cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Rani Nooraeni
Contact Email
raninoor@stis.ac.id
Phone
+6221-8191437
Journal Mail Official
semnas@stis.ac.id
Editorial Address
https://prosiding.stis.ac.id/index.php/semnasoffstat/about/contact
Location
Kota adm. jakarta timur,
Dki jakarta
INDONESIA
Prosiding Seminar Nasional Official Statistics
Published by Politeknik Statistika STIS
ISSN : 27721970     EISSN : 27721970     DOI : https://doi.org/10.34123/semnasoffstat.v2022i1
Core Subject : Economy, Humanities, Science, Social,
Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences
prosiding seminar ini bertujuan untuk menghasilkan berbagai pemikiran solutif, inovatif, dan adaptif terkait isu, strategi, dan metode yang memanfaatkan official statistics
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 729 Documents
 61   62   63   64   65 
Analisis Multilevel pada NEET di Wilayah Perdesaan Indonesia Tahun 2022 Jessica, Theresia Intan; Arcana, I Made
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.v2024i1.2170

Abstract

The population aged 15-24 years has played an important role in achieving Indonesia Emas 2045 and needs to be improved through education, employment, and training. Not in Education, Employment, or Training (NEET) is an indicator that counts those who are not in education, employment or training. In the last 4 years, the highest percentage of NEETs was in rural areas, especially in 2022. This research aims to analyze the variables that affect NEETs using multilevel binary logistic regression seen from individual and household factors. The results of the study showed that 23.6 percent of the 15-24 year-olds in the Indonesian countryside are NEETs. Individual factors that influence are gender, disability, age, marital status, education, training experience, and work/employment experience. The education of the head of the household, the working status of the household, and the number of household members are the variables that affect the NEET based on household factors. It is hoped that this research will reduce the percentage of NEETs in the Indonesian countryside and improve the quality of the population towards Indonesia Emas 2045.
Pengaruh Ekspor Sektor Industri Pengolahan terhadap PDB, Tingkat Pengangguran dan Investasi Asing di Indonesia Periode 2000 – 2022 Laksmana Putri, Calivi Kezia; Nasrudin, Nasrudin
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.v2024i1.2171

Abstract

The manufacturing industry is one of the sectors that has the largest contribution to Gross Domestic Product (GDP) in Indonesia which absorbs a lot of labor. However, in 2022 the GDP of the manufacturing industry and the Open Unemployment Rate (TPT) have not yet reached the RPJMN target, even though Foreign Investment continues to increase. One of the things that is thought to affect these conditions is export performance. This study aims to analyze the effect of processing exports on processing industry GDP, unemployment, and foreign investment simultaneously. The data used is Indonesian annual data for the period 2000-2022. This study uses a simultaneous equation model with the Two Stage Least Square (2SLS) estimation method. The results obtained are that exports have an influence on manufacturing GDP directly and simultaneously on the level of unemployment and foreign investment. Based on the simulation, it is estimated that the RPJMN target for unemployment rate and GDP of manufacturing industry can be achieved if the export of manufacturing industry can increase up to 25 percent of the average observation period
Pengaruh Kepemilikan Fasilitas Telekomunikasi dan Akses Internet terhadap Capaian Proses Pendidikan di Indonesia Rahmadani, Alif Hidayah Nur; Hutabarat, Josephin Pirdinansius; Prakoso, Nurihisha Nadya Putri; Kartiasih, Fitri
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.v2024i1.2172

Abstract

Fulfilling access to education is one of the Sustainable Development Goals targets to ensure quality education. In the digital era, telecommunication facility ownership and internet access are key to enhancing educational outcomes. This study aims to analyze telecommunication facility ownership contribution and internet access to educational outcomes in Indonesia. The research method used descriptive analysis and inferential analysis with multiple linear regression to analyze the effect of telecommunication facility ownership and internet access on educational outcomes. The results showed that the percentage of computer use and the percentage of cellular phone use had a significant effect on increasing the mean years of schooling. Meanwhile, the variable Percentage of Internet Use has a significant effect on reducing Mean Years of Schooling. The Internet is often used to access social media, online games and YouTube and increase the phenomenon of homeshcooling. The government should provide socialization and education on internet usage and improve telecommunication facilities in schools to improve student learning methods.
Analisis Spasial Perkawinan Usia Anak pada Kabupaten/Kota di Pulau Sulawesi Tahun 2022 Yahya, Muhammad Gozali; Sitorus, Jeffry Raja Hamonangan
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.v2024i1.2173

Abstract

Indonesia has an alarming rate of child marriage. The acceleration of the elimination of child marriage cannot be delayed because it can threaten the future of the younger generation. Child marriage is influenced by regional factors as evidenced by the districts/cities on Sulawesi Island having a percentage of child marriage above the national rate. The purpose of this study is to determine the general description of the percentage of child marriage and factors that are thought to influence child marriage in districts / cities on Sulawesi Island in 2022. The research method used is Spatial Autoregressive (SAR). The results of the analysis show that the percentage of child marriage in districts/cities on Sulawesi Island has a spatial pattern. Then the variables of Average Years of Schooling (RLS) of women, Life Expectancy (UHH), average Family Welfare Empowerment (PKK) per village, proportion of villages that have Elementary School (SD) and Junior High School (SMP), percentage of rural areas, and adjusted expenditure per capita of women have a significant effect on the percentage of child marriage in districts/cities in Sulawesi Island.
Manfaat Algoritma Djikstra dalam Pemetaan Granular Jarak Sekolah dari Pemukiman Penduduk Saadi, Terry Devara Tri
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.v2024i1.2178

Abstract

The Indonesia Emas 2024 Vision emphasizes the importance of educational development in improving future human resources, particularly for the productive-age population in 2045. Enhancing access and participation through equitable education distribution and removing geographic barriers has become a primary focus in achieving educational targets. This study aims to explore the potential of utilizing Dijkstra’s algorithm for granular mapping of school distances from residential areas. The analysis involved calculating school distances on a 1 km populated grid in West Nusa Tenggara, using 2019 infrastructure data, residential tagging, and road graphs from OpenStreetMap. The results demonstrate the potential of the Dijkstra algorithm in granular mapping of school distances and reveal that 21.84% of the population in the area must travel more than 5 km to access senior high school education, and 8.11% for junior high school. This study also discusses the limitations and drawbacks of this approach and explores potential improvements for identifying areas that face challenges in accessing educational facilities.
Potensi Pemanfaatan Machine Learning dan Transfer Learning untuk Klasifikasi Baku Pekerjaan Dwicahayaniawan, Agnes Septi; Saadi, Terry Devara Tri
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.v2024i1.2180

Abstract

Monitoring the state of labor data in Indonesia involves standardized classification to ensure uniformity. The coding process relies on the knowledge of personnel, which often leads to issues such as potential differences in understanding and interpretation among individuals, resulting in inconsistencies in the standardized classification coding outcomes. This study aims to explore the potential of Machine Learning in classifying the Indonesia Business Field Classification (KBLI) and the Indonesian Standard Classification of Occupations (KBJI). Models were developed and evaluated to classify KBLI and KBJI based on open-ended questions about the job, the output produced, and the field of work from respondents' answers collected through the National Labor Force Survey (Sakernas). The results show that although the performance of the IndoBERT method is slightly superior with accuracy is 0,76 for KBLI and 0,65 for KBJI. This advantage is not significant given the higher computational load and longer training time compared to machine learning.
Dampak Bantuan Subsidi Upah Terhadap Kemiskinan di Indonesia Tahun 2023 Pelodu, I Gede Ariasa; Wahyuni, Ribut Nurul Tri
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.v2024i1.2181

Abstract

The COVID-19 pandemic has made poverty alleviation programs in Indonesia less effective. Therefore, the government issued an additional policy, namely the Wage Subsidy Assistance (BSU). This study aims to determine the general picture of BSU recipients and analyze the impact of BSU on poverty in Indonesia using the Propensity Score Matching (PSM) method. This method is used because BSU recipient households must meet certain requirements (not random). The observation unit is individuals aged 15 years and over who meet the criteria for BSU recipients. This study uses the 2023 National Socio-Economic Survey data from BPS-Statistics Indonesia. The results of the study show that the majority of BSU recipients are not poor people. However, the chances of individuals who participate in the BSU program being poor are lower than individuals who do not participate in the BSU program. This shows that the BSU program can be one solution to reducing poverty in Indonesia. Recipients of the BSU policy also need to be evaluated so that they are right on target.
Nowcasting Produk Domestik Bruto Atas Dasar Harga Konstan Triwulanan Indonesia Kurniawan, Taufiq Agung; Choir, Achmad Syahrul
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.v2024i1.2185

Abstract

As a component of macroeconomic assumptions, economic growth is used in the state budget drafting. However, the nominal GDP data used to calculate the economic growth value has a release lag in the first week of the second month after the quarter ends. This research aims to find the best nowcasting model for MIDAS regression, RFR, LightGBM, SVR, MLP, and ensemble methods. Then, based on the best model, the nominal GDP value in the 2023 fourth quarter and the 2024 first quarter are predicted. Overall, the MLP model with variable selection using SHAP values has the best evaluation indicators, therefore this model is used to predict the nominal GDP in both quarters. Using the MLP model, the predicted value of nominal GDP in both quarters is quite accurate when compared to nominal GDP data that have been released by BPS-Statistics Indonesia.
Analisis Clustering Menggunakan Metode K-Means untuk Mengelompokkan Kabupaten/Kota di Indonesia berdasarkan UnsurUnsur Pembangun Literasi Masyarakat (UPLM) Jelita, Mutia
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.v2024i1.2188

Abstract

The government needs to identify which districts/cities require more guidance in the library sector by utilizing the data obtained. This study aims to conduct clustering analysis using the K-Means method to categorize districts/cities in Indonesia based on the Elements of Community Literacy Development (UPLM) data in 2023. The Elbow method is applied to determine the optimal number of clusters. The results of the study reveal four clusters: Cluster I consists of 62 districts/cities with characteristics of having four high-value UPLMs; Cluster II includes 84 districts/cities with no high-value UPLMs; Cluster III encompasses 222 districts/cities with one high-value UPLM; and Cluster IV includes 146 districts/cities with two highvalue UPLMs. Based on these clusters, the government, particularly the National Library of Indonesia, can focus on providing more targeted guidance, especially in Cluster II, which includes districts like Bener Meriah, Indragiri Hilir, Bogor, Sikka, and Yahukimo.
Club Convergence dalam Paradigma Kemiskinan di Indonesia Tahun 2007 - 2022 Syahadati, Amelia; Hartania, Made Sukma
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.v2024i1.2195

Abstract

Following the objectives of the Sustainable Development Goals (SDGs), poverty alleviation requires a trend of national poverty convergence to zero. This study aims to look at the convergence pattern of poverty in Indonesia's provinces and the factors that influence it. The research results show that there is no absolute convergence in grouping according to the percentage of poor people, the depth and severity of poverty index and the tendency towards club convergence. The data processing results related to the formation of group convergence noted the formation of seven groups for the percentage of poor people and the poverty depth index and two groups for the poverty severity index. Testing the ordered logit model for each group shows the significance of the influence of the initial and previous conditions of the Gini ratio, per capita expenditure and minimum cost for eliminating poverty on the formation of each convergence group.

Page 63 of 73 | Total Record : 729

 61   62   63   64   65 

Filter by Year

2019 2025


Reset
Filter By Issues
All Issue Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025 Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024 Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 Vol 2021 No 1 (2021): Seminar Nasional Official Statistics 2021 Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020 Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019