Melola Discovery

← Melola Discovery

Open access Journal SINTA 3

GRAPHICAL REPRESENTATION AND TWO GROUPS ANALYSIS ON DATA MATRIX OF ROBUSTA GREEN CHERRIES PRODUCTION IN TWO HARVEST PERIODS

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 2 (2025) · pp. 1279–1294

DOI
10.30598/barekengvol19iss2pp1279-1294
ISSN
2615-3017, 1978-7227
Published
2025-04-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Several factors that play a role in the productivity of Robusta coffee trees are the influence of pruning techniques and weather elements. This paper discussed the graphical analysis and comparison of two data matrices of Robusta green cherries production, which would enter the ripening process in branch categories for the harvest period in 2023 and 2024. Hypothesis testing on secondary data in the form of daily weather conditions in 2022 and 2023, which include temperature, dew, humidity, wind speed, and cloud cover for the two periods, was significantly different. However, solar radiation and precipitation were not. The data source for each harvest period was primary data, with the object being a sample of 30 trees that were sampled purposively. The research object was in Pagaralam Municipality, South Sumatra. There were 18 variables covering many branch categories based on production year, position, and shape. The PCA (Principal Component Analysis) results on each data matrix show similarities in the dominant variables representing each subspace. The first three PCs in each data matrix for 2023 and 2024 span a subspace and describe the variation of the original data of 77.3% and 68.8%, respectively. The 3rd and 1st-year production branch categories dominate the subspace of each data matrix for 2023 and 2024. Comparison of the two PC subspaces using two groups analysis in 3rd dimension space produces angles of 19.70, 28.80, and 69.10. The bisector components show that the variables that dominate the similarity of the two data matrices are the variables that tend to represent both PC subspaces dominantly. Robusta green cherry production can be represented by the number of secondary branches, which are straight in shape, along with the number of fruit clusters. This study result can be a reference for farmers when considering the composition of the number of branch categories when pruning.

Collaboration network of the authors

32 authors · 105 co-authorship links · 15 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Sriwijaya University
  • Politeknik Negeri Lhokseumawe
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Rifkie PrimarthaSriwijaya University3
Muhammad ArhamiPoliteknik Negeri Lhokseumawe3
Desty RodiahSriwijaya University3
Siddiq MakhalliAffiliation unknown3
Sugandi YahdinSriwijaya University2
Ning EliyatiAffiliation unknown2
Yuli AndrianiSriwijaya University2
Dwi FitriantiSriwijaya University2
Henny Nur SyafitriSriwijaya University2
Fitri Maya PuspitaSriwijaya University2
Endro Setyo CahyonoAffiliation unknown2
Indrawati IndrawatiSriwijaya University1
Rahayu Tamy AgustinSriwijaya University1
Oki DwipurwaniAffiliation unknown1
Shaly Wanda HamidahAffiliation unknown1
Ditia Fitri ArindaAffiliation unknown1
Shania Putri AndhiniAffiliation unknown1
Dian CahyawatiAffiliation unknown1
Evi YulizaSriwijaya University1
Sisca OctarinaSriwijaya University1
Divasanda ArmaliaAffiliation unknown1
Putra BJ BangunAffiliation unknown1
Indrawati IndrawatiAffiliation unknown1
Budi MulyonoAffiliation unknown1
Echa Alda MeliniaAffiliation unknown1
Nidatri Mutiah ZatzahAffiliation unknown1
Zunaidah ZunaidahAffiliation 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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">GRAPHICAL REPRESENTATION AND TWO GROUPS ANALYSIS ON DATA MATRIX OF ROBUSTA GREEN CHERRIES PRODUCTION IN TWO HARVEST PERIODS</dc:title>
	<dc:creator>Irmeilyana, Irmeilyana</dc:creator>
	<dc:creator>Suprihatin, Bambang</dc:creator>
	<dc:creator>Desiani, Anita</dc:creator>
	<dc:creator>Ngudiantoro, Ngudiantoro</dc:creator>
	<dc:creator>Maiyanti, Sri Indra</dc:creator>
	<dc:description xml:lang="en-US">Several factors that play a role in the productivity of Robusta coffee trees are the influence of pruning techniques and weather elements. This paper discussed the graphical analysis and comparison of two data matrices of Robusta green cherries production, which would enter the ripening process in branch categories for the harvest period in 2023 and 2024. Hypothesis testing on secondary data in the form of daily weather conditions in 2022 and 2023, which include temperature, dew, humidity, wind speed, and cloud cover for the two periods, was significantly different. However, solar radiation and precipitation were not. The data source for each harvest period was primary data, with the object being a sample of 30 trees that were sampled purposively. The research object was in Pagaralam Municipality, South Sumatra.&amp;nbsp; There were 18 variables covering many branch categories based on production year, position, and shape. The PCA (Principal Component Analysis) results on each data matrix show similarities in the dominant variables representing each subspace. The first three PCs in each data matrix for 2023 and 2024 span a subspace and describe the variation of the original data of 77.3% and 68.8%, respectively. The 3rd and 1st-year production branch categories dominate the subspace of each data matrix for 2023 and 2024. Comparison of the two PC subspaces using two groups analysis in 3rd dimension space produces angles of 19.70, 28.80, and 69.10. The bisector components show that the variables that dominate the similarity of the two data matrices are the variables that tend to represent both PC subspaces dominantly. Robusta green cherry production can be represented by the number of secondary branches, which are straight in shape, along with the number of fruit clusters. This study result can be a reference for farmers when considering the composition of the number of branch categories when pruning.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-04-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15615</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss2pp1279-1294</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application; 1279-1294</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss2year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15615/9973</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Irmeilyana Irmeilyana, Bambang Suprihatin, Anita Desiani, Ngudiantoro Ngudiantoro, Sri Indra Maiyanti</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>