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All Journal Jurnal Teknik Industri Terintegrasi (JUTIN) Indonesian Journal of Informatic Research and Software Engineering PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Nazira, Nanda
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Analisa Algoritma Naïve Bayes Classifier (NBC) Untuk Prediksi Penjualan Alat Kesehatan : Naïve Bayes Classifier (NBC) Algorithm Analysis for Prediction Medical Device Sales Ramadhani, Dian; A’yuniyah, Qurotul; Elvira, Winda; Nazira, Nanda; Ambarani, Isnani; Intan, Sofia Fulvi
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 3 No. 2 (2023): Indonesian Journal of Informatic Research and Software Engineering
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v3i2.941

Abstract

The application of Data Mining in the business scope can be found in the use of Customer Relationship Management (CRM). CRM is a company's effort to manage its sales and customers more optimally. Company Sales Data can be processed into knowledge that can be used to optimize marketing strategies. Purna Karya Scientific is a company engaged in the field of medical/medical devices, laboratory equipment, chemical and dental materials as well as educational aids. In this study has used sales data at PT. After Scientific Work with attributes item code, relation, number of items, and label as class. Then classify medical device sales data by implementing the Naïve Bayes Classifier (NBC) algorithm which can predict sales results by displaying an accuracy value. Implementation was carried out using Google Colab to obtain an accuracy value of 95%, a recall value of 95%, and a precision value of 81%. The results of data on sales of medical devices with 2 classes namely "Selling" and "Not Selling". The resulting value is very good and can be used as a basis for classifying sales of medical devices by analyzing the stock of goods at PT. Full Scientific Work.
Implementation of C4.5 and Support Vector Machine (SVM) Algorithm for Classification of Coronary Heart Disease Anugrah, Muhammad Ridho; Al-Qadr, Nola Ardelia; Nazira, Nanda; Ihza, Nurul
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 1 No. 1: PREDATECS July 2023
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v1i1.805

Abstract

Coronary Heart Disease (CHD) is a chronic disease that is not contagious and can cause heart attacks. This makes CHD one of the diseases that cause the highest mortality globally. CHD can be caused by the main factor, namely an unhealthy lifestyle, so that in an effort to identify and deal with CHD, many studies have been conducted, one of which is the use of information technology. With so many CHD patient data, data mining can be used using. classification methods include C4.5 algorithm and Support Vector Machine (NBC). The C4.5 algorithm is a decision tree-like algorithm that groups attribute values into classes so that it resembles a tree, while SVM is an algorithm that separates data with a hyperplane. This study aims to classify the CHD dataset by comparing the C4.5 and SVM algorithms. So that the best accuracy value for this data is produced, namely the SVM algorithm of 64.51% and followed by the C4.5 algorithm of 64.30%.
Analisis Model Manajemen Permintaan SCM dan Peramalan Penjualan Busana Menggunakan Metode Holt-Winter Exponential Smoothing Tasia, Ena; Nazira, Nanda; A’yuniyah, Qurotul; Fikri , M. Hayatul; Am, Andri Nofiar
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 6 No. 4 (2023): Oktober
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v6i4.20313

Abstract

Sales forecasting is a highly crucial strategy in the business world, as it significantly contributes to enhancing a company's profits. In this context, sales transaction forecasting plays a vital role in assisting business decision-makers in planning effective sales strategies. The utilization of the Holt-Winters Exponential Smoothing method in sales forecasting demonstrates an effective approach. In this study, this method was applied to retail sales data of Muslim clothing from 2021 to 2023. By setting the parameters ? = 0.9, ? = 0.1, and ? = 0.1, the forecasting results indicate a high level of accuracy with low values for Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE), amounting to 29.93, 295.93, and 0.62%, respectively. Consequently, the forecast reveals that the inventory of clothing for periods 13 to 16 is 83, 228, 129, and 115, respectively
Co-Authors Al-Qadr, Nola Ardelia Am, Andri Nofiar Ambarani, Isnani Anugrah, Muhammad Ridho A’yuniyah, Qurotul Elvira, Winda Fikri , M. Hayatul Ihza, Nurul Intan, Sofia Fulvi Ramadhani, Dian Tasia, Ena