TWOFOLD SUBAREA MODEL FOR ESTIMATING COMMUTER PROPORTION IN 10 METROPOLITAN AREAS
Abstract
The metropolitan area is a major contributor to national GDP. The metropolitan area is a center of attraction for many people who come to earn income as commuters. Commuters are people who carry out work activities in the center of the metropolitan area, which are carried out by residents who live in suburban areas around the center of the metropolitan area and commute regularly every day. The availability of commuter statistics from surveys for presentation level down to the smallest administrative level, such as regencies/municipalities, is unreliable. This happens because this level of presentation has poor precision due to insufficient samples due to the Statistics Indonesia survey design for making estimates at the national and provincial levels. It can be done using small area estimation (SAE) to meet increasing data needs, but existing SAE models can often estimate only at one level. To meet data requests more effectively, a model is needed that can estimate several small areas simultaneously. In SAE, one of the SAE models that can do this is the twofold subarea model. The twofold subarea model produces estimates of the proportion of commuters with good precision at the subarea level (regencies/municipalities) and area level (metropolitan area), with the RRMSE percentage value of the estimated proportion of commuters being below 25% for all regions. The results of this research can be used to present commuter data at the regencies/municipalities level and metropolitan area level where there is a lack of samples and become a new opportunity for Statistics Indonesia to increase statistical production in small areas, which is more effective compared to other SAE methods which have so far been used only to estimate one area level.
Downloads
References
[BPS] Badan Pusat Statistik, Kajian Wilayah Metropolitan Patungraya Agung dan Banjarbakula Menggunakan MSA MPD. Jakarta: Badan Pusat Statistik, 2022.
I. Buchori, M. B. A. Yusuf, A. W. Sejati, dan A. Sugiri, “Rancang Bangun Sistem Informasi Keruangan Berbasis Web-Sistem Informasi Geografis (SIG) Untuk Pembangunan Metropolitan Berkelanjutan Studi Kasus: Wilayah Metropolitan Semarang,” dalam Prosiding Seminar Nasional Tata Ruang dan Space# 2, Universitas Hindu Indonesia, 2015.
A. D. Irjayanti, D. W. Sari, dan I. Rosida, “Perilaku Pemilihan Moda Transportasi Pekerja Komuter: Studi Kasus Jabodetabek,” Jurnal Ekonomi Dan Pembangunan Indonesia, vol. 21, no. 2, hlm. 125–147, 2021.
S. Khadijah, D. P. Lubis, dan R. A. Kinseng, “Komunikasi Kelompok Di Kalangan Komuter,” Jurnal Komunikasi Pembangunan, vol. 13, no. 2, 2015.
F. Abdillah, “Fungsi Kereta Api dan Karakteristik Mobilitas Komuter Yogyakarta - Surakarta,” Universitas Gajah Mada, Yogyakarta, 2014.
D. Noviyanti, A. E. Pravitasari, dan S. Sahara, “Analisis perkembangan wilayah provinsi Jawa Barat untuk arahan pembangunan berbasis wilayah pengembangan,” Jurnal Geografi, vol. 12, no. 1, hlm. 57–73, 2020.
T. L. Jones, M. A. J. Baxter, dan V. Khanduja, “A quick guide to survey research,” The Annals of The Royal College of Surgeons of England, vol. 95, no. 1, hlm. 5–7, 2013.
D. Firmansyah, “Teknik Pengambilan Sampel Umum dalam Metodologi Penelitian: Literature Review,” Jurnal Ilmiah Pendidikan Holistik (JIPH), vol. 1, no. 2, hlm. 85–114, 2022.
M. Y. Darsyah dan S. Iriyanto, “Small Area Estimation Untuk Pemetaan Kemiskinan di Kabupaten Demak,” dalam PROSIDING SEMINAR NASIONAL & INTERNASIONAL, 2014.
A. H. Hakim dan N. Hajarisman, “Pendugaan Rata-rata Pengeluaran Per Kapita Menurut Kabupaten/Kota di Provinsi Jawa Barat Melalui Empirical Best Linear Unbiased Prediction dalam Pendugaan Area Kecil,” dalam Bandung Conference Series: Statistics, 2022, hlm. 474–481.
N. Permatasari dan W. Larasati, “Perbandingan Metode SAE EBLUP dan SAE HB Pada Pendugaan Area Kecil (Studi Kasus Pendugaan Kemiskinan di Provinsi Jawa Timur),” Jurnal Statistika Dan Aplikasinya, vol. 6, no. 1, hlm. 96–108, 2022.
F. Apriani, “Pemodelan pengeluaran per kapita menggunakan small area estimation dengan pendekatan semiparametrik penalized spline,” Program Pascasarjana, Institut Teknologi Sepuluh Nopember, Surabaya, 2017.
R. Saadi dan A. Ubaidillah, “Pendugaan Area Kecil Angka Partisipasi Kasar Perguruan Tinggi di Indonesia Menggunakan Model Subarea Twofold dengan Pendekatan Hierarchical Bayes,” dalam Seminar Nasional Official Statistics, 2022, hlm. 123–136.
J. N. K. Rao dan I. Molina, Small area estimation. John Wiley & Sons, 2015.
M. Torabi dan J. Rao, “On small area estimation under a sub-area level model,” J Multivar Anal, vol. 127, hlm. 36–55, 2014.
E. Sunandi, A. Kurnia, K. Sadik, dan K. A. Notodiputro, “A Bayesian Logit-Normal Model in Small Area Estimation,” dalam Journal of Physics: Conference Series, IOP Publishing, 2021, hlm. 012039.
I. Y. Wulansari dan G. Pawitan, “Pendugaan area kecil terhadap proporsi rumah tangga miskin level kelurahan di Kabupaten Sampang menggunakan Hierarchical Bayes (HB) logit normal,” 2014.
I. K. G. Sukarsa dan I. G. K. Gandhiadi, “Pendugaan Proporsi Rumah Tangga Miskin Tingkat Desa di Provinsi Bali dengan Metode Empirical Best Linear Unbiased Prediction dan Bayesian,” BAREKENG: Jurnal Ilmu Matematika dan Terapan, vol. 15, no. 2, hlm. 215–222, 2021.
B. Nandram, “Bayesian predictive inference of a proportion under a twofold small-area model,” J Off Stat, vol. 32, no. 1, hlm. 187–208, 2016.
S. Cai, J. N. K. Rao, L. Dumitrescu, dan G. Chatrchi, “Effective transformation-based variable selection under two-fold subarea models in small area estimation,” Statistics in transition new series, vol. 21, no. 4, hlm. 68–83, 2020.
A. L. Erciulescu, N. B. Cruze, dan B. Nandram, “Model-based county level crop estimates incorporating auxiliary sources of information,” J R Stat Soc Ser A Stat Soc, vol. 182, no. 1, hlm. 283–303, 2019.
E. Eyduran, D. Zaborski, A. Waheed, S. Celik, K. Karadas, dan W. Grzesiak, “Comparison of the predictive capabilities of several data mining algorithms and multiple linear regression in the prediction of body weight by means of body measurements in the indigenous Beetal goat of Pakistan,” Pak J Zool, vol. 49, no. 1, 2017.
P. Mahlangu dkk., “Indirect estimation of structural parameters in South African forests using MISR-HR and LiDAR remote sensing data,” Remote Sens (Basel), vol. 10, no. 10, hlm. 1537, 2018.
Copyright (c) 2024 Yudi Fathul Amin, Indahwati Indahwati, Anang Kurnia
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this Journal agree to the following terms:
- Author retain copyright and grant the journal right of first publication with the work simultaneously licensed under a creative commons attribution license that allow others to share the work within an acknowledgement of the work’s authorship and initial publication of this journal.
- Authors are able to enter into separate, additional contractual arrangement for the non-exclusive distribution of the journal’s published version of the work (e.g. acknowledgement of its initial publication in this journal).
- Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their websites) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published works.
1.gif)
