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All Journal Jurnal Ilmiah Admnistrasi Niaga Indonesian Journal of Artificial Intelligence and Data Mining
Nadiah Nadiah
Politeknik Negeri Sriwijaya
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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ANALISIS PERHITUNGAN PERSEDIAAN BAHAN BAKU UNTUK MEMPERLANCAR PROSES PRODUKSI PADA PD MIE BERKAH KM 5 PALEMBANG Hanifati Hanifati; Elisa Elisa; Nadiah Nadiah
Orasi Bisnis : Jurnal Ilmiah Administrasi Niaga Vol. 9 No. 3 (2013): Orasi Bisnis Edisi IX Mei 2013
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (90.489 KB)

Abstract

This research entitled  Analysis of Raw Material Inventory to Expedite the Production Process in PD Mie Berkah which  located at KM 5 Palembang. It is found that the company had some problems in the minimum stock of flour is not optimal and imprecision calculation the number of orders of  raw materials.  It is would like to know the efforts of the company in meeting the production process  in the company. Data collected through field research, interviews,  and observation.  Data from the inventory reports of flour were analyzed by using the formula of Economic Order Quantity  (EOQ) by Handoko (1995)  and Minimal Inventory by Assauri (1999).  This study relevaled that company had been halted due raw materials that have been depleted and  there is no minimum inventory.  It is concluded that the minimum stock of flour the compaany has not been optimal and uncertainty calculations in a number of orders of raw materials. It is sugested that the company make a purchases that  is economical to make it more prifitable for the company. 
Implementation of Decision Tree Algorithm Machine Learning in Detecting Covid-19 Virus Patients Using Public Datasets Nadiah Nadiah; Sopian Soim; Sholihin Sholihin
Indonesian Journal of Artificial Intelligence and Data Mining Vol 5, No 1 (2022): March 2022
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v5i1.17054

Abstract

The advancement of AI (Artificial Intelligence) technology has been widely implemented in numerous sectors of daily life. Machine Learning is one of the subfields of Artificial Intelligence. Using statistics, mathematics, and data mining, machine learning is developed so that machines may learn by assessing data without being reprogrammed. At this time the world is on alert for the spread of a popular virus, the corona virus. Coronaviruses are part of a family of viruses caused by diseases ranging from the flu. The disease caused by the coronavirus is known as Covid-19. Therefore, to help identify whether a somebody has coronavirus disease based on certain symptoms, a model is created that can classify people with the covid-19 virus using machine learning. The classification methods utilized in this study are decision trees and large-scale machine learning projects. The study employed Python 3.7 as its programming language and PyCharm as its Integrated Development Environment (IDE). Based on the results, the accuracy rate as expected after conducting various trials is 99%.
Co-Authors Elisa Elisa Hanifati Hanifati Sholihin Sholihin Sopian Soim, Sopian