Publikasi Ilmiah

Introduction. This research aims to study a novel approach to producing tourism statistics, especially accommodation statistics, in Indonesia using scraping of online travel agent Websites.Method. Accommodation data (e.g., room availability and price) were gathered from two of the largest online travel agencies in Indonesia. All data were collected automatically from the sites’ URLs listed in the sitemap.Analysis. The data were collected daily from 6 March to 27 July 2019. Datasets from the two Websites were merged. The room occupation rate (ROR) for each province was calculated and compared with the official statistics from Statistics Indonesia.Results. The results show that the online room occupancy rates and official statistics have a similar pattern indicating the use of the Web scraping technique provides valuable information, to measure the room occupation rate with an advantage in terms of cost and collection time.Conclusions. It is feasible to use big data as a proxy of or a complement to official statistics, especially in tourism statistics. By using the Web scraping technique, the indicator that usually requires significant time and cost can be done in real-time and less cost. This new approach would improve the quality of tourism statistics produced by BPS Statistics Indonesia.

Purpose: This research aims to explore the level of air pollution in Jakarta, the epicenter of COVID-19 Pandemic in Indonesia and its surrounding provinces during the first month of the Pandemic. Research design, data and methodology: This study uses data, which have been obtained real time from API (Application Programming Interfaces) of air quality website. The measurements of Air Quality Index (AQI), temperature, humidity, and other factors from several cities and regencies in Indonesia were obtained eight times a day. The data collected have been analyzed using descriptive statistics and mapped using QGIS. Results: The finding of this study indicates that The Greater Jakarta Area experienced a decrease in pollutant levels, especially in the Bogor area. Nevertheless, some areas, such as the north Jakarta, have exhibited slow reduction. Furthermore, the regions with high COVID-19 confirmed cases have experienced a decline in AQI. Conclusions: The study concludes that the air quality of three provinces, Jakarta, Banten, and West Java, especially in cities located in the Jakarta Metropolitan Area during COVID-19 pandemic and large-scale social restrictions, is getting better. However, in some regions, the reduction of pollutant concentrations requires a longer time, as it was very high before the pandemic.

Nowadays, the use of so-called big data as a new data source to complement official statistics has become an opportunity for organizations focusing on statistics. The use of big data can lead to a more efficient data collection. However, currently, there has not been any standard business process for big data collection and processing in BPS-Statistics Indonesia. Meanwhile, the adoption of technologies alone cannot determine the success of big data use. It is widely known that big data use can be challenging, since there are issues regarding data access, quality, and methodology, as well as the development of required skillsets. This paper proposes a framework for a business process that is specifically designed to support the use of big data for official statistics at BPS-Statistics Indonesia along with how existing technology will support it. The development of this framework is based on the wider Statistical Business Process Framework and Architecture (SBFA) developed by BPS-Statistics Indonesia to describe and manage its overall statistical business processes. The paper uses the example of the use of Mobile Positioning Data (MPD) as a big data source to delineate Metropolitan Areas in Indonesia as a way to explain the implementation of the framework.

Virus  Covid-19  yang  pertama  kali  masuk  ke  Indonesia  pada  Desember  2019 berdampak pada kemunduran dalam industri aviasi. Hal ini dibuktikan oleh data BPS tahun 2020  bahwa  kontribusi  industri  aviasi  terhadap  PDB  Indonesia  turun  dari  1,21%  menjadi 0,28%  di  kuartal  kedua  2020.  Untuk  mengatasi  kemunduran  tersebut,  monitoring  secara komprehensif  oleh  pemangku  kebijakan  sangat  diperlukan.  Pemanfaatan  big  data  dalam monitoring  aktivitas  industri  aviasi  dapat  menjadi  pilihan.  Penelitian  ini  bertujuan  untuk menganalisis   aktivitas   aviasi   dengan   pendekatan   big   data   sebagai   dasar   monitoring. Pengumpulan  data  dilakukan  dengan  menggunakan  metode  web  scraping  pada  salah  satu website aviasi global untuk mendapatkan data status penerbangan di 108 bandara di Indonesia dalam rentang waktu April 2020 hingga Juni 2021. Data lainnya yang digunakan adalah data indeks  mobilitas  google,  data  (Tingkat  Penghunian  Kamar  Hotel)  TPK  dan  data  PDB Indonesia.  Analisis  dilakukan  dengan  metode  analisis  deskriptif,  analisis  korelasi  dan pemodelan time series berbasis machine learning menggunakan AR-NN, single layer ANN, dan MLP.  Hasil  menunjukkan  bahwa  kebijakan  pembatasan  mobilitas  masyarakat  berpengaruh terhadap   produktivitas   industri   aviasi.   Pemodelan   machine   learning   yang   dilakukan menunjukkan bahwa model MLP merupakan model terbaik untuk meramalkan aktivitas aviasi internasional.  Selain  itu,  ditemukan  bahwa  industri  aviasi  memiliki  keterkaitan  erat  dengan perekonomian dan pariwisata di Indonesia.  

Pandemi COVID-19 telah menjadi krisis global yang berdampak luas pada sektor lain seperti ekonomi dan pasar tenaga kerja. Sektor kesehatan merupakan salah satu sektor yang terkena dampak COVID-19 dari sisi permintaan tenaga kerja. Selain kebutuhan tenaga kesehatan untuk penanganan COVID-19 dan permintaan tenaga kesehatan pada jabatan pekerjaan lain, peran teknis dan nonteknis tetap dibutuhkan di masa pandemi. Beberapa sumber big data bisa dijadikan proxy untuk melihat dampak dari pandemi COVID-19. Penelitian ini bertujuan untuk memperoleh gambaran tentang pengaruh pandemi COVID-19 terhadap kebutuhan tenaga kerja di bidang kesehatan khususnya di wilayah Jawa-Bali. Data bersumber dari situs lowongan kerja online dengan metode web scraping. Data jumlah iklan lowongan kerja yang berasal dari situs lowongan kerja online digunakan untuk melihat perubahan permintaan tenaga kerja pada perusahaan di bidang kesehatan. Hasil analisis menunjukkan bahwa pandemi berdampak pada penurunan iklan lowongan pekerjaan bidang kesehatan di wilayah Jawa-Bali. Selain itu, terdapat hubungan yang jelas antara penurunan jumlah iklan lowongan kerja dengan indeks ketat kebijakan pemerintah yang dirancang untuk menghentikan penyebaran COVID-19. Pada tahun 2021, lowongan untuk posisi pekerjaan teknis seperti dokter, perawat, dokter gigi, dan apoteker masih banyak ditawarkan dan cenderung meningkat dibandingkan tahun sebelumnya. Sementara itu, lowongan pekerjaan non-teknis seperti resepsionis, administrasi, dan pemasaran cenderung menurun pada tahun 2021