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All Journal RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Riset Rumpun Ilmu Teknik (JURRITEK)

Zulia Almaida Siregar

STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

Author-ID : 3567291

Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering

Published : 7 Documents Claim Missing Document

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Application of Multiple Linear Regression Algorithm for Motorcycle Sales Estimation Elvri Rahayu; Iin Parlina; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 1 (2022): March
Publisher : Yayasan Literasi Sains Indonesia

CV. Kerinci Motor is a company engaged in the transportation and automotive sector, especially in the sale of motorcycles. The uncertainty in the number of motorcycle sales at this company has hampered the company's development, because the company cannot take definite policies regarding the sales that occur. Therefore, it is necessary to estimate the sales of motorcycles at this company in the future, so that the management can estimate consumer demand in the future. So that the company is able to serve and provide consumer demand. The estimation algorithm that will be used in this research is Multiple Linear Regression which is one of the data mining methods. This method was chosen because it is able to make an estimate by utilizing data regarding sales. The results of the estimated (estimated) sales of manual motorcycles in 2021 by January are 56,941 or 57 motorcycles in the manual category. This means that there is an increase in the number of manual motorbikes by 5 motorbikes, while the results until May 2021 amounted to 65,710 motorbikes. So it can be concluded that sales of motorcycles at CV. Kerinci Motor have increased sales in the next 5 months.

Backpropagation Model in Predicting the Location of Prospective Freshman Schools for Promotion Optimization Muhammad Fahrur Rozi; Dedy Hartama; Ika Purnama Sari; Rafiqa Dewi; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 1 (2022): March
Publisher : Yayasan Literasi Sains Indonesia

In carrying out promotions, it is also necessary to pay for the manufacture of brochures, banners and other promotional media to provide information to prospective students and attract prospective students to register. Determining the location of the promotion is one of the success factors in promotional activities. In this study, the Artificial Neural Network will be used to predict the location of the promotion. Backpropagation is one of the best artificial neural network methods used for prediction, this method is widely used by researchers in predicting a problem. The data analysis tool used is Matlab or what we call the (Matrix Laboratory) which is a program to analyze and compute numerical data, and Matlab is also an advanced mathematical programming language, which was formed on the premise of using the properties and forms of matrices. From the results of the algorithm used, it is expected to get good accuracy results with some architectural experiments later. So that this research can be an indicator to optimize promotions in the following year in order to attract prospective students to register for AMIK and STIKOM Tunas Bangsa Pematangsiantar

Analysis of K-Means Algorithm for Clustering of Covid-19 Social Assistance Recipients Sri Rahmayani; S Sumarno; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 1 (2022): March
Publisher : Yayasan Literasi Sains Indonesia

During the Covid-19 pandemic, the government provided assistance distributed through each sub-district throughout the province of Indonesia, one of which was the Pahlawan Village in the East Siantar District Pematangsiantar City. So far, the assistance provided by Kelurahan Pahlawan is still done manually, so errors in data collection and distribution of aid may occur. To overcome this problem, a study was carried out by applying the K-Means algorithm to determine the eligibility cluster of Covid-19 beneficiaries, which was carried out by collecting population data according to predetermined attributes. Then the population data will be clustered using the K-Means algorithm and tested using the Rapid Miner application. The clustering results obtained are that cluster 0 consists of 26 data and that cluster 1 consists of 24 data. The recipients of Covid-19 social assistance using the K-Means algorithm show that those entitled to receive the gift are the elderly (elderly). Based on this, it can be concluded that the K-Means Algorithm can be applied to produce more practical information in determining who is entitled to receive assistance

Decision Support System for Giving PDAM Tirtauli Pematangsiantar Employee Bonuses Using the Weighted Product (WP) Method Mira Ariffiani; Irfan Sudahri Damanik; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.346

Employee Bonuses at PDAM Tirtauli Pematangsiantar are given to employees who are selected as employees of the workforce who perform their work in accordance with the profession through the selection process. The process of judgment and decision-making in selection is usually subjective when there are some recipients of employee bonuses who have not much different abilities. Applications created in this research in the form of Decision Support System Employee Bonus Employee PDAM Tirtauli Pematangsiantar Using Weighted Product Method. This application is used to assist the selection in conducting assessments of the competency of the recipients of employee bonus giving and recommendation in decision making. The assessment criteria used include other Attendance, Number of Children, Length of Work, Responsibility, and Loyalty. Weighted Product method is a method of completion by using multiplication to associate attribute values, where the value must be raised first with the attribute weights in question. The system is built using WEB and MySQL programming language for data processing. The result of the research is the application of the recipient of the employee bonus giving to facilitate the process of selecting the recipients of the employee bonus giving according to the need.

Co-Authors Bagus Supranda Dedy Hartama Dewi, Rafiqa Elvri Rahayu Heru Satria Tambunan Iin Parlina Ika Purnama Sari Irfan Sudahri Damanik Mira Ariffiani Muhammad Fahrur Rozi Novita Indriyani Putra Pratama Siregar S Solikhun S Sumarno Sri Rahmayani

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