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Faktor-Faktor yang Memengaruhi Foerign Direct Investment (FDI) di Enam Koridor Ekonomi Indonesia: Market Seeking atau Resource Seeking? Iriani Trisna Rahayu; Ernawati Pasaribu
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 9 No 1 (2017): Journal of Statistical Application and Computational Statistics
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

The economic development of a country depends on the amount of foreign direct investment (FDI), including in the Indonesian six economic corridors. The huge gaps of conditions in economic corridors are expected to differences infactors affecting the FDI-inflow into the corridors. This study uses a panel data regression to analyze factors behind the FDI-inflow in each economic corridor and to determine the FDI characteristic in each economic corridor. It shows that the proportion of government capital expenditure, number of highly-educated labor force, trade openness, and the proportion of oil and mineral export affect the FDI-inflow only in some economic corridors. Furthermore, it indicates that, while market seeking FDI occurred in all Indonesian economic corridors, resource seeking FDI was only found in Sulawesi, Maluku and Papua economic corridors.

againaba Daya Saing Industri Life Sciences di Indonesia Ernawati Pasaribu; Retno Indrawati
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

Indonesia is the South East Asia’s largest economy and has a substantial and increasingly inspirational middle class of over 20 million. Indonesia has become an attractive market due to her strongly growing consumer market, especially the middle income segment. The high number of population also indicates the existing potential pool of labour. Life Sciences (LS) industry is widely recognised as the new wave of knowledge-based economy. This study identifies relative position of Indonesia in terms of foreign direct investment (FDI) in LS industry and competitiveness of the LS industry in Indonesia compared with other countries. Based on LS sector, Indonesia has to compete mainly with Portugal, Turkey, Saudi Arabia and Nigeria, while based on LS activities, Argentina and Bulgaria are the main competitors. It also reveals that FDI inflow to LS industry in Indonesia is influenced mainly by inflation and return on investment.

ANALISIS SPASIAL DETERMINAN PERTUMBUHAN INKLUSIF KABUPATEN/KOTA DI PROVINSI JAWA TENGAH TAHUN 2017 Tju Ji Long; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019
Publisher : Politeknik Statistika STIS

The high economic growth of Central Java but still followed by high rates of poverty and uneven distribution of income indicate that the economic growth of Central Java has not been of high quality. To obtain quality economic growth, a concept of inclusive growth is needed. This study aims to measure and analyze the determinants of inclusive growth in the districts/cities in Central Java in 2017 with a spatial analysis approach. The results of the study show that there are three regions that have low inclusive growth, 15 regions with moderate inclusive growth, and 17 regions with high inclusive growth. In addition, the results of spatial regression shows that the PMTB and government expenditure on social protection functions have a positive and significant effect on inclusive growth. UMK has a negative and significant effect on inclusive growth. Meanwhile, inflation and government spending on the education function have a negative and insignificant effect on inclusive growth. Futhermore, there are spatial linkages in inclusive growth of the districts/cities in Central Java. Thus, inclusive growth in certain districts/cities will affect the inclusive growth of the districts/cities around them.

PEMBENTUKAN BIGGI DALAM MENGUKUR PERTUMBUHAN INKLUSIF HIJAU Daniel Mutiha Liderson; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019
Publisher : Politeknik Statistika STIS

Kualitas pembangunan suatu negara pada umumnya hanya diukur melalui pertumbuhan ekonomi, padahal pertumbuhan ekonomi yang diukur melalui PDB tidak mampu mengakomodasi kesejahteraan sosial dan kualitas lingkungan yang juga merupakan tujuan dari pembangunan. Pertumbuhan inklusif hijau merupakan solusi yang mampu menggambarkan kualitas pembangunan secara komprehensif, tidak hanya mencakup dimensi ekonomi, tetapi juga dimensi sosial dan dimensi lingkungan. Penelitian ini bertujuan untuk membentuk suatu indeks untuk mengukur tingkat pertumbuhan inklusif hijau yang disebut Balanced Inclusive Green Growth Index (BIGGI) dengan menggunakan metode analisis faktor dan menerapkan kerangka kerja serta metodologi yang dikembangkan oleh Asian Development Bank (2018). Hasil penelitian menunjukkan bahwa Provinsi Jawa Timur, Jawa Tengah, dan Kalimantan Timur adalah tiga provinsi dengan pertumbuhan inklusif hijau tertinggi, sedangkan Provinsi Bengkulu, Sulawesi Barat, dan Papua adalah tiga provinsi dengan pertumbuhan inklusif hijau terendah. Secara umum, pertumbuhan inklusif hijau provinsi-provinsi di Indonesia berada pada kategori sedang. Dengan menggunakan analisis kuadran antara BIGGI dan pertumbuhan ekonomi, 16 dari 34 provinsi di Indonesia mengalami pertumbuhan ekonomi yang tinggi namun disertai pertumbuhan inklusif hijau yang rendah. Hal ini mengindikasikan bahwa sebagian besar kegiatan ekonomi di Indonesia tidak inklusif, tidak hijau, serta tidak seimbang. Selain itu, terdapat keterkaitan spasial pada pertumbuhan inklusif hijau provinsi-provinsi di Indonesia yang berarti bahwa tingkat pertumbuhan inklusif hijau di suatu provinsi memengaruhi dan dipengaruhi oleh capaian provinsi-provinsi tetangganya.

KONVERGENSI UPAH MINIMUM KABUPATEN/KOTA DI PULAU JAWA TAHUN 2014-2018 Insan Riski Dwi Perdana; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

Pulau Jawa merupakan pusat perekonomian di Indonesia dengan share terhadap PDB sebesar 59% pada tahun 2018. Tingginya produksi yang dihasilkan seharusnya berdampak pada tingginya upah yang ditetapkan. Akan tetapi, masih banyak daerah di Pulau Jawa yang menetapkan upah minimum dibawah rata-rata upah minimum nasional. Selain itu, sebagian besar upah minimum yang ditetapkan di Pulau Jawa lebih rendah dibandingkan upah minimum yang ditetapkan pada daerah-daerah di luar Pulau Jawa. Sehingga, peningkatan UMK diperlukan untuk menjamin pekerja dapat memenuhi kebutuhan hidup secara layak dan tercapainya konvergensi. Konvergensi upah diartikan sebagai kondisi dimana daerah dengan upah yang rendah dapat tumbuh dengan cepat sehingga dapat mengurangi ketimpangan. Penelitian ini bertujuan untuk mengetahui gambaran upah minimum, menganalisis konvergensi, dan mengetahui faktor yang berpengaruh pada pertumbuhan UMK di setiap daerah. Metode yang digunakan adalah Geographically Weighted Panel Regression (GWR-Panel). Hasil penelitian menggunakan GWR-Panel menemukan bahwa terjadi konvergensi UMK pada 68 kabupaten/kota di Pulau Jawa dan 51 daerah lainnya tidak konvergen. Kecepatan konvergensi tiap tahun bervariasi pada setiap daerah antara 32% hingga 103%. Daerah dengan kecepatan konvergensi yang tinggi berkelompok pada kabupaten/kota di Provinsi Jawa Tengah, sedangkan kabupaten/kota di Provinsi DKI Jakarta tidak ada yang mencapai konvergensi. Selanjutnya, terdapat pengelompokan daerah berdasarkan variabel yang mempengaruhi pertumbuhan UMK.

ANALISIS CAPAIAN BELAJAR SISWA SMAN DI INDONESIA TAHUN 2019 DENGAN PEMODELAN MIXED GEOGRAPHICALLY WEIGHTED REGRESSION Febrianto Nainggolan; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

National student learning outcomes so far have been measured by the results of the National Examination (NE). The distribution of NE scores for high school students in Indonesia tends to be uneven, with high learning outcomes only on the island of Java. Ironically, regions in Eastern Indonesia have a very low average NE score. The interesting thing is that regions with the same value categories tend to be close together and indicate a regional effect on learning outcomes in Indonesia. This study analyzes the characteristics and factors that influence the learning achievement of district/city high school students in Indonesia in 2019 using the mixed Geographically Weighted Analysis (mixed GWR) model approach. The results found that there were effects of spatial autocorrelation and spatial heterogeneity in the modeling of district / city level high school NE scores and the factors that influenced them in Indonesia in 2019. Analysis using the mixed GWR method produced variable conditions of classroom buildings, ratio of students per class, and Teacher competency Test scores influences learning outcomes locally in each district/city. Meanwhile, per capita GRDP has a global effect on learning outcomes. Suggestions are given to improve classroom buildings, a more equitable distribution of students per class and the distribution of high-ability teachers. In addition, it is necessary to hold a test form that can better describe the quality of education in Indonesia, in lieu of the National Examination.

PEMBENTUKAN INDEKS MIDDLE INCOME TRAP DAN FAKTOR-FAKTOR YANG MEMENGARUHINYA TAHUN 2015-2018 Zaradia Permatasari; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

Indonesia experiences demographic dividend throughout 2017-2030. However, the momentum of demographic dividend experienced by Indonesia is accompanied by the development of the 4.0 industrial revolution. The demand for labor is decreasing due to the existence of artificial intelligence and advanced robotics which replace human labor. So, the risk of unemployment becomes higher. This has aggravated the situation in which Indonesia is trapped in a middle-income trap. Whereas other countries can take advantage of demographic dividend so as to encourage the economy. This study reveals the existence of middle income trap at the provincial level based on their economic capacity by forming a middle income trap index. In addition, this study statistically tests whether this high unemployment rate due to demographic devidend causes Indonesia not be able to escape the middle income trap. During 2015 to 2018, there are 20 provinces that fall into MIT and 14 provinces that did not. The test results show that the adult unemployment rate and gini ratio have positive and significant effects on the MIT index, while the formation of gross fixed capital, the gross enrollment rate of universities, and the growth of gross value added in the manufacturing sector have negative and significant effects on the MIT index.

Analisis Spasial Kasus COVID-19 sampai dengan PPKM Jilid Dua Arrazi Rahadiyan; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2021 No 1 (2021): Seminar Nasional Official Statistics 2021
Publisher : Politeknik Statistika STIS

The COVID-19 pandemic is the spread of a disease outbreak infectious COVID-19 caused by infection with SARS-CoV-2 in all countries including Indonesia. As of March 31, 2020, Government Regulation Number 21 of 2020 about Large-Scale Social Restrictions to limit the mobility of people and goods. Governments in each region as well establish quarantine policies in several areas on the islands of Java and Bali based on the Instruction of the Minister of Home Affairs Number 1 of 2021 concerning the Enforcement of Limitations on Community Activities (ELCA) phase 1 and phase 2. This study aims to determine the general description, identify spatial diversity, and analyze factors that influence spatial characteristics of cases COVID-19 in Java and Bali until the period ELCA Phase 2 with Geographically Weighted Negative Binomial Regression. The results of the analysis show that there is a spatial diversity of COVID-19 cases in Java and Bali until the ELCA Phase 2. Density of population that significant effect in all districts/cities in Java, meanwhile the ratio of health workers per 1000 population, air quality index, and health spending has a significant effect only in a few districts/cities on the island Java and Bali.

Determinan Pengangguran Lulusan SMK Provinsi Sulawesi Utara Sebelum dan Saat Pandemi Covid-19 Tengku Mashitah Crisanty; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Indonesia is facing a demographic bonus phenomenon and the Covid-19 pandemic. As a result of the Covid-19 Pandemic, to reduce the spread of the Covid-19 virus, the government imposed PSBB which had an impact on reducing employees (PHK). One way to overcome unemployment is the implementation of vocational revitalization. However, the impact of the revitalization of SMK has not been seen as evidenced by the TPT of SMK graduates who are still the largest contributor to Indonesian unemployment in 2018 to 2021. North Sulawesi is one of the provinces that has a high TPT of SMK graduates. This study uses data from the August 2019 and 2021 National Labor Force Survey (Sakernas). The analytical method used is binary logistic regression. The results showed that in 2019 the independent variables that had a significant effect on unemployment status were marital status, field of expertise and year of graduation. Meanwhile, in 2021, the independent variables that have a significant effect on unemployment status are job training, marital status, year of graduation and area of residence.

Analisis Spasial Pertumbuhan Inklusif Kabupaten/Kota Di Sulawesi Tengah Tahun 2015-2020 Fadhel Imam Haichal Tanjung; Ernawati Pasaribu
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Central Sulawesi province is the province which has the third highest economic growth in Indonesia during 2015-2020. However, high economic growth is not in line with solving problems such as the high percentage of the poor, income inequality, and open unemployment. Based on this, indicators are needed that can be a measure of the success of economic development through inclusive growth. Therefore, this study aims to describe the level of inclusive growth using the inclusive index (II) by Ramos, Ranieri, and Lammens and to find out the factors that influence it in districts/cities in Central Sulawesi. In addition, this study also identifies the spatial interrelationships of inclusive growth. The results show that inclusive growth has increased in the 2015-2020 period. Based on the spatial panel method, with spatial lag fixed effect, obtained positive spatial autocorrelation results. There is a positive and significant influence between Road Infrastructure, Government spending on social protection functions, Processing Industry and Electricity Access on inclusive growth. Government spending on education and access to clean water has a negative and significant impact on inclusive growth

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