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All Journal JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Recent in Engineering Science and Technology
Ga, Jonri Lomi
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Humanities Chemical Engineering, Chemistry & Bioengineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Other

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Pengembangan Produk Unggulan Daerah Berorientasi Ekspor Pada Industri Kerajinan Batu Alam Nusa Tenggara Timur Amheka, Adrianus; Ga, Jonri Lomi; Noach, Robert M.
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 3 No 1 (2019): Vol 3 No 1 (2019): JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Forum Dosen Indonesia JATIM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (293.22 KB) | DOI: 10.36339/je.v3i1.180

Abstract

Regional superior products in NTT Province are currently the main pillars of the people's economy. Through the development program of superior products of export-oriented regions in the natural stone handicraft industry in UD Pesona Batu Alam, it is able to increase productivity, turnover and other assets. The support of Kupang State Polytechnic through the improvement of innovation-based mechanization on the types and kinds of production needed by the community through craftsmen in UD. Pesona Batu Alam is very necessary. Measured activities include the development of rock type designs through a variety of forms to attract tastes of domestic and foreign customers. The implementation methods that are carried out include the manufacture and application of cutting tool technology and portable stone grading screw systems to be part of the innovation targeted in this service program. The characteristics of the tool are designed in accordance with the conditions of natural stone and NTT Province's distinctive limestone products. The results of this service program are able to improve the quality of products, including the use of by-products in addition to being able to stimulate sales and marketing between islands and between neighboring countries.
Machine Predictive Maintenance by Using Support Vector Machines Assagaf , Idrus; Sukandi, Agus; Abdillah, Abdul Azis; Arifin, Samsul; Ga, Jonri Lomi
Recent in Engineering Science and Technology Vol. 1 No. 01 (2023): RiESTech Volume 01 No. 01 Years 2023
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v1i01.6

Abstract

Predictive Maintenance (PdM) is an adoptable worth strategy when we deal with the maintenance business, due to a necessity of minimizing stop time into a minimum and reduce expenses.  Recently, the research of PdM is now begin in utilizing the artificial intelligence by using the machine data itself and sensors. Data collected then analyzed and modelled so that the decision can be made for the near and next future. One of the popular artificial intelligences in handling such classification problem is Support Vector Machines (SVM). The purpose of the study is to detect machine failure by using the SVM model. The study is using database approach from the model of Machine Learning. The data collection comes from the sensors installed on the machine itself, so that it can predict the failure of machine function. The study also to test the performance and seek for the best parameter value for building a detection model of machine predictive maintenance The result shows based on dataset AI4I 2020 Predictive Maintenance, SVM is able to detect machine failure with the accuracy of 80%.
Co-Authors Abdillah, Abdul Azis Agus Sukandi Amheka, Adrianus Assagaf, Idrus Noach, Robert M. Samsul Arifin