. Selain itu, TPT lulusan SMK/MAK antara perempuan dan laki-laki masih memiliki perbedaan yang cukup besar. Berdasarkan Survei Angkatan Kerja Nasional (Sakernas) Agustus 2021, TPT perempuan lulusan SMK/MAK mencapai 10,17 persen sementara TPT laki-laki lulusan SMK/MAK mencapai 11,57 persen. Hal ini menunjukkan bahwa masih terdapat ketimpangan gender dalam aspek ketenegakerjaan pada lulusan SMK/MAK di Indonesia. Kesetaraan gender dalam ketenagakerjaan perlu diciptakan karena memiliki dampak pada pertumbuhan ekonomi. Oleh karena itu, penelitian ini bertujuan untuk mengetahui variabel yang signifikan memengaruhi status menganggur lulusan SMK/MAK antargender di Indonesia pada tahun 2021. Penelitian ini menggunakan data Sakernas Agustus 2021 yang dianalisis dengan metode regresi logistik biner. Hasil penelitian ini menunjukkan bahwa variabel yang berpengaruh secara signifikan terhadap status menganggur pada lulusan SMK/MAK perempuan adalah umur, klasifikasi tempat tinggal, status perkawinan, periode lulus, status disabilitas, dan klasifikasi jurusan sementara variabel yang berpengaruh signifikan terhadap status menganggur pada lulusan SMK/MAK laki-laki adalah umur, status perkawinan, periode lulus, status disabilitas, dan klasifikasi jurusan.
Pengelompokkan Wilayah Berdasarkan Variabel-Variabel Kemiskinan di Provinsi Aceh dengan Metode Average Linkage Hierarchical Clustering Wahyudi, Muhammad Rafidzaky; Siagian, Tiodora Hadumaon
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2256

Abstract

The big problem facing the Indonesian government is poverty. Aceh Province is one of the poorest provinces in Indonesia. It ranked 6th and even became the poorest province in the Western region of Indonesia. This condition is quite pathetic considering that Aceh is a province that has special autonomy and quite a large regional income, making it one of the richer provinces. Therefore, this study aims to cluster regions in Aceh Province based on poverty variables using the average linkage hierarchical clustering method and compare the results in 2017 and 2022. The results of the study show that the clustering results in 2017 are no different from 2022. Two clusters were formed, Cluster 1 consists of 3 districts with low poverty levels, and Cluster 2 consists of 20 districts with high poverty levels. This explains that in the 2017–2022 Aceh government period, areas with high poverty levels remain in the high poverty category, and vice versa. It means that the poverty alleviation efforts carried out by the Aceh government during that period have not been able to optimally improve the welfare of the Acehnese population.
Model-Based Approach for Clustering Regencies/Cities in The Land of Papua Based on Food Security Indicators Alfarizal, Ridson; Thahar, Safira Fauziana; Mardani, Shodaidah Ika; Ramadhan, Syairilla Muthia; Marpaung, Leandro Pandapotan; Siagian, Tiodora Hadumaon
Jurnal Ilmu Pertanian Indonesia Vol. 30 No. 1 (2025): Jurnal Ilmu Pertanian Indonesia
Publisher : Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18343/jipi.30.1.19

Abstract

The demand for food continues to increase as population growth concerns the Indonesian government, as stated in the second goal of the Sustainable Development Goals, namely zero hunger. The National Food Agency (BPN) uses the Food Security Index (IKP) to monitor food security conditions in Indonesia's district/city and provincial levels. Based on the BPN data, most districts/cities in The Land of Papua (so called Irian Province before the year 2000) are food insecure. However, the IKP has a weakness in the subjectivity of determining weights so that it can disguise the failure of a program or exaggerate a success. The model-based clustering (MBC) method can measure the food security of districts/cities in this area based on food security indicators. However, the data conditions are generally not multivariate distributed, and there are many outliers, so this study used MBC with multivariate t distribution because it is more robust. The best model was obtained with two clusters based on the largest Bayesian Information Criterion value. Cluster 1, located in the mountains and islands such as Nduga, Intan Jaya, Mamberamo Tengah, Puncak, and Lanny Jaya, had low food security, low indicator achievements with high poverty characteristics, many households with a portion of household expenditure on the food of more than 65%, low access to electricity and clean water, low life expectancy and average years of schooling for women, and the percentage of stunted toddlers. Meanwhile, Cluster 2, areas with high food security, had the opposite condition. Keywords: food security, model-based clustering, multivariate t distribution, Land of Papua
THE EXPLOITATION STATUS OF WORKING SCHOOL-AGE CHILDREN IN INDONESIA: A MULTILEVEL BINARY LOGISTIC REGRESSION ANALYSIS Ariansyah, Setiawan; Siagian, Tiodora Hadumaon
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp291-302

Abstract

Many children in Indonesia are exploited in the workforce. In 2022, 12.22 percent of school-age children worked more than 40 hours per week. Children are considered exploited if they work more than 20 hours a week. Children who work for a long time have serious impacts. This study aims to determine a general picture of the exploitation of working school-age children in Indonesia and its influence factors. This study uses the March 2023 Socioeconomic Survey (SUSENAS) data by utilizing multilevel analysis specifically the two-level binary logistic regression method. The study results showed that 54.22 percent of school-age children are working and exploited in Indonesia. The individual and regional contextual factors that are significantly associated with the exploitation status of working school-age children are age, sex, education level, education of household head, sex of household head, employment status of household head, Smart Indonesia Programme (PIP) ownership status, family size, expected years of schooling (HLS), and poverty level. This study finds that increasing age, male sex, lack of access to the PIP, low household head education, female-headed households, unemployed household heads, and larger household sizes increased the likelihood of child exploitation. Moreover, children residing in districts with lower HLS scores had a higher chance of being exploited. These findings highlight the importance of considering both individual and regional contextual factors when addressing child exploitation. A two-level binary logistic regression model with random effects provides a better fit than the intercept-only model. Therefore, it is recommended to prioritize interventions for children without access to the PIP and those from household heads with low education levels. Furthermore, programs emphasizing the importance of education for children should be strengthened.
KARAKTERISTIK TENAGA KERJA INDONESIA MENJELANG ERA BONUS DEMOGRAFI Heryani, Heryani; Siagian, Tiodora Hadumaon
Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Vol 7 No 2 (2023): Vol. 7 No. 2, November 2023
Publisher : Badan Perencanaan Pembangunan, Riset dan Inovasi Daerah Kabupaten Sragen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32630/sukowati.v7i2.352

Abstract

Based on the results of the 2020 population census, Indonesia's population is 275 million people. As many as 62.28 percent are productive age. This research will study the relationship between the peak of the demographic dividend and workforce characteristics. Data from the Statistics of Indonesia will be analyzed descriptively related to the data presented in the tables and graphs. The productive age population in Indonesia is more than 90 percent of the working population. This population is a population whose highest education is elementary school graduates and below. This will threaten Indonesia as it approaches the peak of the demographic dividend, expected to occur in 2030. Not only low education workforce but also business fields in the agricultural sector with self-employed status. Characteristics of Indonesia's poor characterize this phenomenon. In Indonesia's poor population, more than 50 percent of education is completed in elementary school and below. In addition, the primary source of income comes from the agricultural sector. To overcome this, the solution is for those with primary education to be forced to continue their formal education. However, training and courses can be provided to enhance their skills. The government also needs to increase employment opportunities for the Indonesian population.
ANALISIS KEMISKINAN DIGITAL KABUPATEN/KOTA DI PROVINSI BANTEN DI MASA PANDEMI COVID-19 Futri, Siska; Siagian, Tiodora Hadumaon
Jurnal Kebijakan Pembangunan Daerah Vol 6 No 2 (2022): December 2022
Publisher : Badan Perencanaan Pembangunan Daerah Provinsi Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56945/jkpd.v6i2.210

Abstract

Pandemi Covid-19 yang melanda dunia sepanjang tahun 2020 telah mengubah berbagai aspek kehidupan, khususnya dalam penggunaan fasilitas Teknologi Informasi dan Komunikasi akibat berubahnya berbagai kegiatan manusia dari offline ke online. Namun ternyata masih terdapat penduduk yang hidup dengan sedikit atau bahkan tanpa akses ke teknologi (miskin digital). Penelitian ini bertujuan menghitung kemiskinan digital menurut Barrantes, sebaran dan keterkaitannya dengan kemiskinan ekonomi pada kabupaten/kota di Provinsi Banten pada masa pandemi Covid-19. Metode penelitian yang digunakkan adalah deskriptif dengan data bersumber dari Survei Sosial Ekonomi Nasional BPS pada bulan Maret tahun 2020 dan 2021. Data dianalisis menggunakan Indeks kemiskinan digital dan Indeks kemiskinan ekonomi, serta Quadran GIS. Hasil penelitian menunjukkan pada tahun 2021 angka kemiskinan digital kabupaten/kota di Provinsi Banten secara umum menurun dibandingkan tahun sebelumnya. Dua dari delapan kabupaten/ kota di Banten memiliki angka kemiskinan digital dan juga angka kemiskinan ekonomi yang tinggi, yaitu Kabupaten Pandeglang dan kabupaten Lebak. Untuk itu, pemerintah daerah provinsi Banten hendaknya dapat memprioritaskan perbaikan pada dua aspek tersebut di dua kabupaten ini.
Co-Authors Alfarizal, Ridson Apriliansyah, Apriliansyah Ariansyah, Setiawan Arif Hermawan, Arif Fitri, Muti Nurjannah Futri, Siska Hakim, Syifa Rahmawati Heryani, Heryani Kasim, Muhammad Faturahman Kurniawan, Novianto Budi Madina, Virginia Mardani, Shodaidah Ika Marpaung, Leandro Pandapotan Mufiedah, Maziyyatul Ramadhan, Syairilla Muthia Santika, Zukhrufiyah Mei Sofyan, Sabiq Thahar, Safira Fauziana Tusianti, Ema Wahyudi, Muhammad Rafidzaky Wardaya, Anton