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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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Desain dan Implementasi Sistem Monitoring Jaringan Menggunakan Zabbix dan Telegram Malik, Prasetyo Fajar; Josaphat, Bony Parulian
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.v2024i1.2196

Abstract

The BPS Data Center requires an integrated monitoring system to ensure the integrity and accessibility of statistical data. Currently, the system is fragmented by device type and brand, lacking the ability to send real-time alerts to mobile devices. This research focuses on designing and implementing a monitoring system at the BPS Data Center. Furthermore, this research endeavors to forward alert from the monitoring system into mobile notifications. The study employs the Network Development Life Cycle (NDLC) methodology. From the results of the analysis using Pugh matrix, it was obtained that Zabbix was the selected monitoring application service and Telegram as the mobile application that utilizes the Bot feature to send notifications using webhook method. Based on the evaluation results from Black-box testing and SUS, it was found that overall, the system features were successfully tested with expected outputs, and the system interface received an “acceptable” rating from users.
Pembangunan Chatbot Sistem Informasi KBLI dan KBJI Berbasis LLM Anassai, Bayu Rayhan; Josaphat, Bony Parulian
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.v2024i1.2202

Abstract

The Central Statistics Agency (BPS) collects data through censuses and surveys to provide data to the government and the public. This data is obtained from questionnaires containing open and closed questions. One of the open questions asked is about the respondent's occupation, which will later be classified with the assignment of KBLI and KBJI codes. KBLI and KBJI are classifications used by BPS to classify economic activities. BPS uses the Sibaku Mobile application to facilitate officers in filling out KBLI and KBJI codes, but this application has shortcomings for new users. This research aims to develop a chatbot that can provide the correct KBLI/KBJI codes using Large Language Models (LLM). The chatbot development was carried out using the prototyping method. Evaluation of classification objectives showed accuracy, precision, recall, and F1-score values approaching 97%. The RAG robustness evaluation obtained a hallucination rate of 0% and an error rate of 7%. Usability testing showed a chatbot acceptance rate of 87.45%.
Rekomendasi Skema Sistem Satu Data Daerah Hasudungan, Rocky Gunung; Galistya, Theresia Mutiara; Solana, Aryadi; Aini, Nur; Ngurah Diksa, I Gusti Bagus; Sri Jayanti, Dewa Ayu
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.v2024i1.2203

Abstract

Indonesia has launched a National Statistics System (SSN) and the One Data Indonesia (SDI) program to ensure standardized and interoperable sectoral statistical data. Jembrana Regency, through the innovation "Jembrana Satu Data Dari Desa (JSDDD)," has demonstrated best practices in regional data management and successfully integrated data down to the village level. This success motivated the author to recommend a Regional One Data System Scheme. This paper emphasizes the importance for regions to have core data as a single source of truth to achieve data interoperability both within local government institutions and with central government. Core data can be obtained through independent village-level data collection, as seen in the JSDDD initiative, or by utilizing census-scale data. The regional office of BPS can play a crucial role as a data steward in auditing and evaluating the quality of regional data. The Regional One Data System can enhance the cost-efficiency of data collection and ensure that data is automatically updated through data registration-based government programs and services.
Analisis Sosial Ekonomi dan Kesehatan terhadap Angka Kematian Bayi di Jawa Timur 2022 Putri, Ananda Rania; Agustina, Serly; Sagita, Fauzan Faris; 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.v2024i1.2205

Abstract

Infant Mortality Rate (IMR) is a key indicator of a country's health and well-being. It's frequently regarded as a marker of social advancement and human growth. As a result, eliminating IMR is a major goal in the RPJMN 2020-2024, both nationally and regionally. East Java's IMR reached 13,49 deaths per 1000 live births, exceeding the 2024 objective. The purpose of the research is to investigate how socioeconomic and health-related factors would affect AKB in East Java in 2022. Descriptive and inferential analysis using multiple linear regression were employed. The results showed that the percentage of females aged 10 and up who married before the age of 17 and the open unemployment rate had a favourable effect on IMR. Meanwhile, birth at a health care facility and life expectancy have a detrimental impact on IMR.
Pemodelan Status Ketertinggalan Perekonomian Regional Menggunakan Geographically Weighted Logistic Regression (GWLR) Bani Syafii, Ghulam An-Nabalah; Hanifah, Ria Dini; Arisanti, Rohimma; Pusponegoro, Novi Hidayat
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.v2024i1.2208

Abstract

The goal of economic development is to improve the well-being of the people. However, economic development, especially in developing countries, including Indonesia, has been hampered by interregional disparities. This inequality leads to a grouping of economically backward people. This research aims to find out the general picture and identify the presence of spatial aspects on the status of the regional economy backwardness and the factors that influence it from the production side. Because there are indications of dependency and spatial heterogeneity, the study uses the Geographically Weighted Logistic Regression (GWLR) model. The results show that the rise in capital and the decrease in labor will lower the tendency for one to be categorized as a backward region. Therefore, investment needs to be intensified in industries in Indonesia and it is necessary to improve the quality of technologically literate human resources to streamline the production process.
Kajian Penerapan Machine Learning untuk Sistem Rekomendasi Mitra Statistik BPS Septianugraha, Damar; Wilantika, Nori; Suadaa, Lya Hulliyyatus; Prasetyo, Rindang Bangun; Huraira, Sabit
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.v2024i1.2211

Abstract

BPS routinely conducts censuses and surveys involving BPS partners in data collection and processing. Ensuring these partners exhibit good performance is crucial to minimize the risk of moral hazard, which can negatively impact stakeholders. This research aims to implement machine learning into an information system to recommend statistical partners based on classification results. The best model identified is XGBoost, which is integrated into the system for generating recommendations. System testing using black-box methods confirmed compliance in 41 scenarios. Additionally, the System Usability Scale (SUS) questionnaire yielded an average score of 65.5, indicating the system's potential and suitability for further development. The findings offer insights into utilizing partner characteristics data and evaluation in BPS's censuses and surveys, particularly for selecting assigned partners.
Analisis Faktor-Faktor yang Memengaruhi Ekspor Minyak Kelapa Sawit (CPO dan Turunannya) Indonesia Tahun 1990-2022 Putri, Nabila Aurelliza Candrika; Yuliana, Rita
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.v2024i1.2212

Abstract

International trade plays an important role in economic development, including for Indonesia, which is the world's largest producer and exporter of palm oil in 2021. However, in recent years, palm oil exports have fluctuated, worsening Indonesia's non-oil and gas trade balance. However, domestic palm oil stocks are still large, providing an opportunity to maximize exports amid rising international prices. This study aims to analyze the development of palm oil exports and the factors that influence them in the long and short term from 1990 to 2022 using the Autoregressive Distributed Lag (ARDL) method. Palm oil exports have an increasing trend. In the long term, production, international prices, domestic investment, and foreign investment affect exports. Meanwhile, export lag, real exchange rate, production, real interest rates, and PMDN affect exports in the short term. Simplification of export regulations and investment management can be a concern for the government to increase Indonesian palm oil exports.
Pemanfaatan Citra Satelit untuk Mendeteksi Zona Potensi Penangkapan Ikan Cakalang Sagitama, Daniel Angga; 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.v2024i1.2215

Abstract

North Sumatra has some of the main commodities of fishing, one of which is skipjack tuna. During the period from 2019 to 2021, the production of skipjack tuna in North Sumatra has declined. To help fishermen find out where the fish are gathering, it is necessary to map Potential Fishing Zone (PFZ) using remote sensing methods. The research is aimed at implementing remote sensing methods for PFZ detection using Aqua-MODIS sensor data, determining sea surface temperature spread (SST) and chlorophyll-a concentration, as well as forming a monthly PFZs map. Furthermore, the highest SST occurred in February at 34.5°C and the lowest in December at 27.3°C. Meanwhile, high concentrations of chlorophyll-a tend to accumulate near the coast. As a result of the estimate of the potential zone for catch, September has the most potential points followed by October, while the months with the least potential points are January, July, and March. From the results, it can be said that the best time to catch skipjack tuna in the West Indian Ocean, the Nias Islands and the Sibolga Nias waters is predicted to be in September and October.
Transformasi Kebijakan Ketenagakerjaan Menuju Indonesia Emas 2045: Pemanfaatan Machine Learning dalam Analisis Risiko Pengangguran Rokhmawati, Anita; Aziz, Maulana Zulfikar
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.v2024i1.2222

Abstract

Indonesia is undergoing a positive development, marked by an increase in the productive population and economic capacity over the past two decades. With the vision of "Golden Indonesia 2045," Indonesia aims to boost development across various sectors, including employment, by reducing unemployment and increasing female participation in the labor market. However, the demographic bonus presents both opportunities and challenges, potentially increasing productivity but also risking higher unemployment. This study uses machine learning to evaluate and analyze unemployment risk based on demographics, education, training, and pre-employment program participation. Using data from the National Labor Force Survey (SAKERNAS), the study applies models such as Random Forest, Gradient Boosting, Extreme Gradient Boosting, and KNearest Neighbor. The results show that while these models struggle to predict unemployment risk, they perform well in predicting employment status. Education level and marital status are significant predictors, while the pre-employment program does not significantly reduce unemployment risk.
Sistem Closed Domain Question Answering Metadata Statistik Berbasis Metode Transfer Learning Rachmawati, Nur; Yulianti, Evi
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.v2024i1.2225

Abstract

Statistical metadata plays an important role in society. Statistical metadata allows us to know all information about statistical activities that have been carried out. In this study, we built a Closed Domain Question Answering system related to statistical metadata (CDQA-Metadata Statistik). The absence of a large benchmark regarding QA datasets on statistical metadata caused us to choose the transfer learning method. This study uses a retriever (BM25)-reader (IndoBERT) architecture based on transfer learning with three experiments. The results of the first experiment showed that statistically the performance of the transfer learning model significantly outperformed the non-transfer learning model on human question data and automatic question data. The results of the second experiment showed that statistically the performance of the CDQAStatistical Metadata system based on transfer learning on automatic question data was significantly better than on human question data. The results of the third experiment showed that for human question data, adding automatic question data during fine-tuning did not improve system performance. Then on automatic question data, adding human question data during fine-tuning did not seem to be able to improve system performance.

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