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Pengembangan modul prakarya dan kewirausahaan materi pengolahan berbasis product oriented bagi peserta didik SMK

Jurnal Pendidikan Vokasi · Vol. 5 No. 3 (2015) · pp. 287–296

DOI
10.21831/jpv.v5i3.6484
ISSN
2476-9401, 2088-2866
Published
2015-11-02
Publisher
ADGVI & Graduate School of Universitas Negeri Yogyakarta
Language
eng

Abstract

Penelitian pengembangan ini bertujuan untuk: (1) mengembangkan model tes minat dan bakat dengan metode jaringan syaraf tiruan; (2) memperoleh hasil uji fungsionalitas tes minat dan bakat yang dikembangkan dengan model Jaringan Syaraf Tiruan (JST); dan (3) memperoleh hasil unjuk kerja dari pengujian tes minat dan bakat dengan model jaringan syaraf tiruan untuk memprediksi potensi siswa bidang robotika. Penelitian ini merupakan penelitian dan pengembangan. Subjek uji coba dibagi menjadi dua, uji coba secara terbatas pada 10 siswa dan uji coba secara luas sebanyak 31 siswa. Hasil dari penelitian pengembangan ini adalah: (1) keberhasilan produk yang dikembangkan dengan beberapa spesifikasi model yaitu; (a) JST dibangun dengan struktur single layer, jawaban tes sebagai masukan dan kesimpulan hasil tes sebagai keluaran; (b) Model pembelajaran JST menggunakan metode perceptron dengan model aktifasi pada JST menggunakan model bipolar (symmetric hard limit); (2) Proses pembelajaran secara terbimbing dengan 10 pola mendapatkan bobot yang dapat membedakan 10 pola dengan tepat, berdasar pengujian secara terbalik. (3) Pengujian secara luas menunjukan produk yang dibangun mampu memprediksi potensi siswa dalam bidang robotika, dengan membedakan 31 pola hasil tes siswa yang berbeda dengan menggunakan bobot yang didapat dari 10 pola pembelajaran. DEVELOPING INTEREST AND TALENT TEST USING ARTIFICIAL NEURAL NETWORK (ANN) TO PREDICT STUDENTS' APTITUDE IN ROBOTICSAbstractThis investigation was aimed: (1) to develop the model of interest and talent test using ANN; (2) to obtain the results of functionality examination of interest and talent test which is developed using ANN; and (3) to obtain the results of the performance from the examination of interest and talent test which is developed using ANN to predict students' aptitude in robotics. This study was a research and development. Subjects were divided into two trials, limited trial was given to 10 trainee students, and wider trial was tested on the 31 students. From the analysis, it can be concluded that: (1) the success of the products developed had some model specifications as follows; (a) ANN was built with a single-layered structure, the answers to the test was the input and the conclusion of the test was as output. (b) ANN learning model used a neural network perceptron method with activation of the ANN using bipolar model (symmetric hard limit). (2) The learning process was guided by the 10 patterns that could be weighted appropriately to distinguish 10 patterns, based on testing in reverse. (3) Extensive testing showed the developed product was able to predict the aptitude of students in the field of robotics, by distinguishing 31 different student examination result pattern using the weights obtained from the 10 patterns of learning.

Keywords

Collaboration network of the authors

40 authors · 78 co-authorship links · 3 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.

  • University of Indonesia
  • Universitas Halu Oleo
  • IPB University
  • Universitas Negeri Padang
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Syaiful IslamiAffiliation unknown2
Anggi Agni ZausAffiliation unknown2
Mahesi Agni ZausAffiliation unknown2
Mustarum MusaruddinUniversitas Halu Oleo1
Eng. Lukas Kano ManggallaAffiliation unknown1
Sartiah YusranAffiliation unknown1
Lymbran TinaAffiliation unknown1
Veronika TebaiAffiliation unknown1
Octavian Bayu Surya HaribansahAffiliation unknown1
Hadi Rahmat PurnamaAffiliation unknown1
Mujiono MujionoAffiliation unknown1
Jayanti Yudha PertiwiAffiliation unknown1
Sri SusilaningsihAffiliation unknown1
Dian Ristanto RistantoAffiliation unknown1
Lilinda KoyimahAffiliation unknown1
Suyatmin SuyatminAffiliation unknown1
Deny IsmantoAffiliation unknown1
Muhammad ErfanAffiliation unknown1
Muhammad Archi MaulydaAffiliation unknown1
Vivi Rahmatul HidayatiAffiliation unknown1
Lalu Hamdian AffandiAffiliation unknown1
Moh. FadliAffiliation unknown1
Dhiana PuspitawatiAffiliation unknown1
Diah Pawestri MaharaniAffiliation unknown1
Mustafa LuthfiAffiliation unknown1
Dodi Jaya WardanaAffiliation unknown1
M. IsmailAffiliation unknown1
Ni Made Novi SuryantiAffiliation unknown1
Gunarhadi GunarhadiAffiliation unknown1
Djono DjonoAffiliation unknown1
Muhammad RomliIPB University1
Ani SuryaniAffiliation unknown1
Yeti WidyawatiAffiliation unknown1
Nizwardi JalinusAffiliation unknown1
Rizki Hadian SaktiAffiliation unknown1
Husnuzhan HusnuzhanAffiliation unknown1
Ganefri GanefriUniversitas Negeri Padang1
Doni Tri Putra YantoAffiliation 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) http://journal.uny.ac.id/index.php/jpv/oai, first harvested 9 Nov 2026, last seen 9 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Pengembangan modul prakarya dan kewirausahaan materi pengolahan berbasis product oriented bagi peserta didik SMK</dc:title>
	<dc:creator>Anggraini, Anita</dc:creator>
	<dc:creator>Sukardi, Sukardi</dc:creator>
	<dc:subject xml:lang="en-US">modul</dc:subject>
	<dc:subject xml:lang="en-US">prakarya dan kewirausahaan</dc:subject>
	<dc:subject xml:lang="en-US">pengolahan</dc:subject>
	<dc:subject xml:lang="en-US">product oriented</dc:subject>
	<dc:subject xml:lang="en-US">SMK</dc:subject>
	<dc:description xml:lang="en-US">Penelitian pengembangan ini bertujuan untuk: (1) mengembangkan model tes minat dan bakat dengan metode jaringan syaraf tiruan; (2) memperoleh hasil uji fungsionalitas tes minat dan bakat yang dikembangkan dengan model Jaringan Syaraf Tiruan (JST); dan (3) memperoleh hasil unjuk kerja dari pengujian tes minat dan bakat dengan model jaringan syaraf tiruan untuk memprediksi potensi siswa bidang robotika. Penelitian ini merupakan penelitian dan pengembangan. Subjek uji coba dibagi menjadi dua, uji coba secara terbatas pada 10 siswa dan uji coba secara luas sebanyak 31 siswa. Hasil dari penelitian pengembangan ini adalah: (1) keberhasilan produk yang dikembangkan dengan beberapa spesifikasi model yaitu; (a) JST dibangun dengan struktur single layer, jawaban tes sebagai masukan dan kesimpulan hasil tes sebagai keluaran; (b) Model pembelajaran JST menggunakan metode perceptron dengan model aktifasi pada JST menggunakan model bipolar (symmetric hard limit); (2) Proses pembelajaran secara terbimbing dengan 10 pola mendapatkan bobot yang dapat membedakan 10 pola dengan tepat, berdasar pengujian secara terbalik. (3) Pengujian secara luas menunjukan produk yang dibangun mampu memprediksi potensi siswa dalam bidang robotika, dengan membedakan 31 pola hasil tes siswa yang berbeda dengan menggunakan bobot yang didapat dari 10 pola pembelajaran. DEVELOPING INTEREST AND TALENT TEST USING ARTIFICIAL NEURAL NETWORK (ANN) TO PREDICT STUDENTS' APTITUDE IN ROBOTICSAbstractThis investigation was aimed: (1) to develop the model of interest and talent test using ANN; (2) to obtain the results of functionality examination of interest and talent test which is developed using ANN; and (3) to obtain the results of the performance from the examination of interest and talent test which is developed using ANN to predict students' aptitude in robotics. This study was a research and development. Subjects were divided into two trials, limited trial was given to 10 trainee students, and wider trial was tested on the 31 students. From the analysis, it can be concluded that: (1) the success of the products developed had some model specifications as follows; (a) ANN was built with a single-layered structure, the answers to the test was the input and the conclusion of the test was as output. (b) ANN learning model used a neural network perceptron method with activation of the ANN using bipolar model (symmetric hard limit). (2) The learning process was guided by the 10 patterns that could be weighted appropriately to distinguish 10 patterns, based on testing in reverse. (3) Extensive testing showed the developed product was able to predict the aptitude of students in the field of robotics, by distinguishing 31 different student examination result pattern using the weights obtained from the 10 patterns of learning.</dc:description>
	<dc:publisher xml:lang="en-US">ADGVI &amp; Graduate School of Universitas Negeri Yogyakarta</dc:publisher>
	<dc:date>2015-11-02</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://journal.uny.ac.id/index.php/jpv/article/view/6484</dc:identifier>
	<dc:identifier>10.21831/jpv.v5i3.6484</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Pendidikan Vokasi; Vol. 5 No. 3 (2015); 287-296</dc:source>
	<dc:source>2476-9401</dc:source>
	<dc:source>2088-2866</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.uny.ac.id/index.php/jpv/article/view/6484/5582</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 1970 Jurnal Pendidikan Vokasi</dc:rights>
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