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Jurnal SINTA 2

CONTINUOUS MULTIQUERIES K-DOMINANT SKYLINE ON ROAD NETWORK

JUTI: Jurnal Ilmiah Teknologi Informasi · Vol. 18 No. 2 (2020) · pp. 147–157

DOI
10.12962/j24068535.v18i2.a999
ISSN
2406-8535, 1412-6389
Published
2020-07-31
Publisher
Institut Teknologi Sepuluh Nopember
Language
eng

Abstract

The increasing use of mobile devices makes spatial data worthy of consideration. To get maximum results, users often look for the best from a collection of objects. Among the algorithms that can be used is the skyline query. The algorithm looks for all objects that are not dominated by other objects in all of its attributes. However, data that has many attributes makes the query output a lot of objects so it is less useful for the user. k-dominant skyline queries can be a solution to reduce the output. Among the challenges is the use of skyline queries with spatial data and the many user preferences in finding the best object. This study proposes IKSR: the k-dominant skyline query algorithm that works in a road network environment and can process many queries that have the same subspace in one processing. This algorithm combines queries that operate on the same subspace and set of objects with different k values by computing from the smallest to the largest k. Optimization occurs when some data for larger k are precomputed when calculating the result for the smallest k so the Voronoi cell computing is not repeated. Testing is done by comparing with the naïve algorithm without precomputation. IKSR algorithm can speed up computing time two to three times compared to naïve algorithm.

Collaboration network of the authors

8 authors · 11 co-authorship links · 2 across different organisations

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  • Institut Teknologi Sepuluh Nopember
  • Universitas Pembangunan Nasional Veteran Yogyakarta
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Tohari AhmadInstitut Teknologi Sepuluh Nopember1
Vynska Amalia PermadiUniversitas Pembangunan Nasional Veteran Yogyakarta1
Tosca Yoel ConneryInstitut Teknologi Sepuluh Nopember1
Henning Titi CiptaningtyasInstitut Teknologi Sepuluh Nopember1
Hafara FirdausiInstitut Teknologi Sepuluh Nopember1
Rohana QudusInstitut Teknologi Sepuluh Nopember1

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://juti.if.its.ac.id/index.php/juti/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">CONTINUOUS MULTIQUERIES K-DOMINANT SKYLINE ON ROAD NETWORK</dc:title>
	<dc:creator xml:lang="en">Muttaqi, Syukron Rifail</dc:creator>
	<dc:creator xml:lang="en">Santoso, Bagus Jati</dc:creator>
	<dc:description xml:lang="en">The increasing use of mobile devices makes spatial data worthy of consideration. To get maximum results, users often look for the best from a collection of objects. Among the algorithms that can be used is the skyline query. The algorithm looks for all objects that are not dominated by other objects in all of its attributes. However, data that has many attributes makes the query output a lot of objects so it is less useful for the user. k-dominant skyline queries can be a solution to reduce the output. Among the challenges is the use of skyline queries with spatial data and the many user preferences in finding the best object. This study proposes IKSR: the k-dominant skyline query algorithm that works in a road network environment and can process many queries that have the same subspace in one processing. This algorithm combines queries that operate on the same subspace and set of objects with different k values by computing from the smallest to the largest k. Optimization occurs when some data for larger k are precomputed when calculating the result for the smallest k so the Voronoi cell computing is not repeated. Testing is done by comparing with the naïve algorithm without precomputation. IKSR algorithm can speed up computing time two to three times compared to naïve algorithm.</dc:description>
	<dc:publisher xml:lang="en">Institut Teknologi Sepuluh Nopember</dc:publisher>
	<dc:date>2020-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://juti.if.its.ac.id/index.php/juti/article/view/999</dc:identifier>
	<dc:identifier>10.12962/j24068535.v18i2.a999</dc:identifier>
	<dc:source xml:lang="en">JUTI: Jurnal Ilmiah Teknologi Informasi; Vol. 18, No. 2, July 2020; 147-157</dc:source>
	<dc:source>2406-8535</dc:source>
	<dc:source>1412-6389</dc:source>
	<dc:source>10.12962/j24068535.v18i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://juti.if.its.ac.id/index.php/juti/article/view/999/429</dc:relation>
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