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All Journal Cyberspace: Jurnal Pendidikan Teknologi Informasi
Denni Kurniawan
Universitas Budi Luhur
Computer Science & IT Education Other

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SISTEM PENDUKUNG KEPUTUSAN DALAM PENILAIAN PRESTASI KERJA MENGGUNAKAN FUZZY-AHP DAN SAW Denni Kurniawan; Catur Nugroho
CYBERSPACE: Jurnal Pendidikan Teknologi Informasi Vol 3, No 2 (2019)
Publisher : UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (879.469 KB) | DOI: 10.22373/cj.v3i2.5359

Abstract

Employee appraisal is one of the company's efforts to evaluate employee performance and productivity. As the result, the company can also give awards to employees who are considered gives high contribution to company.  However, it is not easy to measure employee performance, because most them only based on the leaders valuation which is subjective and do not based on standards. The objective of this study is to develop a system to assess employee performance by using a combination of Fuzzy Logic, Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The AHP is a method of weighting in based on multi-criteria decisions. This method uses a pairwise comparison matrix to  calculate the weight value. The Fuzzy logic is used to overcome the problem, where the AHP method is indicated still have subjectivity in criteria evaluation. After calculation based on combination of Fuzzy-AHP methods, the final result of employee performance will determined by using SAW method. The employee with the highest weight value will considered as the most productive employee and also gives the best performance in the company.
Optimization Sentimen Analysis using CRISP-DM and Naive Bayes Methods Implemented on Social Media Denni Kurniawan; Muhammad Yasir
CYBERSPACE: Jurnal Pendidikan Teknologi Informasi Vol 6, No 2 (2022)
Publisher : UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/cj.v6i2.12793

Abstract

Freedom of expression on social media Twitter not always give positive value, because sometimes can contains negative things such as fake news, spreads hate speech, and racism, where these kinds of tweet can be categorized as an act of Cyberbullying. Where this cyberbullying tends to increase every time. The aim of this study is to use the Naïve Bayes method in classifying types of sentiment on Twitter. The keyword used is Saipul Jamil, and the tweet was taken in September 2021. A total of 18,067 tweets were collected and then they will be labelled with a positive or negative value. This study also uses the CRIPS-DM method which is consist of Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment stages. The results of this study obtained the value of Accuracy (85.6%), Negative Recall (82.1%), Positive Recall (90.23%), and Negative Precision (91.76%) Positive Precision (79.18%).
Co-Authors Catur Nugroho Muhammad Yasir