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A CHARACTER-BASED ASSESSMENT MODEL FOR VOCATIONAL HIGH SCHOOLS Edy Supriyadi; Zamtinah Zamtinah; Sunaryo Soenarto; Yuwono Indro Hatmojo
Jurnal Cakrawala Pendidikan CAKRAWALA PENDIDIKAN, VOL. 38, NO. 2, JUNE 2019
Publisher : LPMPP Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (951.055 KB) | DOI: 10.21831/cp.v38i2.24099


The competencies of vocational high school (VHS) graduates, especially in terms of character have not met its standards. This study aims to develop a character-based assessment model for VHS in the form of a guide and procedure. Borg Gall’s (1989) model with the following stages was utilized: (1) needs analysis, (2) planning, (3) development, (4) phase I trial, (5) phase II trial, (6) evaluation of model effectiveness, and (7) final product development. This study involved some experts in the model validation. Trials were done to teachers and principals in eight VHSs in Yogyakarta Special Province, Indonesia in 2017 (first trial), and those from 42 VHSs throughout Java island, Indonesia in 2018 (second trial). Data were collected by questionnaires and interviews and analysed by quantitative and qualitative descriptive statistics. This study suggest that, overall, the model is appropriate and feasible to use, proven by (1) the assessment guide is categorized as ‘very appropriate’ (Mean 3.55; SD .52); (2) assessment procedure achieves an ‘very appropriate’ category (Mean = 3.60; SD = .51); and (3) effectiveness of the assessment model in trial 1 is in the ‘very appropriate’ category (Mean 3.43, and SD .51), and in trial 2 is in the ‘appropriate’ category (Mean 3.38, SD .53).
INOTEKS : Jurnal Inovasi Ilmu Pengetahuan, Teknologi, dan Seni Vol 19, No 1: Februari 2015
Publisher : LPPM UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1166.89 KB) | DOI: 10.21831/ino.v19i1.5150


Community Service Activity (PPM) on training "Power ElectronicsApplications for Induction Motor Settings for vocational teachers in YogyakartaSpecial Region" conducted at the Laboratory of Power Electronics andElectrical Machine Laboratory in the Department of Electrical EngineeringEducation FT UNY. This activity is conducted by the PPM team consisting oflecturers in the Department of Electrical Engineering Education , FT UNY withthe aim of: (1) provide basic knowledge and skills application of power electronics circuits, namely a series of alternating voltage regulator for inductionmotor control; (2) provide knowledge and skills of the induction motor settingsby utilizing one of the instructional media in the form of a variable speed driveunit; (3) do the programming unit of variable speed drives for induction motorsrotation speed controlling; and (4) do the programming variable speed driveunit for braking the motor induction. PPM activities conducted during the three-day meeting with the allocation for 25 hours. The training material covers the theory and practice include:induction motor theory, the theory of series AC drives, AC drive circuit practice, and practice of induction motor control using Altivar 312. This trainingwas attended by 23 people who had a vocational teacher expertise associatedwith this training. Training method used lectures, discussions, question andanswer, demonstration, and practice directly. The achievement of this result can be expressed PPM activities: (1) theparticipants have increased knowledge and skills in power electronics and itsapplications to induction motor settings are indicated by an increase in the valueof the mean pre-test and post-test participants of 48.9 into 76.5; (2 ) of theparticipants felt the benefits of the PPM activity shown from a mean value of 95 96 3.46 questionnaire scores that can be categorized, this activity is very good; and(3) the participants can develop the training materials as a instructional mediafor the control induction motors
Jurnal Penelitian Saintek Vol 11, No 1: April 2006
Publisher : Institute of Research and Community Services, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (7504.068 KB) | DOI: 10.21831/jps.v11i1.5465


Goals   of  this  research   are  implementing    Artificial   Neural   Network (ANN)  algorithm for  load forecasting   and getting  its performance.   The training  data  was takenfrom     UPB  Ungaran.  The performance   can be got through  comparing  ANN test result with the real load at that time. The   research    methodology    usc   experimental     and   design    models approach.    The     phases    of  this   research    were:    I.   analyzing    and identifying    of  need    2.  developing    of  load  forecasting     application software  with  C programming.   3. entering  and  training  the data to get data pattern.The  result  of  this  research.   the  load forecasting  result  by ANN  was close with UPB loadforecasting.    but several  ANN  test result have more deviation  than  UPB. because  number  of training  data  was  less. so the forecasting     pattern    111as not   too   accurate     Beside    that.   another possibility   was  the number  of iteration  must  be more  than  / ()()(J  timesiterations   in  order  to get  more  less  error.   There  was  33,3% of ANN result  that  has  more  less  deviation,   although   the  number   of  training data  was  not  different,  because  that  data  has  no  extrem variation,  sothe pattern   was faster   to be recognized.   Generally,   ANN  will  give  an accurate  pattern  recognation    if the data is valid and the number  of the data is quite enough.
Implementasi Wavelet Haar dan Jaringan Tiruan Pada Pengenalan Pola Selaput Pelangi Mata Yuwono Indro Hatmojo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 3 No 1: Februari 2014
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (192.376 KB)


Abstract—Eye iris pattern recognition is widely used for the purpose of identifying a person's identity. This is can be done because the iris is unique and has a high consistency and stability for years without changing. In this research we will perform iris image pattern recognition by the Haar level 3 wavelet transforms and the LVQ neural networks. This research is expected to know the iris images pattern recognition systems which are more effective; efficient also requires a short time in matching process on this method. The object in this research is the PNG color images with size of 128 x 128 pixels. Parameters used in this research are to varying value of learning rate 0.01 and 0.05, the number of neurons 30 and 40; and epoch value 100 and 200. The values of these parameters will be varied so that the obtained parameter values are the most effective, efficient and a relatively requires short time in the process of the iris image pattern recognition.Based on testing performed, the Haar level 3 wavelet transform combined with LVQ neural network in the process of finding the iris images. The method also gives fast matching process and high accuracy level. Changes in the values of learning rate, number of neurons and epoch value affect network performance. The iris matching process has the fastest time of 2.15 seconds and the higher of accuracy of 87% when the value of learning rate 0.01; the number of neurons 40 as well as the epoch value 100. Intisari—Pengenalan pola selaput pelangi mata atau citra iris mata banyak digunakan untuk tujuan mengidentifikasi identitas seseorang karena iris mata memiliki keunikan, kekonsistenan dan kestabilan yang tinggi bertahun-tahun. Pada penelitian ini akan dilakukan proses pengenalan citra iris mata dengan metode alihragam gelombang singkat wavelet Haar level 3 dan Jaringan syaraf tiruan jenis LVQ, diharapkan akan mengetahui sistem pengenalan pola citra iris mata yang membutuhkan waktu yang singkat dalam proses pencocokannya dengan menggunakan metode tersebut. Obyek dalam penelitian ini adalah citra iris mata berwarna jenis PNG dengan ukuran piksel 128 x 128. Parameter yang digunakan ialah dengan menvariasikan nilai learning rate 0,01 dan 0,05; jumlah neuron 30 dan 40; serta nilai epoh 100 dan 200. Nilai-nilai parameter tersebut divariasikan sehingga akan didapatkan nilai-nilai parameter yang paling efektif dan efisien serta waktu yang relatif singkat dalam proses pengenalan pola citra iris tersebut.Hasil pengujian yang dilakukan pada metode alihragam gelombang singkat jenis Haar level 3 yang dipadukan dengan jaringan syaraf tiruan jenis LVQ dapat berfungsi dengan baik dalam proses pencarian citra iris mata. Metode tersebut memberikan kecepatan pencocokan yang pendek dan tingkat keakuratan yang tinggi. Perubahan nilai learning rate, jumlah neuron dan nilai epoh ternyata mempengaruhi kinerja jaringan. Kecepatan pencocokan citra iris mata memiliki waktu tercepat yaitu 2,15 detik dan tingkat keakuratan atau keberhasilan pencarian citra iris tertinggi yaitu 87% pada saat nilai learning rate 0,01; jumlah neuron 40 serta nilai epoh 100.