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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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Energy Development Index (EDI) dan Implikasinya terhadap Kemiskinan di Indonesia: Studi Pendekatan Persamaan Simultan Dewi, Ni Made Wulan Puspita
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2355

Abstract

This study analyzes the reciprocal relationship between energy development and poverty in Indonesia using the Two Stage Least Squares (2SLS) approach, based on 2023 data from 34 provinces. EDI includes the share of energy expenditure, electricity consumption per capita, access to electricity, and access to clean cooking fuels. The results indicate that declining poverty rates and increased FDI-to-GRDP ratios significantly enhance EDI. In turn, higher EDI scores raise junior secondary Net Enrollment Rates and life expectancy at birth, although only life expectancy contributes to poverty reduction. Conversely, income inequality, measured by the gini ratio, intensifies poverty, while a greater number of health workers improves life expectancy at birth. Policy simulations suggest that reducing the gini ratio to 0,30 could lower the poverty rate by up to 7,848%. These findings underscore the importance of inclusive energy development and reduced income inequality as key elements in poverty alleviation strategies.
Mengukur Ketahanan Ekonomi Sulawesi Tenggara 2017-2023 Putri, Novia Dwi Kumala; Wulandari, Dyah Kusumaning Ayu; Setiawan, Iman
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2362

Abstract

Economic resilience emerged as a key concern for the government facing shocks from the COVID-19 pandemic and the Russia-Ukraine conflict. The economic resilience refers to a region's ability to bounce back quickly from economic challenges. Although Southeast Sulawesi's economic growth improved, the percentage of poor people increased during 2020-2023, signaling false economic resilience. The objective of this study is to assess the degree of economic resilience of Southeast Sulawesi through the Index of Economic Resilience (IKE) formed using factor analysis of panel data in 17 districts from 2017-2023. The results indicate the formation of three dimensions that make up the IKE, namely human capabilities, economic transformation, and income inequality. The average IKE value of the Southeast Sulawesi ranged from 0,29 to 0,40, indicating a gradual improvement in economic resilience. However, there is still an imbalance in the IKE between regions. Industrial downstreaming is one of the policies that should be considered to optimize economic resilience.
Menelusuri Keterbatasan dan Heterogenitas Akurasi Nighttime Light sebagai Proksi Aktivitas Ekonomi di Tingkat Kabupaten/Kota Lestari, Sintya Dwi; Pannu, Abdullah
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2364

Abstract

The use of NTL data as a proxy for economic activity has gained attention in regional economic studies. However, its effectiveness varies across regions depending on sectoral composition and geographic characteristics. This study aims to evaluate the effectiveness of NTL as a proxy for economic activity at the regency/city level in South Sulawesi Province during the 2014–2024 period. Using a fixed effects panel regression model, the results indicate a positive and significant relationship between NTL and GRDP at constant prices, with NTL explaining a substantial portion of interregional economic variation. However, RMSE-based accuracy analysis reveals spatial heterogeneity, with areas such as Makassar and Soppeng showing high prediction errors, indicating the limited ability of NTL to capture local economic dynamics. Additional control variables and remote sensing indicators failed to improve model performance. Thus, while NTL holds promise as an alternative economic indicator, its applicability must be contextually adapted to regional characteristics.
Analisis Sentimen dan Pemodelan Topik Opini Publik Terkait Data Badan Pusat Statistik Tahun 2024 Rahman, Dimas Haafizh; Alistin, Zharifah Dhiya Ayu; Pramana, Setia
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2365

Abstract

The role of BPS has become increasingly crucial with the rising demand and sources of data over time. The quality of BPS data is evaluated through the Data Needs Survey (SKD). The 2024 SKD indicates that 98.16% of consumers are satisfied with the quality of BPS data. However, this evaluation only involved data consumers from BPS PST, and there remains a time gap between the implementation and dissemination of the survey results. Social media platform X, which is popular in Indonesia, allows its users to express their opinions through tweets. This research is conducted to understand public sentiment, identify the best classification model, and discover topics discussed by the public regarding BPS data based on tweets from the X platform in 2024. The tweets were taken through labeling and preprocessing before applying Machine Learning methods to classify public sentiment. The Support Vector Machine (SVM) method, with a weighted average of 0.68, performed best compared to Naïve Bayes, Rocchio Classification, and K-NN in modeling public opinion sentiment. The implementation of LSA and LDA discovered topics consisting of public opinions and issues related to BPS data such as poverty rate manipulation and BPS data as a credible source.
Pendekatan Berbasis Big Data untuk Memetakan Tren Kerajinan Lokal Ponco, Sapta Hastho; Susanti, Susanti; Mufiedah, Maziyyatul
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2367

Abstract

The utilization of big data derived from online search activity is increasingly recognized as an alternative approach for identifying trends and economic opportunities, particularly within the creative economy sector. This study aims to explore the potential of Indonesia’s local craft subsector by analyzing online search data. Utilizing Google Trends and Natural Language Processing (NLP) techniques, this research maps public interest in craft products across spatial and temporal dimensions. Clustering and trend analysis methods are used to identify search patterns that reflect shifts in consumer preferences. The findings indicate that online search data can serve as an early indicator for capturing market dynamics and supporting evidence-based policy formulation. These results demonstrate that big data approaches can complement conventional surveys by providing a more adaptive, contextual, and real-time understanding of the local craft ecosystem.
Regresi Panel dalam Analisis Pengaruh Faktor Makroekonomi terhadap Harga Properti Residensial Tipe Kecil di 18 Kota Indonesia Tahun 2019–2024 Amanah, Cici Nurhaliza; Yuniasih, Aisyah Fitri
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2370

Abstract

Housing is a basic necessity that must be fulfilled by every individual. The 2020–2024 RPJMN targets increased access to adequate, safe, and affordable housing for Low-Income Communities (MBR). However, high property prices remain a major barrier. This study aims to analyze the factors influencing the prices of small-type residential properties in 18 cities in Indonesia during the 2019–2024 period. The small-type category was selected as it represents the MBR housing segment. The method used is panel data regression. The results show that GDRP per capita, GDRP deflator, and population density have a significant positive effect on the Small-Type Residential Property Price Index (IHPR), while the realization of FLPP subsidies has a significant negative effect. Meanwhile, the Construction Cost Index has no significant effect. These findings can serve as a basis for more targeted housing policies to meet the housing needs of low-income communities.
Analisis Multilevel pada Ketidaklayakan Upah Pekerja Perempuan Usia 18–49 Tahun pada Sektor Tersier di Nusa Tenggara Barat Tahun 2023 Mauboy, Lourna Mariska; Sitorus, Jeffry Raja Hamonangan
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2378

Abstract

Unlivable wages remain a key challenge in development. Despite minimum wage policies, many workers, especially women, still earn below the standard. West Nusa Tenggara (NTB) records the lowest average wage for female workers in Indonesia, even within the tertiary sector, which contributes the highest output and is the main employment source for women. This study examines unlivable wages among female tertiary-sector workers aged 18–49 using multilevel binary logistic regression with random intercept. Results show that 78.44% of women in this group still receive unlivable wages. Significant individual factors include child ownership, education level, certified training, and weekly working hours. At the regional level, the Open Unemployment Rate (OUR) is influential. These findings suggest that wage policy should consider both individual and regional aspects to improve wage livability for female workers in NTB’s tertiary sector.
Peran E-commerce terhadap Pengangguran, Kemiskinan, dan Lingkungan di Indonesia: Klasterisasi dan Analisis Jalur untuk Strategi Pembangunan Berkelanjutan Kautsar, Syahrizal; Ridwansyah, Rizki Riza; Priscilla, Nindia
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2379

Abstract

E-commerce has the potential to open new jobs and reveal poverty through digital entrepreneurship and expanding market access. However, there are other challenges such as the closure of old jobs, increasing greenhouse gas emissions and air pollution. This study aims to analyze the impact of e-commerce businesses on poverty, unemployment, and environment. This study uses data from 38 provinces in Indonesia in 2023 which includes the percentage of poor people, unemployment rates, and greenhouse gas emissions sourced from BPS, Sentinel-5P satellite imagery, and MERRA-2. The study results show that 38 provinces in Indonesia can be divided into four clusters with different criteria and problems on e-commerce, poverty, unemployment, and environment. In addition, this study shows that e-commerce can reduce poverty but has the potential to increase unemployment rates and reduce environmental quality. So that the right policy is needed so that e-commerce can be utilized to realize sustainable development.
Identifikasi Keterampilan Digital dalam Iklan Lowongan Kerja Menggunakan Klasifikasi Teks dan Named Entity Recognition Geraldy, Handy; Farentina, Rizka Amalia; Dirk, Fransisca Angelina
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2383

Abstract

Technological advancements have significantly reshaped the nature of work. A survey conducted by APINDO indicates that technology adoption contributed to elevated layoff rates during January-March 2025. Meanwhile, McKinsey & Company states that Indonesia will need 9 million digital talents (2014-2030). This study maps digital talent demand by classifying job vacancies data from Jobstreet based on digital skill levels (digital, semi-digital, and non-digital) and identifying the most frequently mentioned digital skills. The XGBoost achieves the best performance with an F1-score of 94.33%, outperforming SVM, logistic regression, and random forest. The study has provided an overview of job vacancy classifications based on the level of digital skills required. The XGBoost results indicate that 53,1% of job vacancies are classified as non-digital jobs. Furthermore, the NER model successfully identified skill entities in digital job vacancies, revealed that “communication”, “problem solving”, “software”, “design”, “SQL”, and “programming” were the most frequently mentioned skills.
Studi Implementasi Estimasi Luas Area Panen Padi Melalui Satellite Imagery Time Series dan Machine Learning Firmansyah, Achmad Fauzi Bagus; Permatasari, Novia; Utami, Nasiya Alifah
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2389

Abstract

Rice data is essential for policymakers in designing food security strategies in Indonesia. Currently, harvested area estimates are produced monthly using the Area Sampling Frame (ASF), although this method faces operational and cost-related limitations. Satellite Imagery Time Series (SITS) data, particularly from Sentinel-1, offers an alternative for identifying rice growth stages through machine learning-based modelling. This study applies that approach in South Sulawesi Province to estimate harvested rice area. The workflow includes regional clustering, satellite data integration, preprocessing, growth stage modelling using XGBoost, and phase area estimation. The results show that most clusters achieved high classification accuracy. Moreover, the predicted harvest area patterns closely match those from the ASF method. These findings demonstrate that using SITS data combined with machine learning offers an effective and practical alternative, especially in modernizing agricultural statistics systems in major rice-producing regions like South Sulawesi.

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