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All Journal Jurnal Pendidikan Vokasi Jurnal Edukasi Elektro JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Edutech ELINVO (Electronics, Informatics, and Vocational Education) PEDAGOGIA Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Journal of Research in Social Science and Humanities Jurnal Media Computer Science Journal of Information Technology and Education (JITED)

Nuryake Fajaryati

Universitas Negeri Yogyakarta

Author-ID : 263286

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Social Sciences Other

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Evaluasi pelaksanaan teaching factory SMK di Surakarta Fajaryati, Nuryake
Jurnal Pendidikan Vokasi Vol. 2 No. 3 (2012): November
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v2i3.1040

Evaluasi pelaksanaan teaching factory SMK di Surakarta bertujuan untuk mengetahui bagaimana proses pelaksanaan teaching factory SMK di Surakarta. Penelitian ini merupakan penelitian deskriptif dengan pendekatan evaluasi model formatif-sumatif oleh Scriven yang menekankan pada evaluasi formatif. Populasi penelitian adalah semua SMK di Surakarta yang menjalankan teaching factory berjumlah 9 sekolah dan respondennya adalah 81 guru pengampu kompetensi keahlian yang menjalankan teaching factory di sekolah tersebut. Hasil penelitian menunjukkan bahwa pelaksanaan teaching factory SMK di Surakarta ditinjau dari kegiatan pembelajaran dinyatakan sangat baik (17,28%) oleh 14 guru, baik (39,51%) oleh 32 guru, tidak baik (25,93%) oleh 21 guru, dan sangat tidak baik (17,28%) oleh 14 guru. Sedangkan hasil pelaksanaan teaching factory SMK di Surakarta ditinjau dari proses produksi dinyatakan sangat baik (14,81%) oleh 12 guru, baik (27,16%) oleh 22 guru, tidak baik (44,44%) oleh 36 guru, dan sangat tidak baik (13,58%) oleh 11 guru. AN EVALUATION OF SMK TEACHING FACTORY IN SURAKARTAAn evaluation of the teaching factory implementation in vocational high schools (VHSs) in Surakarta aims to find out he teaching factory implementation process in VHSs in Surakarta. This was a descriptive study with the formative-sumative evaluation model by Scriven emphasizing on the formative evaluation. The population comprised all 9 VHSs in Surakarta carrying out the teaching factory. The respondents were 81 teachers involved in the teaching factory. The results of the evaluation show that the teaching factory in VHSs in Surakarta for the learning activity component is very good (17.28%, 14 respondents), good (39.51%, 32 respondents), poor (25.93%, 21 respondents), and very poor (17.28%, 14 respondents), and for the production proccess component it is very good (14.81%, 12 respondents), good (27.16%, 22 respondents), poor (44.44%, 36 respondents), and very poor (13.58%, 11 respondents).

STUDI PENELUSURAN (TRACER STUDY) TERHADAP ALUMNI PROGRAM STUDI PENDIDIKAN TEKNIK INFORMATIKA JURUSAN PENDIDIKAN TEKNIK ELEKTRONIKA FAKULTAS TEKNIK UNIVERSITAS NEGERI YOGYAKARTA Fajaryati, Nuryake; Pambudi, Sigit; Priyanto, Priyanto; Sukardiyono, Totok; Utami, Athika Dwi Wiji; Destiana, Bonita
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 1 No. 1 (2015): November 2015 (Consist of 9 Articles)
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Penelitian tracer study ini bertujuan untuk memperoleh gambaran lama masa tunggu alumni sampai mendapatkan pekerjaan, mendeskripsikan penilaian alumni mengenai penyelenggaraan dan mutu layanan program yang ada di Program Studi Pendidikan Teknik Informatika FT UNY dan mendeskripsikan penilaian pengguna alumni terhadap kompetensi lulusan Pendidikan Teknik Informatika FT UNY. Penelitian ini termasuk jenis penelitian deskriptif kualitatif (qualitative research) melalui pendekatan survei mencakup tiga tahapan: 1) pengembangan konsep dan instrumen; 2) pengumpulan data; dan 3) analisa data dan pelaporan. Metode sampling dengan cara random, dengan proporsi 30% secara proporsional sesuai dengan jumlah lulusan. Jenis data yang dikumpulkan dalam penelitian ini adalah data primer yang diperoleh langsung dari alumni dan pengguna alumni melalui kuesioner yang terstruktur. Penyebaran kuesioner dilakukan secara online melalui Google docs dan penyebaran secara langsung kepada alumni atau pengguna alumni yang diketahui dengan jelas keberadaannya. Pengumpulan data lapangan dimulai pada Mei 2015 hingga Agustus 2015.Hasil penelitian menunjukkan sebagian besar alumni Program Studi Pendidikan Teknik Informatika mendapatkan pekerjaan dengan masa tunggu kurang dari 6 bulan yaitu sebanyak 88%, sementara lainnya membutuhkan waktu selama lebih dari 18 bulan sebanyak 7%, rentang 6 - 12 bulan sebanyak 3%, dan rentang 13 - 18 bulan sebanyak 2%. Mengenai penyelenggaraan dan mutu layanan, alumni memberikan penilaian baik dari persepsi semua aspek, namun dibutuhkan peningkatan dari segi SDM maupun fasilitas sarana dan prasarana. Pengguna alumni menilai bahwa kompetensi lulusan Program Studi Pendidikan Teknik Informatika dari segi aspek integritas, profesionalisme, penggunaan TI, komunikasi, kerjasama tim, dan pengembangan diri sangat baik, namun masih kurang dalam penggunaan bahasa, khususnya bahasa Inggris.

Studi Penelusuran Alumni Teknik Elektronika D3 sebagai Upaya Peningkatan Mutu Penyelenggaraan Program Studi Fajaryati, Nuryake; Santoso, Djoko; Waluyanti, Sri; Baiti, Ahmad Awaluddin
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 3 No. 1 (2018): May 2018
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Penelitian ini bertujuan untuk mengetahui bagaimana profil lulusan Profi D3 Teknik Elektronika, penilaian alumni mengenai mutu penyelenggaraan program yang ada di Prodi D3 Teknik Elektronika, dan penilaian stakeholders terhadap kompetensi lulusan prodi D3 Teknik Elektronika.Penelitian ini merupakan penelitian penelusuran alumni dengan pendekatan analisis deskriptif kuantitatif.pelaksanaan tracer study dilakukan dengan konsep tahapan survey menurut Schomburg, yaitu tahap 1 pengembangan konsep dan instrumen, tahap 2 pengumpulan data, dan tahap 3 analisa data serta penulisan laporan. Sumber data dalam penelitian ini adalah 55 orang alumni Prodi D3 Teknik Elektronika dan 10 orang pengguna alumni (stakeholders) Metode pengumpulan data dilakukan dengan penyebaran kuesioner kepada alumni dan stakeholders secara langsung dan melalui google doc. Metode analisis data yang dipakai dalam penelitian ini adalah teknik analisis deskriptif kuantitatif dan evaluatif. Kuesioner penilaian penyelenggaraan prodi D3 Teknik Elektronika oleh alumni dan penilaian kompetensi alumni oleh stakeholders diberikan lima alternatif jawaban, yaitu sangat baik, baik, cukup baik, kurang baik, dan tidak baik.Hasil penelitian menunjukkan bahwa rerata IPK lulusan prodi D3 Teknik Elektronika untuk angkatan 2008 – 2014 adalah 3,27 dan lama masa studi 3 tahun 8 bulan. Sebagian besar masa tunggu alumni dalam mendapatkan pekerjaan ± 3 bulan dan bekerja sebagai karyawan swasta dan teknisi swasta dengan pendapatan 1-3 juta/bulan. Penilaian alumni terhadap layanan administrasi, aspek pembelajaran, pengalaman belajar, dan keterlibatan dalam penelitian dan PPM termasuk dalam kategori baik. Sedangkan penilaian alumni tentang fasilitas perkuliahan tergolong cukup baik. Penilaian stakeholders terhadap alumni dalam hal integritas, keahlian bidang ilmu, kemampuan mengatasi permasalahan, kemampuan berkomunikasi, dan bekerjasama termasuk dalam kategori baik. sedangkan kemampuan alumni dalam berbahasa inggris tergolong cukup baik.

Reosquido Desalinasi Metode Evaporasi dengan Ultraviolet Berbasis Mikrokontroller Azis, Muhammad Abdul; Fajaryati, Nuryake
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 3 No. 2 (2018): November 2018
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

This research aims to create a Reosquido desalination tool for evaporation methods using a microcontroller. This tool can control the temperature to speed up the evaporation process in producing fresh water. The method applied to Reosquido desalination uses Evaporation. The first process before evaporation is the detection of temperature in sea water that will be heated using an element heater. The second process of temperature measurement is to turn off and turn on the Arduino Uno controlled heater, when the temperature is less than 80 ° then the heater is on. The third process is evaporation during temperatures between 80 ° to 100 °, evaporation water sticks to the glass roof which is designed by pyramid. Evaporated water that flows into the reservoir is detected by its solubility TDS value. The fourth process is heater off when the temperature is more than 100 °. Based on the results of the testing, the desalination process using a microcontroller controlled heater can speed up the time up to 55% of the previous desalination process tool, namely manual desalination prsoes without using the heater element controlled by the temperature and controlled by a microcontroller which takes 9 hours. Produces fresh water as much as 30ml from 3000ml of sea water, so that it can be compared to 1: 100.

Singular Value Decomposition in Machine Leaning for Image Compression in Vocational Tourism Batik Archiving Sudira , Putu; Sahria, Yoga; Fajaryati, Nuryake; Hakim, Septian Rahman; Nursusanto, Stevanus Widuri; Mhd Salim, Mohamad Hidir; Astuti, Rahayu Fuji
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 31 No. 2 (2025): (October)
Publisher : Faculty of Engineering, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jptk.v31i2.95700

The digital archiving of batik products in vocational tourism environments requires efficient image compression techniques that maintain critical visual information, including complex motifs, color patterns, and texture details. This study aims to investigate the application of Singular Value Decomposition (SVD) as a machine learning based approach for image compression in the digital archiving of batik products from the Sundhullangit Batik Vocational Tourism Village. An experimental research design was adopted using digital batik images obtained through direct image acquisition. The research stages comprised image pre-processing, image compression using a truncated Singular Value Decomposition model with varying rank values, and reconstruction of the compressed images. The performance of the compression model was evaluated using objective image quality metrics, namely Mean Squared Error, Peak Signal-to-Noise Ratio, and Structural Similarity Index, while compression efficiency was measured using the compression ratio. The results indicate that higher rank values enhance reconstructed image quality, reflected by lower reconstruction error and higher structural similarity, but reduce compression efficiency. Conversely, lower rank values achieve higher compression ratios at the cost of reduced visual fidelity. Overall, the findings demonstrate that Singular Value Decomposition offers an effective balance between image quality preservation and data size reduction. This study concludes that the proposed method is suitable for supporting sustainable and high-quality digital archiving of batik products within vocational tourism-based cultural heritage systems.

Artificial Intelligence for Competency-Based Assessment in Vocational Education Alfred Michel Mofu; Praramadini Sari; Vetin Yumita Saroh; Nuryake Fajaryati; Pipit Utami; Yoga Sahria
Journal of Research in Social Science and Humanities Vol 5, No 3 (2025)
Publisher : Utan Kayu Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/jrssh.v5i4.564

The rapid adoption of artificial intelligence in education has increasingly influenced research in technical and vocational education and training (TVET). However, much of the existing literature focuses primarily on prediction-oriented learning analytics rather than on competency-based assessment frameworks that are central to vocational education. This study investigates how artificial intelligence has been applied within vocational education research and examines the extent to which competency-based assessment principles are represented in literature. A systematic literature review was conducted using the PRISMA protocol, combined with layered bibliometric mapping using VOSviewer to explore structural and conceptual patterns in the research field. The dataset was constructed from Scopus-indexed journal articles published between 2020 and 2025. Bibliometric results indicate that machine learning, deep learning, and educational data mining dominate the research landscape, while competency constructs remain relatively peripheral. The thematic synthesis further reveals limited attention to authentic performance modeling and explainable artificial intelligence within assessment contexts. In response to these gaps, the study proposes a conceptual framework for AI-supported competency-based assessment in vocational education that integrates construct-grounded modeling, authentic performance analytics, and explainable decision architectures. The framework provides a conceptual foundation for aligning artificial intelligence technologies with competency-oriented evaluation in vocational learning environments.

Multimodal Learning in AIoT Systems: Sensor Fusion and Vision-Based Intelligence Wulanjari, Agnes Prima; Dymyati, Ria; Indar Bismoko, Indar Bismoko; Fajaryati, Nuryake; Utami, Pipit
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.11040

This study evaluates the effectiveness of multimodal learning in Artificial Intelligence of Things (AIoT) systems, focusing on the integration of sensor fusion and computer vision for classification tasks. A systematic review and meta-analysis were conducted on studies published between 2020 and 2025. Thirteen studies met the inclusion criteria; however, only six provided comparable quantitative data due to inconsistent baseline reporting and evaluation practices. The results indicate that multimodal approaches generally improve accuracy compared to unimodal baselines when comparable evaluations are available, with an average increase of 8.88% (95% CI: 5.33%–12.44%, p < 0.001). High heterogeneity was observed, influenced by domain, sensor configuration, and model architecture. These findings suggest that multimodal effectiveness is conditional and depends on modality complementarity, fusion strategy, and system-level constraints

Co-Authors Aanggraini, Yussi Alfred Michel Mofu Anggraini, Yussi Athika Dwi W Athika Dwi Wiji Utami Azis, Muhammad Abdul Baiti, Ahmad Awaluddin Bonita Destiana Budiyono Budiyono Dieni Nugrahini Djoko Santoso Dymyati, Ria Felestin Felestin, Felestin Ferry Jie, Ferry Indar Bismoko, Indar Bismoko Ismail, Mohd Erfy Maneetien, Nopadon Mhd Salim, Mohamad Hidir Muhammad Akhyar Muhammad Irfan Luthfi Muslikhin Nurkhamid Nursusanto, Stevanus Widuri Pambudi, Sigit Pipit Utami Ponco Wali Pranoto Pramudi Utomo Praramadini Sari Priyanto Priyanto Putra, Abdul Aziz Sidiq Tri Putu Sudira Putu Sudira Rafisya, Annisa Risqi Rahayu Fuji Astuti Rinawan, Rangga Bayu Septian Rahman Hakim Sri Waluyanti Sudira , Putu Totok Sukardiyono Vetin Yumita Saroh Wiranto Wiranto Wulanjari, Agnes Prima Yoga Sahria Yoga Sahria Yuwana, Rahmat Ageng

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