Garuda - Garba Rujukan Digital

Penerapan Metode Particle Swarm Optimization Pada Optimasi Prediksi Pemasaran Langsung Yuni Eka Achyani
Jurnal Informatika Vol 5, No 1 (2018): Jurnal INFORMATIKA
Publisher : LPPM Universitas Bina Sarana Informatika

Abstrak Dalam persaingan ketat saat ini, promosi yang baik dapat memberikan kredibilitas untuk produk baru. Promosi perlu mendapat perhatian lebih dan serius, karena dalam kehidupan sehari-hari timbul produk unggulan, jika tidak mengetahuinya, kemungkinan produk yang ditawarkan kepada konsumen kurang ditanggapi oleh pasar, oleh karena itu perusahaan harus mengupayakan produknya, meyakinkan dan mempengaruhi konsumen untuk menciptakan permintaan akan produk ini. Langkah yang bisa dilakukan oleh perusahaan untuk melakukannya adalah dengan melakukan pemasaran langsung. Peningkatan akurasi prediksi pemasaran langsung dapat dilakukan dengan cara melakukan seleksi terhadap atribut, karena seleksi atribut mengurangi dimensi dari data sehingga operasi algoritma data mining dapat berjalan lebih efektif dan lebih cepat. Dalam penelitian ini akan digunakan metode support vector machine dan akan dilakukan seleksi atribut dengan menggunakan particle swarm optimization untuk prediksi pemasaran langsung. Setelah dilakukan pengujian maka hasil yang didapat adalah support vector machine menghasilkan nilai akurasi sebesar 88,71 %, nilai precision 89,47% dan nilai AUC sebesar 0,896. Kemudian dilakukan seleksi atribut dengan menggunakan particle swarm optimization dimana atribut yang semula berjumlah 16 variabel prediktor terpilih 12 atribut yang digunakan. Hasil menunjukkan nilai akurasi yang lebih tinggi yaitu sebesar 89,38%, nilai precision 89,89% dan nilai AUC sebesar 0,909 dengan nilai akurasi klasifikasi sangat baik (excellent clasiffication). Sehingga dicapai peningkatan akurasi sebesar 0,67 %, dan peningkatan AUC sebesar 0,013. Kata Kunci: Particle Swarm Optimization, Pemasaran Langsung, Seleksi Atribut Abstract In the current intense competition a good promotion can provide credibility for a new product. Promotion needs to get more attention and serious, because in everyday life arise a prime product, if not find out, the possibility of products offered to consumers less responded by the market, therefore the company should strive for its products. , convincing, and influencing consumers to create demand for these products. Steps that can be done by the company to do so is to do direct marketing. Increased accuracy of direct marketing predictions can be done by selecting attributes, because of the selection. Data mining can run more effectively and quickly. In this study the method to be used is. With particle swarm optimization for direct marketing prediction optimization. After testing, the results obtained are support vector engine yield value of 88.71%, precision value 89.47% and AUC value of 0.896. Then the attribute selection is done using particle swarm optimization where the original attribute uses 16 predictor variables selected 12 attributes used. The results showed a higher value of 89.38%, 89.89% accuracy and AUC value of 0.909 with very good fair value (excellent classification). The price increase is 0.67%, and the increase of AUC is 0,013. Keywords: Particle Swarm Optimization, Direct Marketing, Selection Attributes.

SISTEM INFORMASI PENDAPATAN JASA PADA KOPERASI PDAM TIRTA PATRIOT BEKASI Yuni Eka Achyani; Eni Arviana
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 4, No 1 (2018): JURNAL TEKNIK KOMPUTER AMIK BSI
Publisher : Universitas Bina Sarana Informatika

Development of information technology is increasingly rapidly makes the need for information is increasing. Information is very important in supporting the course of a company to achieve the desired goal. With the data processing program, and the information will be more rapid, precise and accurate in its presentation. Employees Cooperative PDAM Tirta Patriot is a business entity that is engaged in trade and services. By using the Web program can perform inputting and storing data quickly and can be easier to find the data that we want, so as to reduce the mistakes that often occur. The data collection method used by the authors is the direct observation, interviews, and literature. The author's purpose of research on web-based revenue service information system on Employee Cooperation Tirta Patriot PDAM in the hope to overcome the obstacles that have occurred in the system of service revenue manually, and can assist in making reports service revenue.

Prediksi Pemasaran Langsung Menggunakan Metode Support Vector Machine Yuni Eka Achyani
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 3, No 2 (2017): JURNAL TEKNIK KOMPUTER AMIK BSI
Publisher : Universitas Bina Sarana Informatika

Abstract— Direct marketing is a typical strategy to increase business. The company uses direct marketing when targeting customer segments with their contact to fulfill a specific purpose. Direct marketing is one way that can be used to predict potential customers who open deposits at the bank. Direct marketing became a very important application in data mining today. Data mining is widely used in direct marketing to identify potential customers for new products, using the purchase history data, predictive models can be used to measure that customers will respond to a given promotion or offer. One method that is most widely used method of support vector machine. In this study will be used method of support vector machine for prediction of direct marketing. After testing the results obtained is a support vector machine produces an accuracy value of 88.71%, 89.47% and a precision value AUC value of 0.896 with a value of classification accuracy was very good (excellent clasification). Based on these results it can be concluded that the use of support vector machine method can be used for precise and accurate prediction of direct marketing. Keywords : Prediction, Direct Marketing, Support Vector Machine. Abstrak— Pemasaran langsung merupakan strategi yang khas untuk meningkatkan bisnis. Perusahaan menggunakan pemasaran langsung bila menargetkan segmen pelanggan dengan menghubungi mereka untuk memenuhi tujuan tertentu. pemasaran langsung merupakan salah satu cara yang dapat digunakan untuk memprediksi nasabah yang berpotensi membuka simpanan deposito pada bank tersebut. Pemasaran langsung menjadi aplikasi yang sangat penting dalam data mining saat ini. Data mining secara luas telah digunakan dalam pemasaran langsung untuk mengidentifikasi calon pelanggan untuk produk baru, dengan menggunakan data histori beli, model prediktif dapat digunakan untuk mengukur bahwa pelanggan akan menanggapi promosi atau tawaran yang diberikan. Salah satu metode yang paling banyak digunakan adalah metode support vector machine. Dalam penelitian ini akan digunakan metode support vector machine untuk prediksi pemasaran langsung. Setelah dilakukan pengujian maka hasil yang didapat adalah support vector machine menghasilkan nilai akurasi sebesar 88,71 %, nilai precision 89,47% dan nilai AUC sebesar 0,896 dengan nilai akurasi klasifikasi sangat baik (excellent clasification). Berdasarkan hasil tersebut dapat disimpulkan bahwa penggunaan metode support vector machine dapat digunakan secara tepat dan akurat untuk prediksi pemasaran langsung. Kata Kunci— Prediksi, Pemasaran Langsung, Support Vector Machine.

Analisa dan Implementasi Sistem Informasi Pengeluaran Kas Kecil Pada PT. Bank Bukopin Berbasis Web Yuni Eka Achyani; Anggi Velayati
Paradigma Vol 22, No 1 (2020): Periode Maret 2020
Publisher : LPPM Universitas Bina Sarana Informatika

The application of a petty cash disbursement information system in a company is very important because by applying the petty cash disbursement information system, the company can supervise and control the course of the company's operational activities so that it can run as it should. This study aims to find out how the petty cash fund accounting system applied at PT. Bank Bukopin West Bekasi, is it in accordance with SOP (operational standards) in the company, and to find out the weaknesses of the system that is already running. From the results of this study obtained a discussion that in the petty cash expenditure PT. Bank Bukopin West Bekasi is still done manually starting from recording data to storing other data relating to the petty cash disbursement process to reporting. The research method used by the author is to use field research, interview methods and library methods while the software development method used by the writer is the waterfall method with the SDLC model. So according to the research of PT. Bank Bukopin West Bekasi requires a system that is expected to produce better reports in support of petty cash activities. The programming language used in development is to use a MySQL database and an editor using Notepad ++. This research will discuss about a web-based petty cash expenditure information system that is how the submission process, reimbursement, capital and reports. The author's purpose of this research is a small cash expenditure information system with the hope that it can overcome the obstacles that have occurred in the small cash expenditure system manually, and can assist in the process of making reports.

Penerapan Metode Rapid Application Development pada Sistem Informasi Persediaan Barang berbasis Web Biktra Rudianto; Yuni Eka Achyani
Bianglala Informatika Vol 8, No 2 (2020): Bianglala Informatika 2020
Publisher : LPPM Universitas Bina Sarana Informatika

At this time information technology is developing very rapidly and requires business actors to be able to follow the developments and advances of the times, especially in the world of technology and information. Inventory of merchandise is a company asset that is one of the assets included in current assets. Merchandise inventories are company assets that are purchased and stored to be resold and make a profit. Recording of merchandise inventory that is still manual, such as data collection of incoming goods, demand for goods, delivery of goods, returns of goods to the preparation of reports will certainly result in the accumulation of goods request notes. The difficulty of data collection of requests for goods from branches to deliver goods, errors in goods requested and sent, the length of time to record the return of goods, errors in calculating the stock of goods and difficulty in obtaining reports when needed are also one of the obstacles in the process of merchandise inventory. Therefore, a web-based inventory information system is needed in order to make it easier for users to manage the inventory process of their merchandise, so that it can simplify the process of recording, storing, searching and making reports. In designing a web-based inventory information system, the author uses the Rapid Application Development (RAD) method. This information system is the best solution for solving problems in managing inventory. With the use of computer data technology, managed data becomes faster, reduces time inefficiency and reduces the occurrence of errors in processing data.

Title

Found 5 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 5 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 5 Documents
Search