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Jurnal SINTA 3

IMPLEMENTASI METODE NAÏVE BAYES CLASSIFIER DALAM SISTEM PAKAR DEFISIENSI NUTRISI PADA BALITA

SemanTIK: Teknik Informasi · Vol. 2 No. 1 (2016)

DOI
10.55679/semantik.v2i1.1307
ISSN
2502-8928, 2460-1446
Published
2016-04-18
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng

Abstract

Nutrition deficiency is one of the problems experienced by most children under five years old in Indonesia. This problem appear because the lack of knowledge from parents about nutrition which needed by their children. Regarding with such problem, the researcher then made a diagnose system which provided the information about nutrition deficiency of the children to the people, in order to prevent any problem of nutrition deficiency per se. The system was an expert system of nutrition deficiency using Naïve Bayes Classifier method. This method was developed from Bayes Theorem, where the value of probability from an object was classified based of specific requirements. Some research showed that Naïve Bayes Classifier was the best among other classification methods, so that the researcher employed this method in the research. In the system, the indication of nutrition deficiency was determined based on antropometri table including the data about height, weight, and age as well as additional indication to make a specific result. Then the data of 20 patients were examined using confusion matrix method. The result showed that the system was 90% accurate. Indeed, it proved that the system could be very helpful to make a classification for nutrition deficiency and it could be applied in any of local government clinic and hospital. Keywords— Antropometri, Deficiency, Naïve Bayes

Collaboration network of the authors

40 authors · 129 co-authorship links · 2 across different organisations · showing the 40 most connected

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

  • Universitas Halu Oleo
  • Universitas Gadjah Mada
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Muh YaminUniversitas Halu Oleo10
Jumadil NangiUniversitas Halu Oleo6
Sutardi SutardiUniversitas Halu Oleo6
Isnawaty IsnawatyAffiliation unknown5
Adha Mashur SajiahUniversitas Halu Oleo4
LM Bahtiar AksaraUniversitas Halu Oleo3
Bambang PramonoUniversitas Halu Oleo3
Natalis RansiUniversitas Halu Oleo3
Muhammad Ihsan SaritaUniversitas Halu Oleo2
Isnawaty IsnawatyUniversitas Halu Oleo2
Ika Purwanti NingrumUniversitas Halu Oleo2
SutardiUniversitas Halu Oleo1
Ageng Arya Khrysna DwipanggaUniversitas Halu Oleo1
IsnawatyUniversitas Halu Oleo1
Agrian WahabUniversitas Halu Oleo1
IsnawatyUniversitas Halu Oleo1
Muh Yamin AksaraUniversitas Halu Oleo1
LM. Bahtiar AksaraUniversitas Halu Oleo1
SubardinUniversitas Halu Oleo1
Asri SamsudinUniversitas Halu Oleo1
Agfianto Eko PutraUniversitas Gadjah Mada1
Alif H. La JumaniUniversitas Halu Oleo1
Afriyadin AfriyadinAffiliation unknown1
Anggita Nindya Wisnu WardhanaAffiliation unknown1
Andi PrawirawanAffiliation unknown1
Vega Nataya KinantiAffiliation unknown1
LM Bahtiar AksaraAffiliation unknown1
Muhammad Irwan SyahibAffiliation unknown1
Muhammad YusufUniversitas Halu Oleo1
Muhammad Sadam HusainUniversitas Halu Oleo1
Gusti Made Cahya WiarjayaAffiliation unknown1
Ilmi FaizanUniversitas Halu Oleo1
Esy Anugerah Rahayu KasimUniversitas Halu Oleo1
Miftahul Jannah SalamUniversitas Halu Oleo1
Azkar KumalaAffiliation unknown1
Hardiman HardimanAffiliation unknown1
Subardin SubardinAffiliation 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://ojs.uho.ac.id/index.php/semantik/oai, first harvested 29 Okt 2026, last seen 1 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">IMPLEMENTASI METODE NAÏVE BAYES  CLASSIFIER DALAM SISTEM PAKAR DEFISIENSI  NUTRISI PADA BALITA</dc:title>
	<dc:creator>Putra, Helson Mandala</dc:creator>
	<dc:creator>Aksara, LM Fid</dc:creator>
	<dc:creator>Ramadhan, Rahmat</dc:creator>
	<dc:description xml:lang="en-US">Nutrition deficiency is one of the problems experienced by most children under five years old in Indonesia. This problem appear because the lack of knowledge from parents about nutrition which needed by their children. Regarding with such problem, the researcher then made a diagnose system which provided the information about nutrition deficiency of the children to the people, in order to prevent any problem of nutrition deficiency per se. The system was an expert system of nutrition deficiency using Naïve Bayes Classifier method. This method was developed from Bayes Theorem, where the value of probability from an object was classified based of specific requirements. Some research showed that Naïve Bayes Classifier was the best among other classification methods, so that the researcher employed this method in the research. In the system, the indication of nutrition deficiency was determined based on antropometri  table including the data about height, weight, and age as well as additional indication to make a  specific result. Then the data of 20 patients were examined using confusion matrix method. The result showed that the system was 90% accurate. Indeed, it proved that the system could be very helpful to make a classification for nutrition deficiency and it could be applied in any of local government clinic and hospital.  Keywords— Antropometri, Deficiency, Naïve Bayes </dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2016-04-18</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs.uho.ac.id/index.php/semantik/article/view/1307</dc:identifier>
	<dc:identifier>10.55679/semantik.v2i1.1307</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol 2, No 1 (2016): semanTIK</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:source>10.55679/semantik.v2i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/semantik/article/view/1307/949</dc:relation>
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