Pengembangan Aplikasi Perhitungan Prediksi Stock Motor Menggunakan Algoritma C 4.5 Sebagai Bagian dari Sistem Pengambilan Keputusan (Studi Kasus di Saudara Motor)

Putra, Pandu Pratama; Chan, Andi Supriadi

doi:10.35314/isi.v3i1.296

Cited by 5 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Berbagai penelitian tentang prediksi atau perkiraan mengenai hal-hal yang berhubungan dengan keperluan masyarakat umum telah banyak dilakukan [1]- [4], [5]- [7]. Salah satunya menggunakan algoritma regresi untuk memprediksi pergerakan harga saham menggunakan model deep learning dan fuzzy neural network.…”

Section: Pendahuluanunclassified

Prediksi Penetapan Tarif Penerbangan Menggunakan Auto-Ml Dengan Algoritma Random Forest

et al. 2022

View full text Add to dashboard Cite

With so many airlines competing with each other, airlines are competing to become the consumer/market's main choice, but to achieve this, there is no airline strategy that can predict the price of airline tickets according to market needs. To meet the needs of airlines, we need a way to determine the price of airline tickets according to market needs with the help of the influence of technology and information. This research method was carried out using Google Collaboratory as a media to create a data model automated machine learning (AutoML) with the Random Forest, Logistic Regression and Gradient Boosting Regressor algorithms. In this study, the model that produced the highest R2 value and the lowest RMSE was a random forest with an R2 value of 83.91% and an RMSE of $175.9. However, from the three models, Random Forest got a change in accuracy of 1.96% to 85.87. To assist in predicting the determination of flight fares, airline companies can more easily and be alert to determine flight fares that are in accordance with the market. Therefore, Random Forest can be declared better than Logistic Regression and Gradient Boosting models. The Random Forest model that has been created can be used to predict in real-time using Machine Learning.

show abstract

Section: Pendahuluanunclassified

Prediksi Penetapan Tarif Penerbangan Menggunakan Auto-Ml Dengan Algoritma Random Forest

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Data Mining Menurut Gatner Group adalah suatu proses menemukan hubungan yang berarti, pola dan kecenderungan dengan memeriksa dalam sekumpulan besar data yang tersimpan dalam penyimpanan, dengan menggunakan teknik pengenalan pola seperti teknik statistik dan matematika (Putra & Chan, 2018). Data Mining merupakan proses menemukan hubungan, pola, dan tren yang bermakna dengan memeriksa sekumpulan besar data yang disimpan dalam penyimpanan menggunakan teknik pengenalan pola seperti teknik statistik dan matematika (Darmawan, 2018).…”

Section: A Data Miningunclassified

“…Penelitian terdahulu oleh (Sungkar & Qurohman, 2021) dengan judul Penerapan Algoritma C5.0 untuk Prediksi Kelulusan Pembelajaran Pada Matajuliah Arsitektur Sistem Komputer. Penelitian terdahulu yang dilakukan oleh (Putra & Chan, 2018) dengan judul "Pengembangan Aplikasi Perhitungan Prediksi Stock Motor Menggunakan Algoritma C 4.5 Sebagai Bagian dari Sistem Pengambilan Keputusan" menyatakan bahwa proses perhitungan yang telah dilakukan melalui beberapa langkah pada proses penerapan Data Mining menggunakan algoritma C4.5 sebelumnya, maka diperoleh pohon keputusan. Melalui pohon keputusan tersebut diperoleh 12 aturan-aturan (rule) dalam menentukan prediksi persediaan stock motor pada dealer Saudara Motor.…”

unclassified

Prediction System for Credit Eligibility Using C4.5 Algorithm

Puspita¹,

Aminah²,

Arif³

2022

JITE

View full text Add to dashboard Cite

Independent Multipurpose Cooperative, Tasti, Pagar Alam City, currently granting credit, the data collection process for the selection of prospective members and prospective credit recipients is still done manually, so they must come to the cooperative to find out whether it is still eligible to receive credit or not, officers must evaluate the data. is to form a decision tree classification model for creditworthiness in cooperatives. The analytical method with the C4.5 Algorithm, the C4.5 Algorithm is one of the algorithms for performing data mining using data classification techniques. The C4.5 algorithm is used to search for knowledge in the data, by finding the relationship between input variables or criteria attributes with target variables or decision attributes. The resulting knowledge is converted into the form of a decision tree so that it is easy to understand. The C4.5 algorithm was chosen because it can make a decision to be able to predict whether a customer is eligible or not to be given credit. The attribute used is income with specified criteria. The results obtained from this study are predictive information on the feasibility of providing credit to cooperatives using the C4.5 algorithm by getting an accuracy value of 93% with an AUC value of 0.898 where this classification is classified as Good Classification or good.

show abstract

“…Algoritma C4.5 Salah satu algoritma yang dapat digunakan untuk membuat pohon keputusan (decission tree) adalah algoritma C4.5 [9]. Algortima C4.5 merupakan model tree mirip sebuah pohon dimana terdapat node internal (bukan daun) yang mendeskripsikan atribut-atribut, setiap cabang menggambarkan hasil dari atribut yang diuji, dan setiap daun menggambarkan kelas [10].…”

Section: Pembentukan Model Algoritma C45unclassified

Penerapan Algoritma C45 Untuk Klasifikasi Keberhasilan Pengiriman Barang

Taufik

Jatmika

2021

ISI

View full text Add to dashboard Cite

Abstrack -The success rate of shipping goods is a very important factor in the world of ecommerce business with logistics delivery services being the last link in the chain with customers. This greatly affects the satisfaction of customers who expect the goods they buy can be sent on time and in good condition when received. One technique of data mining that can be used to help predictions is to use classification techniques. Classification can be done with a decision tree that is with the C4.5 algorithm. The purpose of this study is to make a classification and apply data mining classification based on the decision tree and the rules generated. Furthermore, the results of the data classification are evaluated using a confusion matrix and ROC curve in the rapid miner application to determine the level of accuracy results. In this study produced an accuracy value of 93% and produced an AUC (Area Under Curve) value of 0.73 with a sufficient classification accuracy (Fair classification). From the results of this study can be a recommendation for the distribution section in choosing logistics services in shipping goods based on categories of goods, the destination address so that the risk of failure in shipping can be reduced.

show abstract

Pengembangan Aplikasi Perhitungan Prediksi Stock Motor Menggunakan Algoritma C 4.5 Sebagai Bagian dari Sistem Pengambilan Keputusan (Studi Kasus di Saudara Motor)

Cited by 5 publications

References 0 publications

Prediksi Penetapan Tarif Penerbangan Menggunakan Auto-Ml Dengan Algoritma Random Forest

Prediksi Penetapan Tarif Penerbangan Menggunakan Auto-Ml Dengan Algoritma Random Forest

Prediction System for Credit Eligibility Using C4.5 Algorithm

Penerapan Algoritma C45 Untuk Klasifikasi Keberhasilan Pengiriman Barang

Contact Info

Product

Resources

About