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Andini Putri Riandani
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SAINTEK
Published by Universitas Pelita Bangsa
ISSN : -     EISSN : 29623545     DOI : 10.37366/SAINTEK
Core Subject : Science, Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering
Prosiding Sains dan Teknologi (SAINTEK) merupakan wadah publikasi dari hasil penelitian yang telah dipresentasikan pada Seminar Nasional Sains dan Teknologi (SAINTEK) yang diselenggarakan setiap tahun oleh Fakultas Teknik Universitas Pelita Bangsa. Penelitian yang dipublikasikan bersifat multi-disiplin dalam ruang lingkup Teknik tentang analisa dan implementasi perkembangan teknologi. 
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 452 Documents
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Penerapan Data Mining Menggunakan Algoritma K-Means Clustering Untuk Analisa Penjualan Di Toko Nibras House Kertaharja Muhamad Fatchan; Dhea Tara Monika
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Abstract Nibras House Kertaharja is a retail store that sells of muslim clothes, but the owner doesn’t know what products are best selling in his store. Data on sales, purchases, expenses at the store are not well organized, so the data is only as an archive. One of the way to find out which products are selling less and best selling based on available data is through the use of Data Mining. Data Mining can assist in data processing, one of the technique that is often used is clusterization using the K-means algorithm. The purpose of this research is to help owners find out what products are best selling at Nibras House Kertaharja. The data used in this study is Nibras House Kertaharja sales from March - June 2023 as many as 243 data in excel. The data will be grouped into 3 clusters which are categorized as less in demand, in demand, and very in demand. The data is processed in the RapidMiner and the results obtained based on cluster category are cluster_0 with 204 products, cluster_1 with 35 products, cluster_2 with 4 products.
Penerapan Data Mining Menggunakan Metode Naïve Bayes Untuk Menentukan Faktor Yang Mempengaruhi Kelulusan Dan Ketidaklulusan Mahasiswa Di Universitas Pelita Bangsa Edy Widodo; Ditya Lambang Setyawan
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Data mining is the process of discovering patterns from datasets to generate information that can be used for prediction based on historical data. This study aims to analyze the factors influencing student graduation and non-graduation at Universitas Pelita Bangsa using the Naïve Bayes method. Data processing was conducted through manual calculations, Microsoft Excel, and RapidMiner, producing consistent evaluation results with an accuracy of 68.18%, precision of 33.33%, and recall of 16.67%. The findings indicate that the Naïve Bayes method can be effectively applied to predict student graduation factors with acceptable accuracy, making it a suitable approach for analyzing graduation data and supporting academic decision-making processes.
Klasifikasi Penyakit Stroke Menggunakan Algoritma SVM (Support Vector Machine) Dendy K Pramudito; Miftahurridwan
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Stroke is a disease caused by a sudden disruption of blood flow to the brain and is one of the leading causes of death in Indonesia. The high mortality rate and delays in early detection make stroke a serious health problem that requires technology-based solutions. Therefore, an approach is needed to support the rapid and accurate classification of stroke disease. This study aims to develop and evaluate a stroke disease classification model using the Support Vector Machine (SVM) algorithm. The dataset used in this study was obtained from the Kaggle platform and consists of 5,110 records with 11 attributes representing stroke risk factors. The research stages include data collection, preprocessing, which consists of data type conversion, feature selection, data cleaning, normalization, and data transformation. To address class imbalance in the dataset, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. Furthermore, the data were partitioned using the 10-Fold Cross Validation method before performing the classification process using the SVM algorithm. Model performance evaluation was conducted using a Confusion Matrix with accuracy, precision, and recall parameters. The experimental results show that the SVM model achieved an average accuracy of 0.79, precision of 0.72, and recall of 0.93. Based on these results, it can be concluded that the Support Vector Machine algorithm demonstrates good performance in classifying stroke disease and has the potential to be used as an effective support system for early stroke detection.
Aplikasi Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Berbasis Website Menggunakan Metode SAW Pada PT. Lion Super Indo Andri Firmansyah; Muhammad Dicky Chandra
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Employee performance quality is a key factor in a company’s progress, making objective and accurate evaluation essential in selecting the best employee. At PT. Lion Superindo Marketing Division, the selection process for the best employee is still conducted manually using Microsoft Excel, which may lead to inaccuracies in decision-making. This study aims to develop a web-based decision support system using the Simple Additive Weighting (SAW) method to improve efficiency and accuracy in performance evaluation. The system was developed using PHP, JavaScript, and Bootstrap, with MySQL as the database. The implementation results show that the SAW method accelerates the calculation process and produces more objective decisions. Based on the calculation results, alternative A9, Adam Alfian, obtained the highest preference value of 0.97 and was selected as the best employee. The developed system effectively supports more efficient and accurate decision-making.
Penerapan Algoritma SVM (Support Vector Machine) Untuk Prediksi Resiko Penyakit Jantung Dengan Kernel Sigmoid Handala Simetris Harahap; Safira Novianti
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Heart disease, also known as coronary heart disease, occurs when blood flow to the heart muscle is reduced or blocked, causing significant damage. The objective of this study is to develop a predictive model that can estimate the risk of heart disease using the Support Vector Machine (SVM) algorithm with a sigmoid kernel, so that patients can be classified into high-risk and low-risk categories. The modeling stage is carried out to select and implement the appropriate modeling technique, determine the data mining tools to be used, and set optimal parameter values. At this stage, the training data are learned by the selected algorithm model, and the testing data are then evaluated using the developed classifier to obtain performance metrics. The results of this study indicate that the SVM method with a sigmoid kernel provides a good level of accuracy in predicting heart disease risk based on measured risk factors such as age, gender, blood pressure, cholesterol levels, and others. From the experiments conducted, the classification performed well. Using 303 data instances that were randomly sampled into 1,220 data points, the model achieved an accuracy of 0.788, a precision of 0.787, and a recall of 0.788.
Implementasi Algoritma Naïve Bayes Classifier Sinkronisasi Absensi Dengan Prestasi Akademik Pasraman Taman Dharma Widya Hemdani Rahendra Herlianto; I Gede Krishna Yogananda Raken Putra
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Data mining is a technique that utilizes large amounts of data to obtain valuable information that was previously unknown and can be used to support important decision-making. In this study, the author attempts to mine customer data from an insurance company to determine whether the customers are categorized as current, less current, or delinquent in their payments. The existing data are analyzed using the Naive Bayes algorithm. Naive Bayes is one of the methods in probabilistic reasoning. The Naive Bayes algorithm aims to classify data into specific classes; the resulting patterns can then be used to predict students’ academic performance based on attendance records, enabling Pasraman Taman Dharma Widya to make appropriate decisions regarding the students.
Pengujian Sistem Informasi Kontrol Stok Barang Pendukung Produksi Berbasis Web Dengan Metode User Acceptance Testing (UAT) Pada PT. Tenma Cikarang Indonesia Isarianto; Rina Patmawati
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

An information system is one of the most essential components within a company. By implementing an information system, a company can ensure the quality of the information produced and make decisions based on that information. PT. Tenma Cikarang Indonesia is a company engaged in the production of plastic injection molds and molding. One of the main weaknesses in the current stock control system at PT. Tenma Cikarang Indonesia is the lack of visibility and accuracy in managing supporting production inventory. Without a computerized system, the company often faces difficulties in tracking available stock, updating depleted items, and anticipating customer demand. In response to these issues, a supporting production inventory control information system was designed to assist the warehouse department in managing item data. This system is web-based and was developed using the waterfall method, with PHP as the programming language and MySQL as the database. Testing was conducted using the User Acceptance Testing (UAT) method. The resulting system is capable of providing information on item data, goods receipt, goods issuance, and generating transaction reports that are useful for users.
Aplikasi Bank Sampah Sebagai Alternatif Pengelolaan Sampah Dengan Metode Prototype Berbasis Android Suprapto; Ramdhan Syaifulloh
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

The development of information technology has progressed rapidly as humans interact with the internet through mobile devices and computers. These advancements enhance performance and enable various activities to be carried out quickly, accurately, and efficiently, thereby increasing productivity. In Indonesia, rapid technological growth coincides with a rising population, which leads to an increase in waste volume. Waste is the residual material from human activities or natural processes in solid form, generated daily. To address waste management issues, the establishment of waste banks has become an alternative solution. Waste banks serve as collection centers for sorted waste and are also used in social planning to educate the community on environmental health, encourage behavioral changes at the household level the main source of waste and support the implementation of a circular economy. As a result, the community benefits both ecologically and financially. To improve the effectiveness of waste bank management, an Android-based Waste Bank Application using the Prototype Method is proposed. This system provides general information about waste banks and enables customers to monitor deposit and withdrawal transactions in real time through an online savings book. The mobile-based application can be accessed from various smartphones connected to the internet, facilitating waste bank management and encouraging community participation in waste management programs.
Pengembangan Sistem Informasi Laporan Produksi Berbasis Web Menggunakan Metode Rapid Application Development (RAD) Pada PT. Nichias Metalwork Indonesia Zaenur Rozikin; Edi Hotman Sijabat
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

In general, production management consists of several functions in which management experts give their respective opinions. From the problems that exist in PT. Nichias Metalwork Indonesia in production, the process of inputting production report data still uses sheets of paper which are done manually and then collected at the supervisor's desk, and hinders the process of inputting data by the admin, because the admin has to take the report sheets that are on the supervisor's desk. The method used in this study is the Rapid Application Development (RAD) method. The Rapid Application Development method is a software development method that emphasizes development in a short time and uses iterative (repetitive) methods where the working model is constructed at the early stages of development to determine user requirements. In making the production report system the author uses the PHP Programming Language and MySQL database. The purpose of this study is to design and build a production reporting information system to make it easier to check and input goods to minimize the difference in production inventory and speed up the process of inputting and reporting production at PT. Nichias Metalwork Indonesia
Pengembangan Aplikasi Pengadaan Barang Pada Koperasi Karyawan Dan Warga Al-Muslim Berbasis Web Dengan Metode SDLC Andri Firmansyah; Tri Wahyuni
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

The growth of information technology for entrepreneurs in Indonesia is very rapid, especially in the city of Bekasi. Al-Muslim Employees and Citizens Cooperative is one of the businesses engaged in cooperative sales of fulfillment needs within the Al-Muslim Foundation which has a large inventory of goods and needs better management. In carrying out its business processes, the Al-Muslim Employees and Citizens Cooperative has several problems including data processing is still manual by using records only so that it is vulnerable to lost or damaged data. Another problem is human error or people who process data from the process of recording incoming goods data, recording outgoing goods data, recording stock data. The method used in this research is Software Development Life Cycle (SDLC), this method describes the overall software development process to produce quality software and meet the expectations of system users. The result of this research is to build a procurement system to make it easier to control the amount of inventory of each item appropriately and can speed up the production of information on ordering goods so that there is no delay in ordering goods.

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