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Pemanfaatan Big Data dalam Monitoring Pola Aktivitas Aviasi di Indonesia Nasiya Alifah Utami; Thosan Girisona Suganda; Setia Pramana
Jurnal Matematika Vol 11 No 2 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2021.v11.i02.p140

Abstract

Abstract: Covid-19 which entered Indonesia in December 2019 has a significant impact on the aviation industry. According to BPS data for 2020, the aviation industry's contribution to Indonesia's GDP decreased from 1.21% to 0.28% in the second quarter of 2020. To overcome this setback, comprehensive monitoring by policy makers is needed. The use of big data in monitoring aviation industry activities can be an option. This study aims to analyze aviation activities using big data approach for monitoring basis. The data was collected by using web scraping method on one of the global aviation websites to obtain flight status data at 108 airports in Indonesia on April 2020 until June 2021. Other data used are google mobility index data, GDP data, and TPK. The analysis method used are descriptive analysis, correlation analysis and machine learning based time series modelling with ARNN, single layer ANN and MLP. The results show that the policy of restricting mobility has a significant effect on the productivity of aviation industry. Machine learning modeling shows that the MLP model is the best model for forecasting international aviation activity. In addition, it was found that the aviation industry has a strong correlation with the economy and tourism sector in Indonesia.
Development of Website-Based a Health Crisis Reporting System Yeni Rimadeni; Hizir Sofyan; Safrizal Rahman; Setia Pramana; Rina S. Oktari
International Conference on Multidisciplinary Research Vol 4, No 1 (2021): ICMR
Publisher : Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/pic-mr.v4i1.3774

Abstract

Health crisis management is prioritized on health crisis risk reduction consisting of pre-health crisis stage, health crisis emergency response stage, and post-health crisis stage. Prevention and mitigation efforts at the pre-health crisis stage, in the context of our study, aim to develop an information system for health crisis management. Information system for health crisis, in general, is provided by the Health Agency. In this study, we discussed the system applied by the Health Agency of Aceh Tengah that still uses a manual information system for reporting during disasters. Hence, it causes a delay of the information updates despite the emergency situation. To overcome this problem, we proposed a newly developed health crisis management reporting system in disaster risk reduction. We used a Research and Development approach with Heuristic Review Analysis to assess the performance of the proposed system. The scope of the study was limited to the development of a new reporting system and system test on users. The research subjects were disaster officers and heads of 14 health centers involved in the health crisis reporting in Aceh Tengah. Improvements can be made in the future through trainings and system adjustments supported by institutional policies. Keywords: Health crisis, disasters, website, reporting system.
ANALISIS FAKTOR-FAKTOR YANG MEMENGARUHI KETAHANAN INTERVAL KELAHIRAN ANAK PERTAMA Farakh Khoirotun Nasida; Setia Pramana
Seminar Nasional Official Statistics Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (530.536 KB) | DOI: 10.34123/semnasoffstat.v2019i1.24

Abstract

Perencanaan keluarga merupakan hal yang penting dalam pencapaian Sustainable Development Goals. Tingginya angka kelahiran di negara berkembang biasanya tidak diimbangi dengan perencanaan keluarga yang baik sehingga mengakibatkan banyak masalah yang lebih serius. Tujuan ketiga SDGs yaitu good health and wealth being bahkan menyoroti secara serius masalah kematian ibu dan bayi. Tingkat fertilitas diukur dengan angka fertilitas total (TFR). Papua merupakan provinsi dengan TFR tertinggi kedua di Indonesia. Tingginya TFR merupakan implikasi dari umur melahirkan pertama yang terlalu muda. Untuk menurunkan TFR Provinsi Papua, perlu dilakukan kebijakan dan program khususnya yang berkaitan dengan interval kelahiran pertama. Tujuan penelitian ini adalah untuk mengetahui faktor-faktor yang memengaruhi interval kelahiran pertama di Provinsi Papua. Penelitian ini menggunakan data sekunder dari Survei Demografi dan Kesehatan Indonesia (SDKI) 2017 sebagai wujud pemanfaatan data official statistics untuk memantau pencapaian SDGs. Variabel yang dicakup meliputi faktor wanita dan faktor rumah tangga. Menggunakan pengujian log-rank, didapatkan bahwa terdapat perbedaan ketahanan yang signifikan antarkategori variabel tingkat pendidikan dan status kesejahteraan. Melalui permodelan semiparametrik menggunakan Cox-Proportional Hazard, variabel tingkat pendidikan, status kesejahteraan, dan status migrasi wanita berpengaruh signifikan terhadap interval kelahiran anak pertama. Wanita dengan pendidikan SMP ke atas, memiliki kesejahteraan tinggi, dan bukan migran memiliki risiko yang lebih tinggi untuk melahirkan anak pertama lebih cepat daripada wanita dalam kategori referensi masing-masing.
FAKTOR-FAKTOR YANG MEMPENGARUHI ANGKA KEMATIAN BALITA DI PROVINSI PAPUA Mieke Nurmalasari; Linta Ifada; Setia Pramana
Seminar Nasional Official Statistics Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (258.725 KB) | DOI: 10.34123/semnasoffstat.v2019i1.159

Abstract

Usaha untuk menurunkan Angka Kematian Bayi (AKB) dan Angka Kematian Anak Bawah Lima Tahun (AKABA) masih terus dilakukan meskipun secara global sudah mengalami penurunan. Kematian bayi dan balita merupakan masalah kesehatan yang penting di Indonesia terutama bagi wilayah Indonesia di bagian timur karena angka kematian keduanya masih tinggi. Salah satu agenda dari Sustainable Development Goals (SGDs) adalah menurunkan angka kematian bayi menjadi paling tidak 12/1000 kelahiran pada tahun 2030. Penelitian ini bertujuan untuk mengidentifikasikan faktor-faktor yang mempengaruhi angka kematian balita di Propinsi Papua dilihat dari karakteristik individu ibu, anak yang dilahirkan dan lingkungannya berdasarkan data SUPAS 2015. Metode yang digunakan adalah analisis regresi logistik. Hasil penelitian ini menunjukkan bahwa faktor pendidikan ibu, interval melahirkan sebelumnya, jenis atau tipe kelahiran, jenis kelamin, dan sanitasi memberikan pengaruh yang signifikan terhadap kematian balita di Propinsi Papua.
PEMANFAATAN BIG DATA MARKETPLACE TERHADAP PROFIL EKONOMI DIGITAL DAERAH SEKTOR PERDAGANGAN DI KALIMANTAN BARAT, INDONESIA Dandy Adetiar Al Rizki; Usman Bustaman; Setia Pramana
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.18 KB) | DOI: 10.34123/semnasoffstat.v2020i1.474

Abstract

Ekonomi digital lahir dan berkembang seiring penggunaan teknologi informasi dan komunikasi yang juga semakin mengglobal di dunia. Keberadaan ekonomi digital ditandai dengan semakin maraknya perkembangan bisnis atau transaksi perdagangan yang memanfaatkan internet sebagai media komunikasi, kolaborasi, dan kooperasi antar perusahaan ataupun individu. Dalam mewujudkan pembangunan ekonomi nasional pemerintah perlu memberikan insight untuk menjadi bahan dasar edukasi kepada berbagai pihak dengan memanfaatan Big Data penjualan pada marketplace dalam membentuk profil ekonomi digital daerah. Penelitian dilakukan dengan pendekatan kualitatif menggunakan deskriptif kualitatif metodologi visual site of self, dimana peneliti bertindak sendiri untuk melakukan interpretasi, pemaknaan dan pemahaman terhadap obyek penelitian yang diamati. Pertumbuhan penjualan online dengan Januari sebagai bulan dasar menunjukkan tren naik di Kalimantan Barat hal ini merepresentasikan bahwa ekonomi digital di kalimantan barat dapat tumbuh dan berkembang serta mempengaruhi keadaan ekonomi masyarakat. Ditinjau dari kategori yang telah dikumpulkan banyak kategori yang mengalami pelonjakan dalam pertumbuhan penjualannya dengan Januari sebagai bulan dasarnya. Big Data penjualan pada salah satu marketplace menunjukkan distribusi harga produk yang relatif tersebar dengan selisih yang tidak terlalu besar antar kabupaten/kota di Kalimantan Barat. Produk terbanyak yang terjual di Kalimantan Barat didominasi oleh kategori Voucher dengan jenis barang Pulsa & Data, Voucher Gaming, dan Voucher Belanja termasuk didalamnya Voucher Listrik, Gas, & Air. Kota Pontianak tercatat sebagai daerah dengan penjualan barang terbanyak melalui kategori Perawatan & Kecantikan sebagai komoditasnya dan jenis produk terbanyak berupa Kosmetik Wajah.
PROFIL TINGKAT OKUPANSI HOTEL DI NTB SELAMA PANDEMI COVID-19 DENGAN MENGGUNAKAN BIG DATA Wiwin Srimulyani; Nurtia Nurtia; Maulana Faris; Nensi Fitria Deli; Setia Pramana
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (308.071 KB) | DOI: 10.34123/semnasoffstat.v2020i1.503

Abstract

SARS-CoV-2 atau lebih biasa dikenal dengan COVID-19 pertama kali terjadi di Wuhan, ibukota Provinsi Hubei, China pada akhir tahun 2019 lalu. Virus covid-19 juga berdampak besar terhadap industri perhotelan dengan tingkat hunian yang jauh dibawah rata-rata musiman di seluruh Indonesia. pada saat pertama kali covid-19 diumumkan tingkat okupansi turun hingga 20% di seluruh hotel di Indonesia. Tak hanya itu kebijakan new normal juga sangat mempengaruhi preferensi masyarakat untuk berlibur dan menggunakan fasilitas akomondasi. Untuk itu penelitian ini bertujuan untuk mengetahui tentang dampak covid-19 terhadap tingkat okupansi hotel di Nusa Tenggara Barat dengan menggunakan metode web scraping. Tingkat okupansi hotel didekati dengan menjumlahkan jumlah kamar total dikurangi dengan jumlah kamar tersisa kemudian hasilnya dibagi dengan jumlah kamar total lalu dikalikan dengan sebuah konstanta. Secara keseluruhan,diumumkannya covid-19 pertama kali membuat tingkat okupansi hotel di Nusa Tenggara barat turun drastis hingga 14%. Penurunan ini juga terjadi untuk hotel berbintang dan hotel dengan tipe guesthouse, hostel, resor dan hotel. Namun, penurunan ini tidak terjadi untuk hotel non bintang. Sedangkan pada era new normal, kenaikan tingkat okupansi yang bertahap terjadi di Nusa Tenggara Barat. Hal ini juga berlaku untuk hotel berbintang, non bintang, hotel dengan tipe resor dan hotel. Sebaliknya, new normal tidak terlalu mempengaruhi tingkat okupansi hotel dengan tipe guesthouse dan hostel.
KAJIAN PEMANFAATAN DATA GOOGLE MAPS DALAM OFFICIAL STATISTICS Cholifa Fitri Annisa; Setia Pramana
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (404.635 KB) | DOI: 10.34123/semnasoffstat.v2020i1.614

Abstract

Publication of food and drink supply business statistics published by BPS cannot facilitate businessmen in identifying areas that have the potential to develop businesses in the food and drink supply sector. In addition, there are limitations in time, cost, and manpower in data collection by the BPS Tourism Sub-directorate on the VREST survey, so that the food and drink supply statistics cannot be published according to the methodology, namely every year. This study utilizes the web scraping method to obtain business data on food and drink providers from the google maps website. The amount of data collected is as many as 34,526 food and drink providers in Java and Bali. The results of the matching value of web scraping data with BPS data frames show a match percentage of 68.22%. Bali Province is an area that has the potential to develop food and beverage supply businesses, especially in the City / Regency of Jembrana, Buleleng, Tabanan, Karangasem, and Klungkung. Meanwhile, Central Java province is an area that has the potential to develop accommodation businesses, especially in the cities / regencies of Cilacap, Blora, Grobogan, Batang, and Kendal.
Penerapan Bayesian Network dalam Memodelkan Kondisi Ekonomi Hijau Indonesia di Era Pandemi Berdasarkan Big Data Salwa Rizqina Putri; Thosan Girisona Suganda; Setia Pramana
Seminar Nasional Official Statistics Vol 2021 No 1 (2021): Seminar Nasional Official Statistics 2021
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (681.519 KB) | DOI: 10.34123/semnasoffstat.v2021i1.1023

Abstract

To support Indonesia's green economic growth, further analysis is needed regarding economic activity during the pandemic and its relationship to environmental conditions. This study aims to apply the Bayesian Network approach in modeling Indonesia's green economy conditions during the pandemic based on variables that are allegedly influential, such as economic activity, air quality, population mobility levels, and positive cases of COVID-19 obtained through big data. The Bayesian Network model that was constructed manually with the Maximum Spanning Tree algorithm was chosen as the best model with an average 5-cross validation accuracy in predicting four classes of GRDP is 0.83. The best model chosen shows that Indonesia's economic conditions in the pandemic era are directly influenced by the intensity of night light (NTL) which shows economic activity, air quality (AQI), and positive cases of COVID-19. Analysis of parameter learning shows that the economic growth of the Indonesian provinces still tends not to be in line with the maintenance of air quality so that efforts to achieve a green economy condition still have to be improved.
Klasterisasi Wilayah Rentan Bencana Alam Berupa Gerakan Tanah Dan Gempa Bumi Di Indonesia I Nyoman Setiawan; Dewi Krismawati; Setia Pramana; Erwin Tanur
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (437.82 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1538

Abstract

Indonesia is one of the countries prone to natural disasters, such as soil movements and earthquakes. The people of Indonesia have felt various kinds of impacts caused by the disaster, both in the form of losing their jobs, their homes, and even their beloved family members. However, this impact can certainly be minimized with good disaster management. Therefore, the author focuses on the clustering of earthquake-prone areas in Indonesia using Density-based Spatial Clustering of Application with Noise (DBSCAN), Common Nearest Neighbor Clustering (CNN), and K-Medoids. The results of the clustering show that the soil movement-prone cluster formed from the DBSCAN algorithm is centered on the islands of Java and Bali, as well as along the western part of North Sumatra to Lampung, while the earthquake-prone areas formed from the K-Medoids algorithm are spread over the area traversed by the Pacific Ring of Fire.
Time-Series Clustering of the Regencies Hotel Room Occupancy Rate in Indonesia after the COVID-19 Pandemic Ladisa Busaina; Setia Pramana; Satria Bagus Panuntun
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.387

Abstract

After COVID-19 pandemic, Indonesia entering the recovery era. The government provides incentives for tourism industry recovery. This policy was created because the impact of COVID-19 pandemic on tourism industry at each regencies/cities are different. This study investigates a different recovery pattern at regencies/cities across Indonesia. The data of this study consist of the room occupancy rate (ROR) from Badan Pusat Statistik (BPS) Indonesia and from web scraping monthly data from Agoda website between 1 January 2021 until 1 August 2023. The regencies/cities are clustered by ROR category using the dynamic time warping method. The result of study, there is a difference of tourism industry recovery at regencies/cities across Indonesia, which is the speed are fast, medium, or slow. This could be the result of differences of different policy in each regency/city to respond COVID-19 pandemic on their tourism industry.
Co-Authors Cholifa Fitri Annisa Dandy Adetiar Al Rizki Dewi Krismawati Erwin Tanur Farakh Khoirotun Nasida Hizir Sofyan I Nyoman Setiawan Ladisa Busaina Linta Ifada Maulana Faris Mieke Nurmalasari Nasiya Alifah Utami Nensi Fitria Deli Nurtia Nurtia Rina S. Oktari Safrizal Rahman Salwa Rizqina Putri Satria Bagus Panuntun Thosan Girisona Suganda Usman Bustaman Wiwin Srimulyani Yeni Rimadeni