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Pengukuran Tingkat Kapabilitas Sistem Pengolahan Data Survei Pada Manajamen Kinerja Dan Manajemen Data Operasi Menggunakan Dmbok Dan Cobit2019 Di BPS RI

Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 10 No. 3 (2023) · pp. 573–582

DOI
10.25126/jtiik.2023106533
ISSN
2528-6579, 2355-7699
Published
2023-07-01
Publisher
Fakultas Ilmu Komputer, Universitas Brawijaya
Language
id

Abstract

BPS telah membangun salah satu sistem pengolahan data survei yang disebut Integrated Collection System (ICS) dalam upaya melakukan transformasi digital. ICS merupakan sistem untuk mengumpulkan data multimetode yang terdiri dari Pen and Paper Interviewing (PAPI), Computer Assisted Personal Interviewing (CAPI), Computer Assisted Web Interviewing (CAWI), dan Acquisition of Administrative Data. Sistem ini mereformasi cara BPS mengumpulkan data menggunakan berbagai teknologi dan mengintegrasikan data. Sejak diinisiasi tahun 2019, penggunaan ICS semakin bertambah sejalan dengan meningkatnya kebutuhan data yang cepat dan akurat. Untuk menyukseskan transformasi digital, ICS diharapkan memiliki kemampuan manajemen kinerja dan operasi data yang baik maka penelitian ini mengakomodir untuk mengukur tingkat kapabilitas pada ICS dengan proses yang spesifik tersebut. Penelitian ini menggunakan acuan framework dari COBIT 2019, DMBoK dan CMMI. Dari hasil penelitian menunjukkan tingkat manajemen kinerja dari 5 sub domain area, yaitu MEA.01.01-MEA.01.05 masih berada pada tingkat 1, sedangkan hasil penelitian tingkat manajemen operasi data didapatkan bahwa 2 PA (practice areas) berada di level 1, 8 PA berada di level 2, dan 5 PA berada pada level 3. Rekomendasi disusun untuk mengoptimalkan tingkat kapabilitas pada manajemen kinerja dan manajemen operasi data pada ICS sehingga ICS dapat dijalankan dengan baik sesuai dengan target transformasi digital BPS. AbstractAs an effort to carry out digital transformation, BPS has built one of the survey data processing systems known as Integrated Collection System (ICS). ICS is a system for multimode data collection through Pen and Paper Interviewing (PAPI), Computer Assisted Personal Interviewing (CAPI), Computer Assisted Web Interviewing (CAWI), and Acquisition of Administrative Data. ICS reforms the way BPS collects and integrates data using various technologies. Since its initiation in 2019, the use of ICS has increased. With the increasing demand for data, a system that can produce fast and accurate data is extremely necessary. To achieve the goals of digital transformation through the implementation of ICS, it is crucial to have good performance and data operations managements. Therefore, this study accommodates to measure the Capability Level of ICS with these specific processes by applying the frameworks from COBIT 2019, DMBoK, and CMMI as references. From the Performance Management measurement, it was found that the 5 sub-domain areas (MEA.01.01-MEA.01.05) were still at Level 1. Furthermore, the Data Operations Management measurement showed that 2 PA (Practice Areas) were at Level 1, 8 PA were at Level 2, and 5 PA were at Level 3. Based on the results of this study, recommendations have been made to optimize the Capability Level in both Performance Management and Data Operations Management of ICS so that it can be run properly in accordance with the goals of digital transformation of BPS.

Collaboration network of the authors

8 authors · 18 co-authorship links · 9 across different organisations

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  • University of Indonesia
  • Badan Pusat Statistik
  • Ministry of Finance
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Mohamad Faisal ZulmyMinistry of Finance1
Monica Vivi KurniawatiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jtiik.ub.ac.id/index.php/jtiik/en/oai, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="id">Pengukuran Tingkat Kapabilitas Sistem Pengolahan Data Survei Pada Manajamen Kinerja Dan Manajemen Data Operasi Menggunakan Dmbok Dan Cobit2019 Di BPS RI</dc:title>
	<dc:creator xml:lang="id">Wintang, Siti Mawar Rini</dc:creator>
	<dc:creator xml:lang="id">Ruldeviyani, Yova</dc:creator>
	<dc:creator xml:lang="id">Parmiyanto, Joko</dc:creator>
	<dc:creator xml:lang="id">Putra Hulu, Freddy Richard</dc:creator>
	<dc:creator xml:lang="id">Putri, Azanisa</dc:creator>
	<dc:creator xml:lang="id">Sulistiyo, Rifta Dimas</dc:creator>
	<dc:description xml:lang="id">BPS telah membangun salah satu sistem pengolahan data survei yang disebut Integrated Collection System (ICS) dalam upaya melakukan transformasi digital. ICS merupakan sistem untuk mengumpulkan data multimetode yang terdiri dari Pen and Paper Interviewing (PAPI), Computer Assisted Personal Interviewing (CAPI), Computer Assisted Web Interviewing (CAWI), dan Acquisition of Administrative Data. Sistem ini mereformasi cara BPS mengumpulkan data menggunakan berbagai teknologi dan mengintegrasikan data. Sejak diinisiasi tahun 2019, penggunaan ICS semakin bertambah sejalan dengan meningkatnya kebutuhan data yang cepat dan akurat. Untuk menyukseskan transformasi digital, ICS diharapkan memiliki kemampuan manajemen kinerja dan operasi data yang baik maka penelitian ini mengakomodir untuk mengukur tingkat kapabilitas pada ICS dengan proses yang spesifik tersebut. Penelitian ini menggunakan acuan framework dari COBIT 2019, DMBoK dan CMMI. Dari hasil penelitian menunjukkan tingkat manajemen kinerja dari 5 sub domain area, yaitu MEA.01.01-MEA.01.05 masih berada pada tingkat 1, sedangkan hasil penelitian tingkat manajemen operasi data didapatkan bahwa 2 PA (practice areas) berada di level 1, 8 PA berada di level 2, dan 5 PA berada pada level 3. Rekomendasi disusun untuk mengoptimalkan tingkat kapabilitas pada manajemen kinerja dan manajemen operasi data pada ICS sehingga ICS dapat dijalankan dengan baik sesuai dengan target transformasi digital BPS. AbstractAs an effort to carry out digital transformation, BPS has built one of the survey data processing systems known as Integrated Collection System (ICS). ICS is a system for multimode data collection through Pen and Paper Interviewing (PAPI), Computer Assisted Personal Interviewing (CAPI), Computer Assisted Web Interviewing (CAWI), and Acquisition of Administrative Data. ICS reforms the way BPS collects and integrates data using various technologies. Since its initiation in 2019, the use of ICS has increased. With the increasing demand for data, a system that can produce fast and accurate data is extremely necessary. To achieve the goals of digital transformation through the implementation of ICS, it is crucial to have good performance and data operations managements. Therefore, this study accommodates to measure the Capability Level of ICS with these specific processes by applying the frameworks from COBIT 2019, DMBoK, and CMMI as references. From the Performance Management measurement, it was found that the 5 sub-domain areas (MEA.01.01-MEA.01.05) were still at Level 1. Furthermore, the Data Operations Management measurement showed that 2 PA (Practice Areas) were at Level 1, 8 PA were at Level 2, and 5 PA were at Level 3. Based on the results of this study, recommendations have been made to optimize the Capability Level in both Performance Management and Data Operations Management of ICS so that it can be run properly in accordance with the goals of digital transformation of BPS.</dc:description>
	<dc:publisher xml:lang="en">Fakultas Ilmu Komputer, Universitas Brawijaya</dc:publisher>
	<dc:date>2023-07-01</dc:date>
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	<dc:identifier>https://jtiik.ub.ac.id/index.php/jtiik/article/view/6533</dc:identifier>
	<dc:identifier>10.25126/jtiik.2023106533</dc:identifier>
	<dc:source xml:lang="id">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol 10 No 3: Juni 2023; 573-582</dc:source>
	<dc:source xml:lang="en">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol. 10 No. 3: Juni 2023; 573-582</dc:source>
	<dc:source>2528-6579</dc:source>
	<dc:source>2355-7699</dc:source>
	<dc:source>10.25126/jtiik.2023103</dc:source>
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	<dc:rights xml:lang="en">Copyright (c) 2023 Jurnal Teknologi Informasi dan Ilmu Komputer</dc:rights>
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