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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Journal on Information Systems, Technology of Information and Communications (JoISTIC) JOURNAL OF APPLIED INFORMATICS AND COMPUTING KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) IJISCS (International Journal Of Information System and Computer Science) Tematik : Jurnal Teknologi Informasi Komunikasi Teknika Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Rakhmad Maulidi
Jurusan Teknik Informatika, STIKI Malang
Computer Science & IT Control & Systems Engineering Dentistry Education Electrical & Electronics Engineering Engineering Library & Information Science

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Pembagian Task Karyawan Berdasarkan Riwayat Kerja dengan Metode Naive Bayes Mustafidatun Nashihah; Siti Aminah; Rakhmad Maulidi
Journal of Applied Informatics and Computing Vol 6 No 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4602

Abstract

Accuracy and suitability in the division of employee tasks have an important role in the division of employee tasks, in order to obtain a list of criteria that are in accordance with the abilities of employees in one division. PT. Assist Software Indonesia Pratama is currently still in manual division of tasks, namely by sorting out tasks based on features, applications, divisions, and employees who usually do the work. So that it takes a long time in the process of dividing employee tasks, one of the factors is HRD must sort out tasks based on features, applications in order to determine the division and employees who work on the task. The purpose of the research is to facilitate the division of tasks to employees in order to get a list of criteria that are in accordance with the abilities of employees in one division using the Naive Bayes method. So we need a system that can help HRD in distributing employee tasks in accordance with the division and employee capabilities. In this task distribution system using the Multinomial Naïve Bayes Classifier method as a determinant of employee task distribution. The division of employee tasks is based on the tasks that have been done by the previous employee, so that the system can perform the appropriate task division. The system can see the similarities between tasks using the Multinomial Naïve Bayes method as a consideration for determining the divisions and employees who work with the percentage accuracy of 92.5% and 82.5%.
Optimasi Pengendalian Persediaan dengan Metode Reorder Point dalam Pengembangan Aplikasi Kontrol Stok Berbasis Web Rakhmad Maulidi; Prima Listianti
Journal of Applied Informatics and Computing Vol 7 No 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.5204

Abstract

Stock control is a process of keeping track of owned items, their location, and their movements in and out of storage. It helps businesses to manage their inventory efficiently and meet consumer demand while reducing the cost of storing goods. However, online shops like Omah Mode often struggle to meet the demand of consumers due to the lack of a stock control system, resulting in penalties from the marketplace. To solve this problem, a web-based stock control application was designed using the reorder point method. This method determines the minimum stock of goods that should be in the warehouse and the right time to order goods with low stock from suppliers. The purpose of this research is to develop an inventory control system that displays the minimum stock of goods needed in the warehouse. The study used the SDLC Prototype method, consisting of needs analysis, prototype making, prototype evaluation, system coding, system testing, system evaluation, and system use. The results showed that the system created has an 85.71% accuracy rate based on a comparison of manual calculations and system calculations of 28 sample items.
Co-Authors Agnes Nola Sekar Kinasih Bagus Kristomoyo Kristanto Febry Eka Purwiantono Imron, Mokhammad Ali Kusuma, Bibie Hadi Muhammad Bima Indra Kusuma Mustafidatun Nashihah Nando Suchlistio Pramuda Nira Radita Palandi, Jozua Ferjanus Prima Listianti Siti Aminah Yohanes Dwi Listio