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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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Optimasi Prediksi Jumlah Wisatawan Nusantara ke Provinsi Bali Melalui Big Data Analytics dengan Integrasi Google Trends dan Tingkat Penghunian Kamar Hotel Prayoga, Suhendra Widi; Wijayanto, Arie Wahyu
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.v2024i1.2114

Abstract

The tourism sector plays an important role in the Indonesian economy. Bali, as a major tourist destination, attracts a large number of domestic tourists, which has a significant impact on the local economy. However, providing accurate and real time data remains a challenge. This data limitation makes it difficult to effectively monitor tourism conditions. Therefore, this research optimises the prediction of the number of domestic tourists to Bali using hotel room occupancy rate and Google Trends index. Real-time hotel availability and search interest play an important role in this prediction. The application of big data analytics allows the analysis of large amounts of data quickly and accurately. The results show that the best model is Support Vector Regression with Mean Absolute Percentage Error, Root Mean Square Error, and Mean Absolute Error of 14.8366, 94.5575, and 77.1152, respectively. This prediction is expected to help stakeholders monitor the condition of Bali tourism.
Peranan dan Analisis Faktor Produksi Subsektor Bahan Galian Golongan C di Indonesia: Estimasi Regresi Panel Data Makro Anggraini, I Gusti Ayu Puspita; Wahyuni, Krismanti 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.v2024i1.2115

Abstract

The production results of the mining and other quarrying subsectors are often called class C excavations and are mostly used by other sectors as raw materials. The importance of class C excavation for other sectors makes it necessary to increase production output. Production results can be increased by using a combination of inputs that can be seen with the production function. Therefore, this research aims to look at the role and potential of class C minerals, analyze the general description of production and production functions and analyze the stats that influence output. The analytical method used is the panel data regression method with the SUR approach. The research results show that there are 18 provinces with mining and other quarrying subsectors classified as basic or superior. Production output and production factors appear to fluctuate. Variables that influence output were analyzed using the SUR method panel data regression model and it was found that labor, capital and technology had a positive and significant effect on production results, while fuel had a negative and significant effect.
Pembentukan Portofolio Saham Berdasarkan Klastering K-Means dengan Fitur Tren Berkelanjutan Firmansyah, Hilmi; Rosadi, Dedi
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.v2024i1.2118

Abstract

Investors aim to reduce risk and increase returns with an optimal portfolio. However, several challenges arise in portfolio construction. First, selecting assets can be difficult when there are many options, as traditional portfolio theories like risk parity and Markowitz theory only calculate optimal weights but do not automatically select assets. Second, these theories focus on covariances between stocks and overlook market data. Third, while the Sharpe ratio is used to evaluate investment performance, it does not account for risk when stock prices decline. To address these issues, this paper proposes a new approach to portfolio construction that focuses on sustainable trends. The k-means clustering technique is used to group assets, categorize them based on their characteristics, and calculate the Sharpe ratio to minimize the risk of price drops. This method also combines different approaches, including equal weighting, inverse volatility, risk parity, and Markowitz portfolio theory to optimize the portfolio.
Pembentukan Indeks Emisi Gas Rumah Kaca dan Strategi Menuju Net Zero Emission Kabupaten/Kota di Pulau Jawa dalam Mendukung Indonesia Emas 2045 Kautsar, Syahrizal; Ridwansyah, Rizki Riza; Priscilla, Nindia
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.v2024i1.2119

Abstract

Net zero emissions is one of the visions that Indonesia wants to achieve in the RPJPN 2025-2045. This is done to prevent global warming due to increased concentrations of greenhouse gases. In 2023, 5 out of 6 provinces on the island of Java have the lowest Air Quality Index, which indicates the existence of greenhouse gas problems on the island of Java. This research aims to form a greenhouse gas emissions index with more complex forming indicators using factor analysis and then connecting it with socio-economic indicators using linear regression analysis. This research uses data from districts/cities on the island of Java in 2023 sourced from Sentinel-5P satellite imagery, MERRA-2, and BPS. The research results show that 15 cities have high emissions, 66 cities have medium emissions, and 38 cities have low emissions. In addition, per capita expenditure, population density, and industrial sector share can increase greenhouse gas emissions, while average years of schooling can reduce greenhouse gas emissions.
Pemanfaatan Data Citra Satelit Multi Sumber dalam Analisis Spasial Jumlah Kasus Demam Berdarah Dengue (DBD) di Pulau Jawa Tahun 2022 Magfirah, Deanty Fatihatul; Pramana, Setia
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.v2024i1.2120

Abstract

Dengue Hemorrhagic Fever (DHF) is one of the world's dangerous infectious diseases, especially in tropical areas, such as Indonesia. The spread of dengue virus is generally caused by an environment that supports the development of DHF vectors, including temperature, rainfall, humidity, surface water, population density, and urbanization. The purpose of this study was to obtain environmental factors that significantly influence the number of DHF cases in Java and to group districts/cities according to the same characteristics by utilizing Sentinel-2, Sentinel-5P, Landsat-8 and CHIRPS satellite imagery. Descriptive analysis and inferential analysis were carried out with Mixed Geographically Weighted Regression (MGWR) spatial modeling for spatial regression analysis of the characteristics of each region. Environmental factors obtained from the analysis results describe each characteristic of the district/city area according to their respective local conditions and six groups are formed with the same regional characteristics and are located close to each other.
Pengaruh Pendidikan dan Pertumbuhan Ekonomi Terhadap Ketimpangan Pendapatan di Indonesia dengan Akses Energi Sebagai Variabel Moderasi: Moderated Regression Analysis Wahyuni, Ribut Nurul Tri; Utami, Tarisha Althaf
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.v2024i1.2122

Abstract

Every country, including Indonesia, persistently faces the issue of income disparity. Indonesia's gini ratio in 2022, a measure of income inequality, reached 0.384. We categorize this value as moderate and require efforts to decrease it. One of these efforts is to improve energy access. When combined with other factors, energy access can reduce economic inequality. This study seeks to examine the impact of the interaction between energy access, economic growth, and average years of schooling on income inequality in 34 Indonesian provinces from 2015 to 2022. The study will use moderated regression analysis. According to the research findings, increasing energy availability can mitigate the positive effects of economic growth and average years of schooling on income disparity. Consequently, it is advisable to integrate strategies that foster economic expansion, prolong the average duration of education, and ensure a fair allocation of energy infrastructure, especially in underdeveloped areas. Thus, income disparities will decline.
Forecasting Jumlah Penumpang Pesawat Yogyakarta International Airport dengan Big Data Google Trends dan Variabel Makroekonomi untuk Mendukung Official Statistics Chisan, Innas Khoirun; Wijayanto, Arie Wahyu
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.v2024i1.2123

Abstract

Aviation is an important element to support human connectivity and mobility so it is important to carry out an analysis of the number of airplane passengers. BPS releases data on the number of airplane passengers with a lag of around thirty days. In addition, the use of search engines is increasingly being used nowadays. This research aims to predict the number of Yogyakarta International Airport (YIA) airplane passengers in 2024 using Google Trends and macroeconomic data. To carry out this forecast, the SARIMA and SARIMAX models will be compared with several combinations of external variables. The research results show that the use of Google Trends Index variables and macroeconomics can increase forecasting accuracy. The best model selected was SARIMAX with external variables Google Trends Index and macroeconomics. The forecast results for the number of airplane passengers in January 2024 are 332 thousand passengers and in February 2024 there are 292 thousand passengers. Accurate predictions can help flight planning so that this research can play a role in improving the quality of official statistics in the field of air transportation.
Peramalan Tinggi Muka Air Menggunakan Long-Short Term Memory dengan Mekanisme Multi-Head Attention Atmaja, Anugerah Surya; Muzakki, Naufal Fadli; Oktavian, Zulfaa Dwi
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.v2024i1.2125

Abstract

This study aims to predict the Ciliwung River water level in DKI Jakarta using an Long-Short Term Memory (LSTM) model with a multi-head attention mechanism. Increasing flood frequency due to climate change necessitates an effective early warning system. Utilizing historical water level data and related meteorological variables, the LSTM model with multi-head attention demonstrated superior performance, with Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Symmetric Mean Absolute Percentage Error (SMAPE) of 31.74, 3.3%, and 3.3%, respectively. Predictions for the next 72 hours indicate safe water levels between 450 cm and 500 cm, suggesting no flooding. In conclusion, the LSTM model with multi-head attention enhances water level forecasting accuracy and serves as a useful flood risk mitigation tool in Jakarta. This research significantly contributes to the development of flood early warning systems and the application of machine learning in disaster mitigation.
Pengelompokan Kabupaten/Kota Di Provinsi Papua Tahun 2023 Berdasarkan Kualitas Sumber Daya Manusia Sari, Novalianisa Permata; Renaldi, Egi
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.v2024i1.2129

Abstract

Since the establishment of the Golden Indonesia Vision in 2045, the government has targeted accelerating the distribution of education and improving the level of health and quality of life of the community as one of the efforts to develop the quality of human resources. This research focuses on the grouping of regencies in Papua Province in 2023 based on a composite index that describes the quality of human resources in Papua Province in 2023. The data used in this research is macro secondary data which is analyzed using descriptive analysis in the form of radar charts and inferential analysis using factor analysis. Formation of a composite index using factor analysis. Three factors were obtained which were used to create a composite index which was then used to present a better picture of various indicators supporting human resource development such as education, health, employment, economic and other variables. Then grouping by dividing into five groups based on quantiles to see spatial stratification.
Determinan Ketahanan Pembiayaan Defisit Anggaran Indonesia Tahun 1998-2022 Kholis, Nur; Wahyudin, Wahyudin
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.v2024i1.2132

Abstract

Indonesia's government debt ratio is still below the 60% limit set by law. However, the primary deficit in Indonesia's government budget from 2012-2022 has an increasing trend. Moreover, interest payments from sovereign debt are an additional burden on the government budget. This study examines the sustainability of Indonesia's budget-deficit financing using the Dornbusch Deficit Burden value and the factors that influence it. The Dornbusch Deficit Burden value is interpreted as a change in value of debt-to-GDP ratio. Yearly data used from 1998-2022. The analysis method used is the ARDL-ECM. In the short term, the rupiah exchange rate has negative effect on Dornbusch Deficit Burden value, while in the long term, the rupiah exchange rate has positive effect. The world crude oil price negatively affects Dornbusch Deficit Burden value in short term, while foreign interest rate (Fed Rate), in long and short term, has nonsignificant effect on Dornbusch Deficit Burden value.

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