Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Sains Materi Indonesia Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Jurnal Penelitian Pendidikan Kreano, Jurnal Matematika Kreatif-Inovatif Jurnal Kimia dan Kemasan JKIE (Journal Knowledge Industrial Engineering) Majalah Ilmiah Bijak Unnes Journal of Mathematics Education Unnes Journal of Mathematics Jurnal PETISI (Pendidikan Teknologi Informasi)
Wuryanto Wuryanto
Tenaga Ahli CV Hycon Andrameda Yogyakarta
Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
ANALISIS TOTAL PREDICTIVE MAINTENANCE DENGAN METODE OEE (OVERALL EQUIPMENT EFFECTIVENESS) GUNA MENINGKATKAN PERFORMA PADA MESIN HUSKY (PT. XY GEMPOL) Wuryanto, Wuryanto; Wahid, Abdul
Journal Knowledge Industrial Engineering (JKIE) Vol 5 No 1 (2018): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v5i1.1921

Abstract

The study was conducted with the aim of: 1. To determine the maintenance conditions and effectiveness of the Husky engine at PT. XY at present.2. To find out the effectiveness level of Husky machines at PT. XY.3. To find out the efficiency before and after the husky engine repair at PT. XY. The method used is Overall Equipment Effectiveness. After conducting research, an overall equipment effectiveness score of 90.95% is obtained. This result has exceeded the world-class standard of 85% but has not reached the company standard of 97%. It is known that the lowest value that causes this low OEE value is a performance rate of 92.8%. What causes the low-performance rate consists of machine, human, environmental, method and material factors. Human and machine factors are the most dominant factors. To improve the performance rate, improvements were made to the machine's start-up and shut-down training to the operator as well as the machine's setting parameters, the application of 5S and GMP audits and the replacement of engine spare parts according to the schedule in the manual book. The results obtained after the improvement showed an increase in performance rate to 102.02%, these results were obtained by increasing the engine cycle time from 9 seconds to 7.5 seconds.
Algoritma Deep Learning untuk Mengukur Tingkat Kesesuaian Rumusan dan Asesmen Capaian Pembelajaran Mata Kuliah Wuryanto, Wuryanto; Thamrin, Husni; Wantoro, Jan
JURNAL PETISI (Pendidikan Teknologi Informasi) Vol. 7 No. 1 (2026): JURNAL PETISI (Pendidikan Teknologi Informasi)
Publisher : Universitas Pendidikan Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36232/jurnalpetisi.v7i1.2675

Abstract

Penelitian ini mengamati kinerja algoritma deep learning untuk mengukur keselarasan antara pertanyaan ujian dengan capaian pembelajaran matakuliah. Keselarasan kedua teks menggambarkan kewajaran proses pembelajaran, sehigga proses terbukti telah berjalan sesuai rencana pembelajaran. Secara umum, proses pembelajaran dimulai dari penyusunan rencana pembelaran, yang menghasilkan dokumen yang mengandung capaian pembelajaran (learning outcome). Selanjutnya proses belajar mengajar dijalankan baik secara daring ataupun luring, dan capaian pembelajaran diuur dengan metode asesmen yang mengukur secara substantif tingkat pencapaian pembelajaran. Riset dimulai dengan pengumpulan data dan preprosesing, dan berlanjut dengan menghitung tingkat kesesuaian menggunakan tiga model deep learning. Ketiga model yang diuji adalah sentence-transformer (model SBERT), denaya/indoSBERT-large (model Denaya), and cahya/bert-base-indonesian-1.5G (model Cahya). Penelitian ini menunjukkan bahwa model Cahya memiliki kinerja terbaik dengan nilai akurasi 0.92 dan F1-score 0.88 dibanding dengan evaluasi oleh manusia. Studi ini menunjukkan bahwa algoritma deep learning dapat diterapkan untuk mereview teks soal dalam kegiatan ujian agar selaras dengan capaian pembelajaran.
Co-Authors Abdul Wahid ANISA KURNIAWATI Ardhi Prabowo Arief Agoestanto Ariyani, Dian Fitri Astatik, Reni Panca Andri Chotim, Moch Darajati, Rusdiana Darmo, Darmo Dewi, Nuriana Rachmani Edy Soedjoko Emi Pujiastuti Hery Sutarto Hidayati, Siti Noertri Husni Thamrin Ilyyana, Kharisma Jan Wantoro Joko Prasetyo Kusni Kusni Kusrianto, Swastika Imas Laura Lahindah, Laura Maharani, Yosela Septi Martyaningrum, Ika Deavy Masrukan Masrukan Maysaroh, Ais Mohammad Asikin Mohammad Ihsan Muhammad Kharis Munawar, Herfi Atrinawati Munawaroh, Zumrotul Ninik Rahayu Purwati, Lina Putri Rizki Amalia, Putri Rizki Ratih Kusumawati Ririn Asmawati Rochmad - Rofienda, Rofienda S Siswanto Siti Agustina, Siti St. Budi Waluya Suhito Suhito Sukestiyarno Sukestiyarno Supraptono, Toton M. Supriyono Supriyono Suratmono, Suratmono Widyaningrum, Ismi Yulianti, Dahniar Eka Yunita, Windha Zaini, Novy Kris