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ANDROID SALES PREDICTION DURING PANDEMIC USING NAÏVE BAYES AND K-NN METHODS BASED ON PARTICLE SWARM OPTIMIZATION Endang Sri Palupi
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

During the pandemic, most schools, campuses, and places of education conducted online teaching and learning activities. Many teaching and learning activities are carried out using the Zoom, Google, WebEx, or Microsoft Teams applications. All of this can be done through a PC or laptop, or using a cellphone, so the need for PCs and cellphones increases, both new and used goods. Even though during the pandemic the economic situation was declining, many companies suffered losses, resulting in a reduction in employees and causing a high unemployment rate, the need for Android phones remains high. In addition to online distance learning facilities, Android phones can also be used for online sales through e-commerce, market places, social media, and other digital platforms. Currently, Android phones have many choices and according to the funds we have, with various brands and specifications. Many brands issue android cellphone products with pretty good specifications and affordable prices, so that even though purchasing power has decreased due to the pandemic, sales of android cellphones are still high. In this study, the author predicts the highest sales of android cellphones using the Naïve Bayes method and the K-Nearest Neighbor method based on Particle Swarm Optimization accuracy of 81.33%.

Web-Based Customer Services Management Implementation For The Sales Division Endang Sri Palupi
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.485

With the growing business at PT Mastersystem Infotama, more and more customers and orders have been obtained. As time goes by, many sales go in and out, and staff change, so the customer database cannot be maintained and updated correctly. All leads and opportunities cannot be monitored and appropriately managed, and the daily activity of the sales division is also not monitored. Implementation of Customer Relationship Management (CRM) helps maintain customer data and can be continuously updated to maintain good relations with all customers. Prospects and opportunities can be managed and monitored, the daily activities of the sales division are neatly scheduled, and customer observations can be gathered, all of which can be done in one application, CRM. With this implementation, sales at PT Mastersystem Infotama experienced a 20% increase in sales in 2018. This research uses the waterfall model, which has the advantage of being a gradual and more detailed method to minimize errors. This CRM implementation produces a web-based CRM application that can be accessed by all employees wherever they are connected to a LAN. Employees can access CRM according to each division's capacity to make work easier.

Classification of Blighted Ovum Factors in Pregnant Women Using PSO-Based NaÃ¯ve Bayes Febryo Ponco Sulistyo; Endang Sri Palupi
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.554

Klasifikasi Faktor Blighted Ovum atau janin tidak berkembang dilakukan mengingat kasus Blighted Ovum banyak terjadi pada ibu hamil. Blighted Ovum merupakan 60% dari penyebab keguguran, di Indonesia ditemukan 37% dari setiap 100 kehamilan. Klasifikasi menggunakan NaÃ¯ve Bayes berbasis Particle Swarm Optimization (PSO) yang hanya membutuhkan data training yang kecil untuk menentukan estimasi parameter yang diperlukan dalam proses pengklasifikasian dan penggunaan Particle Swarm Optimization dapat meningkatkan nilai akurasi serta memecahkan masalah optimasi. Dengan proses pemilihan data variable dan data attribute untuk membuat kuisioner sebagai metode pengambilan data. Hasil klasifikasi blighted ovum pada wanita hamil menggunakan algoritma NaÃ¯ve Bayes dengan framework Rapid Miner mendapatkan nilai akurasi sebesar 71,56% dengan Area Under Curve (AUC) 0,674 termasuk dalam kategori klasifikasi yang baik. Setelah menggunakan optimasi PSO nilai akurasi naik menjadi 79,82% dengan Area Under Curve 0,764 termasuk kategori klasifikasi yang baik. NaÃ¯ve bayes merupakan metode yang cocok untuk klasifikasi, dan PSO bisa membuat nilai akurasi dan AUC lebih baik lagi.

DESIGNING A JAVANESE SCRIPT LEARNING MOBILE APPLICATION USING A PROTOTYPE MODEL Endang Sri Palupi
Jurnal Riset Informatika Vol. 3 No. 1 (2020): December 2020 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i1.47

Javanese script is one of the special characters that need to be studied specifically. At the elementary to high school level in central Java province, there are regional language subjects, namely Javanese language that has Javanese script. Javanese characters are different from the Latin writings used daily, so it requires special understanding and teaching. There are still many students who have difficulty learning Javanese script and limited learning time in elementary school for Javanese language subjects. In addition to helping students to learn Javanese characters more easily, this application is designed so that outsiders can also learn Javanese characters to preserve the culture and love the culture in Indonesia more. The method used in the development of mobile applications is the prototype model with this modelhe author can interact directly with the user so that it can tell the difficulty, provide inputs on what can be set on the application, and what is needed by the user. This application can be useful to learn Javanese characters by utilizing information technology according to the development of the times.

PREDICTION OF ANDROID HANDPHONE SALES DURING PANDEMIC USING NAÏVE BAYES AND K-NN METHODS BASED ON PARTICLE SWARM OPTIMIZATION Endang Sri Palupi
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i1.133

Abstract During the pandemic, most schools, campuses, and places of education conducted online teaching and learning activities. Many teaching and learning activities are carried out using the Zoom, Google, WebEx, or Microsoft Teams applications. All of that can be done through a laptop, you can also use a cellphone (HP) so that the need for laptops and cellphones increases, both new and used goods. Even though during the pandemic the economic situation was declining, many companies suffered losses, resulting in a reduction in employees and causing a high unemployment rate, the need for Android phones remains high. In addition to online distance learning facilities, Android phones can also be used for online sales through e-commerce, market places, social media, and other digital ceilings. Currently, Android phones have many choices and according to the funds we have, with various brands and specifications. Many brands issue android cellphone products with pretty good specifications and affordable prices, so that even though purchasing power has decreased due to the pandemic, sales of android cellphones are still high. In this study, the author predicts the highest sales of android cellphones using the Naïve Bayes method and the K-Nearest Neighbor method based on Particle Swarm Optimization. accuracy of 81.33%.

Classification of Blighted Ovum Factors in Pregnant Women Using PSO-Based Naïve Bayes Febryo Ponco Sulistyo; Endang Sri Palupi
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Classification of Blighted Ovum Factors or undeveloped fetuses is carried out considering that many cases occur in pregnant women. Blighted Ovum is 60% of the causes of miscarriage. In Indonesia, it is found in 37% of every 100 pregnancies. Classification uses Naïve Bayes based on Particle Swarm Optimization (PSO), which only requires small training data to determine the parameter estimates needed in the classification process, and the use of Particle Swarm Optimization can increase accuracy and solve optimization problems with the process of selecting variable data and attribute data to create a questionnaire as a data collection method. The results of the classification of blighted Ovum in pregnant women using the Naïve Bayes algorithm with the Rapid Miner framework obtained an accuracy value of 71.56% with an Area Under Curve (AUC) of 0.674 included in the excellent classification category. After using the PSO optimization, the accuracy value rose to 79.82% with an Area Under the Curve of 0.764, including a good classification category. Naïve Bayes is a suitable method for classification, and PSO can improve the accuracy and AUC values .

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