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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
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Pola Migrasi dan Variabel yang Memengaruhinya di Provinsi Jawa Barat Fauziyah, Syifa; Wijaya, Yuliagnis Transver
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.v2024i1.2081

Abstract

Migration is one of the demographic components of population growth in a region. A problem phenomenon in population growth that occurs at this time is that the population is not evenly distributed and only concentrated in one region. The purpose of this study is to determine the distribution pattern of migrant population working in the formal sector between districts / cities in West Java Province and the factors that influence it. This study uses multiple linear regression analysis methods to determine what variables affect the occurrence of migration, both in-migration, out-migration, and between the two that occur between districts / cities in West Java Province. The variables that significantly affect the occurrence of out-migration are the population size variable and the proportion of higher education; the variables that affect the occurrence of in-migration are the Gross Regional Domestic Product value variable and the proportion of higher education; the variables that affect migration between in-migration and out-migration include the neighboring variable, the stock of lifetime migrants, the GRDP ratio, and the distance ratio of the capital to the Province.
Pemanfaatan Hasil Data Digital Elevation Model untuk Estimasi Produksi Pertambangan Pasir dan Batu Robiul Awaliah, Mesya Anggita; Marsisno, Waris
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.v2024i1.2093

Abstract

Sand and gravel (sirtu) are important materials in construction activities. Magelang Regency is a strategic area for sirtu mining with an abundant supply from Mount Merapi. Until now, data collection on sirtu mining still done manually through reporting from mining business owners. This research aims to estimate sirtu production data through the formation of Digital Elevation Model (DEM) data sourced from Sentinel-1 imagery using the Interferometric Synthetic Aperture Radar (InSAR) method. The DEM is processed using the cut and fill method to produce estimates of sirtu production. It is hoped that this research can be an alternative for collecting data on sirtu mining production in Magelang Regency. The research results show that the DEM obtained from Sentinel-1 imagery using the InSAR method has quite good quality so that the DEM can be used as a basis for calculating sirtu mining production estimates in Magelang Regency
Analisis Prevalensi Stunting Menggunakan Model Spasial Bayes dengan Conditional Autoregressive Hasibuan, Ardian Saputra; Nagari, Rizki; Nisa, Rifqi Aulan
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.v2024i1.2095

Abstract

Stunting is a growth disorder in children caused by chronic malnutrition and recurrent infections. According to SSGI, the stunting prevalence rate in Indonesia was 21.6% in 2022, decreasing from 27.7% in 2019. However, it remains far from 5% stunting target for Golden Indonesia 2045. This study aims to analyze the determinants of stunting prevalence based on socio-economic factors accommodating spatial aspect using Bayesian Spatial analysis with inference based on INLA (Integrated Nested Laplace Approximation). The Bayesian Spatial Model used is a conditional autoregressive that incorporates stunting prevalence rate as the response variable. The spatial modelling results indicate that the food security index, percentage of households with improved drinking water services, and per capita expenditure have significant impacts on the stunting prevalence rate. Spatial mapping reveals regional bonding affecting stunting prevalence rates and shows the vulnerability distribution of regencies and municipalities with stunting prevalence above the national rate.
Pendeteksian dan Determinan Overfishing di Indonesia: Penerapan Analisis Klaster dan Regresi Logistik Biner Johan, Muhammad Fazlan; Zareka, Andi Muh. Zulfadhil; Kesumawijaya, Anak Agung Istri Anggita; Kurniasari, Agustin; Maharani, Jessica; Putri, Nimas Ayu Eka
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.v2024i1.2096

Abstract

Overfishing causes a decline in fish stocks, imbalance in marine ecosystems, and economic losses for the fisheries sector. This study aims to obtain a model that is able to detect overfishing in various provinces in Indonesia using a combination of cluster analysis and logistic regression. The data used in this research is secondary data obtained from the Central Statistics Agency (BPS) and the Indonesian Ministry of Maritime Affairs and Fisheries (KKP) which includes information related to marine fish production in Indonesia in 2022. From the study conducted, it was found that the provincial data are classified into two clusters where the second cluster was classified as overfished provinces. Based on the analysis carried out, the best model for modeling overfishing is a logistic regression model with two predictor variables, which are exports and fish consumption rates. Thus, it is hoped that this research can serve as a guide for the government in formulating sustainable policies to reduce the number of overfishing in Indonesia in the following years.
Deteksi Sampah di Permukaan Sungai menggunakan Convolutional Neural Network dengan Algoritma YOLOv8 Hutabarat, Rizky Theofilus; Kurniawan, Robert
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.v2024i1.2099

Abstract

The increase in solid wastes floating on surface of rivers has become a big problem in the urban environment, such as floods and diseases. The goal of this research is to build an object detection model using Convolutional Neural Network (CNN) with YOLOv8 (You Only Look Once v8) algorithm, and to implement that model to detect floating wastes on the surface of Ciliwung River. The model used in this research is YOLOv8, because of its high speed and accuracy. The data used are obtained from online sources (Google Images and YouTube), and directly from Ciliwung River obtained with smartphone camera. The best epoch is the 177th epoch. The Precision value is 84.02%, the Recall value is 91.03%, the Accuracy value is 77.6%, and the F1-Score is 87.38%. The conclusion is that the model built with YOLOv8 algorithm can be used to detect floating wastes on the surface of Ciliwung River.
Pengaruh Aksesibilitas dan Kesehatan Masyarakat terhadap Ketahanan Pangan di Papua dan Papua Barat Tahun 2022 Eliezer, Wisly Ryan
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.v2024i1.2100

Abstract

The need for food is crucial for human life, no wonder it has become one of the common development goals by countries in the world related to ending hunger, obtaining food security, improving the quality of nutrition and proposing sustainable agricultural systems. Indonesia has problems in terms of food security, especially in Papua and West Papua with the lowest food security index value in 2022, even though these regions have extensive agricultural potential. This study aims to see an overview of the level of food security in Papua and West Papua and see the variables that affect it. The data used is data from 42 districts/cities in Papua and West Papua provinces sourced from the Central Bureau of Statistics and the Food Security Agency. The analysis method used is multiple linear regression. It was found that 25 districts/cities were still categorized as food insecure. Purchasing power and the level of public health are key factors to improve food security in Papua and West Papua.
Peramalan Produksi Minyak dan Gas Bumi di Indonesia Gampar, Yohanes Apriyano; Agustina, Neli
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.v2024i1.2101

Abstract

The oil and gas sector remains the primary source of energy in Indonesia. However, the industry faces a significant challenge in declining production year after year. This situation necessitates the implementation of appropriate policies and decisions in oil and gas management to achieve energy security and self-sufficiency through forecasted data. By utilizing forecasting results, it is possible to estimate the realization of the RPJMN targets for oil and gas production for 2023-2024. This study aims to analyze the general trend of Indonesia's oil and gas production from the first quarter of 2007 to the second quarter of 2023, determine the best forecasting model by comparing Holt’s Double Exponential Smoothing and ARIMA methods, and forecast oil and gas production from the third quarter of 2023 to the fourth quarter of 2024 using the best method. The study results indicate a decline in oil and gas production, with an average growth rate of -0.69 percent and -0.48 percent, respectively. Holt's Double Exponential Smoothing is the best method for forecasting oil production, while ARIMA is more suitable for forecasting gas production. The forecast results show a decline in oil production, with an average production of 52,763.19 thousand barrels, and an increase in gas production, with an average production of 493,306.05 MMscf over the next six quarters. This indicates that the oil and gas production targets set by the RPJMN and the Directorate General of Oil and Gas for 2023-2024 have not yet been achieved.
Analisis Keamanan Aplikasi Berbasis Web di Lingkungan BPS RI Pandudinata, Maulana; Ridho, Farid
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.v2024i1.2109

Abstract

Security is principal factor that matters in Web Applications. Penetration Testing now become the standard for security testing of applications before released to the public. Security analysis of the Functional Position Information System (JAFUNG) web application from BPS RI is conducted because BPS RI has important applications that assist in implementing statistical business processes. Therefore, conducting Grey-Box Penetration Testing is important to assess how resistant that application is. With PTES (Penetration Testing Execution Standard) testing method 2014 version for procedures and OWASP Risk Rating Methodology 2021 version for vulnerability assessment, counting attack scenarios by the BSSN Top 10 Vulnerabilities. Hopefully after conducting security testing, systematic analysis and assessment of vulnerabilities for the application will be obtained, counting a vulnerability category rating that accurately reflects the actual conditions, and hereafter, this research can be a reference for BPS in testing the security of applications to ensure the safety of statistical data.
Penerapan Analisis Klaster dan Prediksi Indeks Pembangunan Manusia untuk Mengevaluasi Kualitas Hidup Manusia dalam Pembangunan Nasional Ismail, Ghaffar
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.v2024i1.2111

Abstract

This study evaluates the development of human quality through cluster analysis based on the HDI to achieve the vision of "Golden Indonesia 2045". The purpose of this research is to classify of regencies/cities based on health, education, and standard of living indicators, so that these regions can effectively address their deficient indicators. Using various machine learning methods, AGNES was selected as the best method. The regencies/cities were grouped into four clusters: low, medium, high, and very high. The results show that 244 regencies/cities are in the medium cluster, 188 in the high cluster, 68 in the very high cluster, and 14 in the low cluster. Regencies/cities with low and medium HDI require improvement all aspects, while the high cluster needs to focus on education. Strategic policies in health, education, and decent living standards are essential to enhance quality of life and achieve equitable national development.
Vulnerable Worker di Provinsi Jawa Timur Rahman, Ahmad Aulia; 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.v2024i1.2113

Abstract

Vulnerable employment has negative impacts on individuals (vulnerable workers) and regions. In 2022, there was an increase in the vulnerable employment rate in Indonesia. By province, East Java is the province with the largest number of vulnerable workers in 2022. This could lead to an increase in poverty and economic stability in East Java and other provinces in Indonesia. This study aims to determine the picture of vulnerable workers in East Java and the variables that influence their trends. The variables used in this study consist of variables derived from individual and regional characteristics sourced from Sakernas August 2022 and the East Java Gross Regional Domestic Product publication. The statistical method used is binary logistic multilevel regression to analyze the effect of variables at the individual level and regional level on the status of vulnerable workers. The results of this study show that the variables of gender, age, education level, marital status, disability status, skills training, formal work experience, manufacturing sector contribution, and agricultural sector contribution affect the tendency of the labor force to become vulnerable workers.

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