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All Journal Indonesian Journal of Electrical Engineering and Computer Science Majalah Ilmiah UPI YPTK
Annisak Izzaty Jamhur
Universitas Putra Indonesia YPTK
Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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Analisa Perancangan Desain Aplikasi Pengelolaan Absensi dan Sistem Penggajian Karyawan pada Daihatsu Capella Medan Cabang Padang Tito; Redha Ramadhani; Annisak Izzaty Jamhur
Majalah Ilmiah UPI YPTK Vol. 27 (2020) No. 1
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jmi.v27i1.31

Abstract

The payroll system is one of the things related to the management of the welfare of the workforce so it must be given special attention by the company in order to achieve its objectives. Salary has a very important meaning for employees because salary is a reflection of the value of the work, and also as an encouragement in a job of their performance, both for the company, the community, and for themselves. In the form of a company's payroll system, employee absence is very influential in taking employee salaries. As in the field research, it can be taken from Daihatsu Capella Medan, Padang Branch. This PT is a company that already exists in several regions in Indonesia
Optimization artificial neural network classification analysis model diagnosis Gingivitis disease Vicky Ariandi; Musli Yanto; Annisak Izzaty Jamhur; Firdaus Firdaus; Riandana Afira
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1648-1656

Abstract

Gingivitis is a disease that can be caused by the buildup of bacteria and plaque caused by leftover food. This disease can attack anyone, especially children who are not aware of maintaining dental and oral health. This study aims to build and optimize the classification analysis model for the diagnosis of Gingivitis. The classification analysis model was built using the artificial neural network (ANN) method which was optimized using fuzzy logic and the multiple linear regression (MRL) method. Optimization with fuzzy aims to develop a pattern of rules in the detection. The MRL method is also used as a process of measuring analysis patterns to ensure the analytical model presents maximum results. The results study indicate that the optimization of fuzzy and MRL methods provides excellent output. These results are based on the fuzzy output which can provide a pattern of 40 rules. The MRL method is can present the level of correlation of each analysis variable with a significant output having an average value of 94.2%. Based on the results of this study, the analysis model that is optimized with the fuzzy logic method and MRL contributes to maximizing the process of diagnosing Gingivitis.
Co-Authors Firdaus Firdaus Musli Yanto Redha Ramadhani Riandana Afira Tito Vicky Ariandi