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All Journal JOIN (Jurnal Online Informatika) JURNAL DINAMIKA VOKASIONAL TEKNIK MESIN Jurnal Informatika Universitas Pamulang JSiI (Jurnal Sistem Informasi) Jurnal Pengembangan Riset dan Observasi Teknik Informatika STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal Perspektif Journal of Machine Learning and Soft Computing Journal of Telecommunication, Electronics and Control Engineering (JTECE) Jurnal Dinamika Informatika (JDI)
Hay's, Riyan Naufal
Universitas Serang Raya
Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Social Sciences Other

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Journal : journal of machine learning and soft computing

 1 
Adhesive Calculation System for Determination of Bonding Glue Needs Using Weighted Product and Lot Sizing Methods Purnamasari, Ita; Setyawan, Agus; Hay’s, Ryan Naufal
Journal of Machine Learning and Soft Computing Vol 1, No 1 (2019): Volume 1, Nomor 1, Maret 2019
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (254.095 KB) | DOI: 10.30656/jlmsc.v1i1.1671

Abstract

The production process that exists at PT. Parkland World Indonesia consists of several parts of the production process, one of which is the production process ofondonding which is used for shoe glue between outsole and upper. Adhesive is a material that is able to connect or unite the two surfaces of separate objects so that it has adequate strength when subjected to the load. This study discusses the making of an adhesive calculation system as a determination of the need for the first time to be ordered, using the weighted product method and lot sizing. The application was developed using the Power Builder programming language with Sybase SQL anyware as its database. With this system will help managers or superiors to know and determine alternative priorities or types of adhesive needs that must be prioritized for adhesive needs to help smooth the production process. To minimize the total cost of adhesive requirements.
Expert System for Diagnosing Types of Diseases in Human Intestine Organs Using the Certainty Factor Method Nurhayatmi, Elis; Muttaqin, Zaenal; Sugiyarta, Ahmad; Hay’s, Ryan Naufal
Journal of Machine Learning and Soft Computing Vol 1, No 2 (2019): Volume 1 Nomor 2, July 2019
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.07 KB) | DOI: 10.30656/jlmsc.v1i2.1676

Abstract

Intestine is one of the organs of the digestive system in the human body which is shaped like pipes and act as gatekeeper food system for our bodies. Many people do not noticed his intestines health because they are too busy with his activity, or lazy to go to the doctor, even when hospital were many visitors there is also felt a lot of to waste time to queue up because they want to get their turn to be checked and a lot of costs to be incurred. This research discusses about creating expert system to diagnose intestinal diseases using certainty factor method.  Applications developed with Visual Basic programming language with MySQL as its database. The results of this research able to do early diagnosis of the symptoms that is felt system users, and provide diagnostic results such as type of disease suffered, prevention and its information.
Co-Authors Adam Maulana Adrean, Reza Agi Febrian Ramadhan Agus Setyawan Agus Setyawan Ahmad Sugiyarta Aminuyati Anharudin, Anharudin Ardi Setyo Anggoro Ayu Purnamasari Bahari, Faisal Rizki Dessy Eka Winungkas Dzuelqarnain, Muhammad Essa Elisa, Dina Ester Wijayanti Eva Safaah Eva Safaah, Eva Febri Lesmana Florentino, Alfredo Jati Guntur Bayu Setaidhi Ita purnamasari, Ita Maya Selvia Lauryn Mustikaningtyas, Andhita Nurhayatmi, Elis Ramadhan, Agi Febrian Ramazanu, Sheena S Siswanto Sihana Sihana Siswanto Siswanto, Siswanto Situmorang, Vincensius Sugiyarta, Ahmad Suhendar, Akip Sumindar, Dadan Sutarti Sutarti Winungkas, Dessy Eka Yan Mitha Djaksana Zaenal Muttaqin