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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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Pengelompokkan Wilayah Berdasarkan Variabel-Variabel Kemiskinan di Provinsi Aceh dengan Metode Average Linkage Hierarchical Clustering Wahyudi, Muhammad Rafidzaky; Siagian, Tiodora Hadumaon
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.v2024i1.2256

Abstract

The big problem facing the Indonesian government is poverty. Aceh Province is one of the poorest provinces in Indonesia. It ranked 6th and even became the poorest province in the Western region of Indonesia. This condition is quite pathetic considering that Aceh is a province that has special autonomy and quite a large regional income, making it one of the richer provinces. Therefore, this study aims to cluster regions in Aceh Province based on poverty variables using the average linkage hierarchical clustering method and compare the results in 2017 and 2022. The results of the study show that the clustering results in 2017 are no different from 2022. Two clusters were formed, Cluster 1 consists of 3 districts with low poverty levels, and Cluster 2 consists of 20 districts with high poverty levels. This explains that in the 2017–2022 Aceh government period, areas with high poverty levels remain in the high poverty category, and vice versa. It means that the poverty alleviation efforts carried out by the Aceh government during that period have not been able to optimally improve the welfare of the Acehnese population.
Blue Economy Sebagai Solusi Keluar Dari Middle Income Trap Ayuningtyas, Agian Dila; Muchlisoh, Siti
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.v2024i1.2267

Abstract

From 2001 to 2021, the income slowdown in Indonesia has led to the middle-income trap phenomenon. Indonesia has significant potential in the blue economy sector due to its vast marine area of 6,4 million square kilometers, 1,8 million hectares of seagrass beds, and 3,4 million hectares of mangroves. This potential can be leveraged by Indonesia as an alternative solution to the middle-income trap issue. This study uses World Bank and World Tourism Data from 2001-2021. A multiple linear regression model is employed to determine the impact of blue economy variables on Indonesia's national per capita income. The results show that blue economy variables such as aquaculture production and total sea containers positively impact. Conversely, capture fisheries production and marine tourism negatively impact, while the percentage of protected areas has no significant effect on Indonesia's national per capita income. Policy simulation results indicate that increasing capture fisheries and aquaculture production can be a solution to overcome the middle-income trap.
Prediksi Jumlah Wisatawan Mancanegara Yang Masuk Melalui Bandara Kualanamu Menggunakan Big Data Google Trends Febrian, M. Yandre; 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.v2024i1.2273

Abstract

The number of foreign tourists that continues to increase in North Sumatra makes the government must prepare appropriate strategies for policy-making. The data released by the Central Statistics Agency (BPS), as the responsible institution, still has shortcomings, particularly the time gap between data collection and publication. Using Google Trends as supplementary data to fill this time gap is feasible, as Google Trends data can be accessed in real time. This study aims to examine the relationship between Google Trends data and official statistical data, compare the use of SARIMA and SARIMAX models, and forecast the number of tourists for the next year. The results show a moderate correlation between the Google Trends index and official statistics, with a correlation value of 0.592. The most suitable model for this data is the Seasonal Autoregressive Integrated and Moving Average (SARIMA) (0,1,1) (1,0,1)12, with a Root Mean Square Error (RMSE) of 10.223.
Peningkatan Kendali Mutu Audit Inspektorat Utama BPS RI Modul Perencanaan dan Pelaksanaan Audit Melalui Pembangunan Sistem Informasi Fajar, Roby Awaludin; Maghfiroh, Lutfi Rahmatuti
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.v2024i1.2282

Abstract

Statistics Indonesia (BPS) is mandated to perform internal supervision to ensure organizational purposes and functions adhere to good governance standards. This supervision is conducted by the Main Inspectorate, responsible for audit activities.Currently, audit documentation fails to fully comply with quality control standards and the manual audit process induces inefficiencies in data entry and document management. Consequently, this study aims to enhance audit quality control through the development of an information system utilizing the modified waterfall SDLC model. Business process data were collected through interviews and literature reviews.The system was tested using black-box testing and evaluated with Computer System Usability Questionnaire (CSUQ). Results indicated that all system features functioned as specified, with high scores in all CSUQ categories. User evaluations demonstrated that the system effectively improves transparency, accountability, and efficiency, ensures information is displayed according to access rights, produces accurate documentation, and facilitates the input and storage of audit records.
Analisis Nilai Ekspor Nikel Kode HS 75 Tahun 2017-2023 Dengan Pendekatan Error Correction Mechanism (ECM) Rahman, Faiz Fathur; Pasaribu, Ernawati
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.v2024i1.2283

Abstract

Nickel ore is a highly potential mining commodity, evidenced by the fact that 52 percent of the world's nickel reserves are located in Indonesia, and in 2021, Indonesia became the largest nickel producer globally. However, the processing of nickel in Indonesia remains suboptimal, given the substantial volume of nickel ore exported without processing. Therefore, this study aims to analyze the impact of investment, production, unit cost, RCA value, and ECI on the export value of Indonesia's nickel. This research employs the Error Correction Mechanism (ECM) method. The analysis results indicate that, in the long term, nickel ore production, unit cost, and RCA have a significant positive effect. In the short term, only RCA and ECI have a significant positive effect on the export value of nickel. Lastly, according to the speed of adjustment value, the short-term model will be corrected by 44.78 percent in the first year and the remaining in subsequent years.
Implementasi Small Area Estimation Hierarchical Bayes - Beta Difference Benchmark dalam Estimasi NEET Lulusan Perguruan Tinggi Salis, Dian Rahmawati; Japany, Adham Malay; Rodliyah, Ratih; Ibad, Syaikhul; Pulungan, Ridson Al farizal; Ramadhan, Yogi
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.v2024i1.2285

Abstract

The survey data generated by BPS serves as the primary data source for calculating various SDGs indicators. However, not all indicators can be reliably estimated, particularly at detailed disaggregation levels. Some indicators face issues due to sample inadequacy, resulting in high Relative Standard Errors (RSEs) if estimated directly. One such indicator is the percentage of young college graduates who are neither in education, employment, nor training (NEET). This indicator is only available at the provincial level, with disaggregation based on other characteristics only available at national level. Therefore, this study aims to estimate NEET among college graduates at the regency/city level in Sumatra Island for the year 2023 using the SAE HB Beta model. To maintain consistency with direct estimates at the provincial level, which have shown sufficiently low RSEs, a benchmarking process will be conducted using the difference benchmark method. Based on the findings, the difference benchmark method enhances the validity of the estimation results using the SAE HB Beta model.
Topic Modelling Berbasis Embedding pada Komentar YouTube Muhabbab, Ahmad Zein Abid; Rizki, Rohmad Ali Fatur
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.v2024i1.2286

Abstract

The National Data Center is a vital infrastructure for the Indonesian government in processing, storing, and protecting public data. However, the ransomware attack on June 20, 2024, not only disrupted operations but also potentially damaged the government's reputation and public trust. This research analyzes public perceptions of the attack through YouTube comments using topic modeling techniques. The analysis aims to understand public views, develop more effective communication strategies, and help restore public trust. Various embedding models, such as BERT and FastText, were evaluated using Coherence Score (
Dampak Dampak Liberalisasi Perdagangan Terhadap Inflasi di Indonesia Rangkuti, Suifatiha; Rahmi, Meautia; Nuriyo, Amalia Ndaru; 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.v2024i1.2288

Abstract

Globalisation encourages the trade of goods and services between countries without any trade barriers, or known as trade liberalisation. Trade liberalisation can impact the macroeconomic indicators of countries that engage in international trade, one of which is inflation. The purpose of this study is to analyse the effect of trade liberalisation on inflation in Indonesia. The variables used are trade openness and inflation. This study uses autoregressive distributed lag (ARDL) method with the research period 2000 - 2023. In addition, government spending and money supply are also used as control variables. The results show that trade openness can increase the inflation on one untill two years later. Trade openness is also show the same effect in the long run and short run. Meanwhile, government expenditure and money supply also increase inflation in the long run and short run.
Pemetaan Daerah Aktivitas Perikanan Berbasis Data AIS Busaina, Ladisa; Utami, Nandya Rezky; Pramana, Setia; Krismawati, Dewi
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.v2024i1.2299

Abstract

Digital development brings significant changes in data collection and processing, with big data becoming the main source of official statistics. BPS has been using big data since 2015 for more accurate analysis and statistics. Automatic Identification System (AIS) data, an automated ship navigation system, effectively monitors ship movements and is used for official statistics, improving accuracy and reducing human error. However, monitoring of Indonesia's marine activities is still not optimal, as seen from the low contribution of the fisheries sector to GDP and indications of overfishing due to illegal fishing activities (IUU). The use of AIS is important for monitoring illegal activities, but data quality is often low. Data quality assurance through preprocessing is needed. This research will map fisheries activity areas in the waters around Papua Island using AIS data and the DBSCAN algorithm to cluster fishing vessels, in order to improve monitoring of fisheries activities in Indonesia.
Analisis Not in Employment, Education or Training (NEET) pada Penduduk Usia Muda di Kawasan Timur Indonesia Tahun 2022 dengan Regresi Logistik Biner Tiga Level Amaliah, Rizka; 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.v2024i1.2300

Abstract

NEET is one of youth issue that can impact development, because its crucial role in national development. The NEET problem in Eastern Part of Indonesia (KTI) is higher than Western Part of Indonesia (KBI), in line with KTI’s lagging development. Studying NEET requires consideration from various aspects, because of varying NEET across regencies/cities. Additionally, youth career decisions can be influenced by family background and individual characteristics. This study aims to analyze the factors causing young people in KTI becomes NEET in 2022 using multilevel binary logistic regression, consisting of individual, household, and regencies/cities levels. Data sources include Sakernas August 2022, PODES 2021, BPS Provincial Publications in Numbers 2023, and Provincial Welfare Statistics 2022. The study found that NEET status in KTI is influenced by gender, migration status, disability, household head’s gender, household head’s education level, household head’s employment status, employment opportunities, and the ratio of high schools per 100 km².

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