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All Journal Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Poningsih, P
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Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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Sistem Pendukung Keputusan Penentuan Kenaikan Gaji Karyawan (Kasus PPKS Marihat) Batubara, Ela Roza; Poningsih, P
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 2 (2024): Edisi Juni
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i2.463

Abstract

Determining employee salary increases is an important aspect of human resource management that influences employee motivation and productivity. This process is often complex and requires accurate evaluation of multiple criteria. This research aims to develop a decision support system (DSS) for determining employee salary increases using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method. The MOORA method was chosen because of its ability to handle various criteria and provide objective results. This system is designed to help managers make faster and more precise decisions by considering various factors such as length of service, attendance and competency. The implementation of this system is expected to increase transparency and accuracy in the process of assessing employee salary increases, as well as reducing the potential for bias and subjectivity. Test results show that this system is effective in providing reliable recommendations for employee salary increase decisions. Thus, this MOORA-based decision support system can be a useful tool for companies in managing human resources more efficiently and fairly.
Penerapan Data Mining Algoritma C4.5 Terhadap Prediksi Faktor Menurunnya Hasil Panen Padi Siahaan, Nove Viktor Boyke; Poningsih, P; Suhendro, Dedi; Hartama, Dedy; Suhada, S
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 7, No 1 (2022): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v7i1.412

Abstract

The aim of the study was to predict the factors causing the decline in rice yields. By knowing the factors of declining rice yields, business owners can further evaluate the causes of declining rice yields and then look for solutions on how to overcome them. The method used in this study is the C4.5 Algorithm, the source of the data used is primary data obtained by direct interviews with rice mill owners and farmers in Siborna Village, Kec. Panei Kab. Simalungun Prov. North Sumatra. The variables used include (1) Pests, (2) Rice Grains, (3) Leaf Color, (4) Planting Month and (5) Planting Method. The results obtained 8 rules for the classification of factors causing the decline in rice yields with 3 increasing decision rules and 5 decreasing decision rules with an accuracy rate of 93.33%. It can be concluded that the predictor of the decline in rice yields is based on the connectedness of the Attributes of Planting Month, Pests, Rice Grains, Leaf Color and Planting Methods.
Co-Authors Batubara, Ela Roza Hartama, Dedy Siahaan, Nove Viktor Boyke Suhada, S Suhendro, Dedi