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Open access Jurnal SINTA 3

Penerapan Algoritma Decision Tree C4.5 Pada Layanan Perbaikan Handphone dan Laptop

SemanTIK: Teknik Informasi · Vol. 12 No. 1 (2026) · pp. 89–99

DOI
10.55679/semantik.v12i1.258
ISSN
2502-8928, 2460-1446
Published
2026-04-26
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Perkembangan teknologi informasi telah mendorong akan kebutuhan sistem prediksi biaya perbaikan perangkat elektronik yang cepat dan akurat. Tujuan dari penelitian ini untuk menerapkan algoritma Decision Tree C4.5 pada layanan perbaikan Handphone dan Laptop yang ditujukan bagi pelanggan A+ Service Center Manado. Data yang digunakan mencakup atribut merek perangkat, tipe unit, dan jenis kerusakan, dengan hasil berupa estimasi biaya perbaikan. Metode penelitian mencakup tahap pengumpulan data, preprocessing, penerapan algoritma C4.5, pembentukan model pohon keputusan, serta evaluasi akurasi menggunakan confusion matrix dan Rapid Miner. Hasilnya menunjukkan bahwa algoritma Decision Tree C4.5 dapat menghasilkan model dengan tingkat akurasi sebesar 81,06%, di mana atribut kerusakan menjadi faktor paling utama dalam menentukan estimasi biaya. Implementasi sistem berbasis web memberikan penghematan waktu, karena pelanggan dapat mengestimasi biaya perbaikan tanpa perlu menunggu pemeriksaan teknisi di tempat servis. Penerapan algoritma ini dapat membantu meningkatkan efisiensi layanan dan kepercayaan pelanggan terhadap proses perbaikan perangkat. The development of information technology has driven the need for a fast and accurate system to predict the repair costs of electronic devices. This study aims to apply the Decision Tree C4.5 algorithm to smartphone and laptop repair services for customers of A+ Service Center Manado. The dataset includes attributes such as device brand, unit type, and type of damage, with the output being the estimated repair cost. The research methodology involves several stages, including data collection, preprocessing, application of the C4.5 algorithm, decision tree model construction, and accuracy evaluation using a confusion matrix. The results show that the Decision Tree C4.5 algorithm can produce a model with an accuracy rate of 81.06%, where the damage type attribute is the most dominant factor in determining the co-st estimation. The implementation of the web-based system provides time efficiency, allowing customers to estimate repair costs without waiting for on-site technician inspection. The application of this algorithm helps improve service efficiency and enhances customer trust in the repair process.

Keywords

Collaboration network of the authors

11 authors · 15 co-authorship links

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

  • Manado State University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Arsila DuauluManado State University1
Kristofel SantaManado State University1
Nibertin ZaiManado State University1
Alfiansyah A HasibuanManado State University1
Tesalonika Natalia RondonuwuManado State University1
Irene Realyta Halldy Trosi TangkawarowManado State University1
Sweet KumontoyManado State University1
Sondy Campvid KumajasManado State University1

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://semantik.uho.ac.id/index.php/journal/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Penerapan Algoritma Decision Tree C4.5 Pada Layanan Perbaikan Handphone dan Laptop</dc:title>
	<dc:creator>Supit, Mesiasi Anjelika</dc:creator>
	<dc:creator>Kenap, Audy Aldrin</dc:creator>
	<dc:creator>Maramis, Glenn David Paulus</dc:creator>
	<dc:subject xml:lang="en-US">Decision Tree C4.5</dc:subject>
	<dc:subject xml:lang="en-US">Data Mining</dc:subject>
	<dc:subject xml:lang="en-US">Estimasi Biaya</dc:subject>
	<dc:subject xml:lang="en-US">Service Handphone dan Laptop</dc:subject>
	<dc:description xml:lang="en-US">Perkembangan teknologi informasi telah mendorong akan kebutuhan sistem prediksi biaya perbaikan perangkat elektronik yang cepat dan akurat. Tujuan dari penelitian ini untuk menerapkan algoritma Decision Tree C4.5 pada layanan perbaikan Handphone dan Laptop yang ditujukan bagi pelanggan A+ Service Center Manado. Data yang digunakan mencakup atribut merek perangkat, tipe unit, dan jenis kerusakan, dengan hasil berupa estimasi biaya perbaikan. Metode penelitian mencakup tahap pengumpulan data, preprocessing, penerapan algoritma C4.5, pembentukan model pohon keputusan, serta evaluasi akurasi menggunakan confusion matrix dan Rapid Miner. Hasilnya menunjukkan bahwa algoritma Decision Tree C4.5 dapat menghasilkan model dengan tingkat akurasi sebesar 81,06%, di mana atribut kerusakan menjadi faktor paling utama dalam menentukan estimasi biaya. Implementasi sistem berbasis web memberikan penghematan waktu, karena pelanggan dapat mengestimasi biaya perbaikan tanpa perlu menunggu pemeriksaan teknisi di tempat servis. Penerapan algoritma ini dapat membantu meningkatkan efisiensi layanan dan kepercayaan pelanggan terhadap proses perbaikan perangkat.
The development of information technology has driven the need for a fast and accurate system to predict the repair costs of electronic devices. This study aims to apply the Decision Tree C4.5 algorithm to smartphone and laptop repair services for customers of A+ Service Center Manado. The dataset includes attributes such as device brand, unit type, and type of damage, with the output being the estimated repair cost. The research methodology involves several stages, including data collection, preprocessing, application of the C4.5 algorithm, decision tree model construction, and accuracy evaluation using a confusion matrix. The results show that the Decision Tree C4.5 algorithm can produce a model with an accuracy rate of 81.06%, where the damage type attribute is the most dominant factor in determining the co-st estimation. The implementation of the web-based system provides time efficiency, allowing customers to estimate repair costs without waiting for on-site technician inspection. The application of this algorithm helps improve service efficiency and enhances customer trust in the repair process.</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:date>2026-04-26</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://semantik.uho.ac.id/index.php/journal/article/view/258</dc:identifier>
	<dc:identifier>10.55679/semantik.v12i1.258</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol. 12 No. 1 (2026): Vol. 12 No. 1 (2026): SemanTIK Teknik Informasi; 89-99</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://semantik.uho.ac.id/index.php/journal/article/view/258/66</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Mesiasi Anjelika Supit, Audy Aldrin Kenap, Glenn David Paulus Maramis</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>