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Implementasi artificial neural network dalam mendeteksi penyakit hati (liver) Irmawati Irmawati; Kudiantoro Widianto; Faruq Aziz; Achmad Rifai; Ami Rahmawati
Journal of Information System, Applied, Management, Accounting and Research Vol 6 No 1 (2022): JISAMAR: February 2022
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v6i1.694

Abstract

Acute liver disease can affect liver function, but can identify the patient's clinical and physical symptoms. One of the problems faced by society today is the delay in treatment of liver disease patients, most patients do not carry out self-examination until an advanced stage is found. To overcome this problem, we need a system that can determine whether a person is a patient with liver disease, so that they can carry out routine checks as soon as possible and allow liver disease patients to get timely treatment. The system can generate classification with the help of data mining algorithms. In this paper, Liver Patients have been investigated using an Artificial Neural Network model to predict a Liver Patient or not and analysis using ANN with Python was used to determine the effect of input variables based on data in the literature and obtained an accuracy of 74%.
DEVELOPMENT OF MANUFACTURING INVENTORY MANAGEMENT SYSTEM USING MATERIAL REQUIREMENT PLANNING METHOD Ami Rahmawati; Rizal Amegia Saputra; Ita Yulianti
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (923.607 KB) | DOI: 10.34288/jri.v4i1.271

Abstract

Inventory has an important role in business activities. This is because inventory has an effect on changes in the production market and anticipates price changes in the demand for many goods. PT. Barkah Jaya Mandiri is a company engaged in manufacturing where the management of inventory at the company is still done conventionally. This causes various problems such as the occurrence of discrepancies in the stock of goods, discrepancies in data and final reports as well as obstacles in the production process in the event of a shortage or excess of raw materials. (Material Requirement Planning) in order to overcome the problems that occur in the company. The combination of the SDLC model and data collection techniques including observation, interviews and literature study were also carried out in this study in order to achieve the system that will be built to suit the targeted needs. With this system, the management of inventory data at this company can be done easily and accurately and save time compared to the previous system, so that the procurement of manufacturing raw materials is optimal and employee performance is better.
Analisis Determinan Tingkat Kepuasan Pengguna Software MYOB Accounting dalam Bidang Akademik Ita Yulianti; Muhamad Abdul Ghani; Ami Rahmawati
Swabumi Vol 10, No 2 (2022): Volume 10 Nomor 2 Tahun 2022
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v10i2.12271

Abstract

Perkembangan teknologi sistem informasi yang semakin pesat memberikan dampak begitu signifikan terhadap pada perubahan layanan termasuk dalam siklus akuntansi. Kehadiran software akuntasi membuat kemudahan dalam pencatatan transaksi sampai dengan laporan keuangan karena dilakukan secara otomatis. Ada berbagai jenis software akuntansi, namun pada penelitian ini dilakukan analisis untuk mengetahui determinan yang berpengaruh terhadap tingkat kepuasan MYOB Accounting dalam bidang akademik berdasarkan variabel kualitas layanan sistem informasi, kualitas sistem informasi dan kualitas informasi. Hal ini dipilih karena banyaknya penggunaan software tersebut yang seringkali dijadikan sebagai salah satu uji kompetensi yang biasanya dilakukan pada tataran SMK bahkan perguruan tinggi. Penelitian ini termasuk kedalam penelitian asosiatif dengan jumlah responden sebanyak 100 orang yang diproses menggunakan metode regresi linier berganda. Dari hasil penelitian menunjukkan bahwa secara simultan ketiga variabel yang digunakan berpengaruh dan berhubungan sangat erat terhadap kepuasan pengguna MYOB accounting dalam bidang akademik yang dinyatakan dengan nilai koefisien korelasi 0,672 dan nilai koefisien determinasi sebesar 69,2%.
Optimalisasi Sistem Pembayaran Administrasi Kesiswaan Berbasis Website Ami Rahmawati; Ita Yulianti
JUSTIKA : Jurnal Sistem Informasi Akuntansi Vol 1 No 2 (2021): JUSTIKA : Jurnal Sistem Informasi Akuntansi
Publisher : Program Studi Sistem Informasi Akuntansi Kampus Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/justika.v1i2.940

Abstract

Sebagai salah satu lembaga pendidikan formal, SMK (Sekolah Menengah Kejurusan) khususnya SMK Abdi Bangsa selalu berupaya memberikan pelayanan yang terbaik bagi siswa/i khususnya dalam pelayanan administrasi kesiswaan. Namun, pada kenyataannya penyelenggaraan pelayanan yang dilakukan hampir di setiap sekolah masih dihadapkan pada pelayanan yang belum efektif dan efisien. Hal ini dikarenakan pencatatan administrasi kesiswaan pada sekolah tersebut masih dilakukan secara konvensional yang terkadang masih terjadinya kesalahan pencatatan. Oleh karena itu, reformasi dan modernisasi diperlukan dengan memanfaatkan teknologi informasi. Penelitian ini dibuat dengan tujuan untuk membangun sistem yang dapat menyempurnaan sistem yang sebelumnya telah ada dengan memperbaiki dari kekurangannya sehingga kebutuhan pelayanan administrasi kesiswaan dapat berjalan secara efektif dan efisien. Sistem yang dibangun yaitu berupa sistem pembayaran administrasi kesiswaan berbasis website menggunakan bahasa pemrograman PHP dan database MySQL. Sedangkan untuk metode penelitian yang digunakan yaitu ada dua metode yakni metode pengembangan perangkat lunak waterfall dan metode pengumpulan data yang terdiri dari observasi, wawancara dan studi pustaka. Dari hasil sistem yang dibangun menunjukkan bahwa dengan adanya sistem ini dapat mengoptimalkan kinerja pelayanan administrasi karena dapat memberikan kemudahan, kecepatan dan ketepatan pencatatan yang lebih baik jika dibandingkan dengan sistem berjalan sebelumnya.
Pengembangan Sistem Forecasting Penjualan Pada Aplikasi Point of Sales Menggunakan Metode Trend Least Square Ita Yulianti; Ami Rahmawati
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 1 (2022): Juli 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (620.371 KB) | DOI: 10.31294/larik.v2i1.1153

Abstract

The use of cash register as evidence of technology utilization in business activities is not enough to help the sustainability of a business, because it has not fully controlled data collection, especially in terms of information about the development of income and inventory planning. Therefore, for the sake of the business sustainability, the strategy is needed, one of which is to build a system that can manage the transaction process equipped with sales forecasting features that can display product predictions according to market needs. To build a system of data collection techniques, the waterfall system development model and the implementation of the Least Square trend method. Of the three research methods that are applied, the contribution produced is in the form of a desktop-based Point of Sales (POS) system with Java programming languages equipped with additional features, namely sales prediction. Based on the application of the system it is proven that the use of the Trend Least Square method is very appropriate to use because it can display the prediction results of sales for the coming period with predictive error rates of only 0.0067% and this system also helps optimize service activities to customers and can help sales management in terms of Provision of products.
Implementation of the Saw Method to Discover the Optimum Internet Service Recommendations for Online Gaming Gunawan Gunawan; Ita Yulianti; Ami Rahmawati; Tati Mardiana; Nanang Ruhyana
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.v5i3.547

Abstract

Currently, the development and use of the Internet have a more complex function so that it can change the paradigm of people's lives, including in aspects of entertainment, especially games. With the rise of numerous ISPs in Indonesia, different internet service packages are now available, particularly for gamers, such as Indihome, Biznet, First Media, and My Republic. The variety of services makes it difficult for users to choose an internet package that suits their needs. Therefore, this research aims to build a decision support system that can facilitate users in choosing the ideal internet service for gamers based on five criteria: quota, network speed, connection, cost, and the number of users using the SAW method. The data collection methods used are observation, questionnaires, and interviews. The research results obtained from data processing using the SAW method through Microsoft Excel are then implemented into a website-based program. With this program, it is hoped that it can be a tool for users in determining the service package to be purchased.
DEVELOPMENT OF MANUFACTURING INVENTORY MANAGEMENT SYSTEM USING MATERIAL REQUIREMENT PLANNING METHOD Ami Rahmawati; Rizal Amegia Saputra; Ita Yulianti
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.v4i1.135

Abstract

Inventory has an important role in business activities. This is because inventory has an effect on changes in the production market and anticipates price changes in the demand for many goods. PT. Barkah Jaya Mandiri is a company engaged in manufacturing where the management of inventory at the company is still done conventionally. This causes various problems such as the occurrence of discrepancies in the stock of goods, discrepancies in data and final reports as well as obstacles in the production process in the event of a shortage or excess of raw materials. (Material Requirement Planning) in order to overcome the problems that occur in the company. The combination of the SDLC model and data collection techniques including observation, interviews and literature study were also carried out in this study in order to achieve the system that will be built to suit the targeted needs. With this system, the management of inventory data at this company can be done easily and accurately and save time compared to the previous system, so that the procurement of manufacturing raw materials is optimal and employee performance is better.
THE EFFECTIVENESS ANALYSIS OF RANDOM FOREST ALGORITHMS WITH SMOTE TECHNIQUE IN PREDICTING LUNG CANCER RISK Ita Yulianti; Ami Rahmawati; Tati Mardiana
Jurnal Riset Informatika Vol. 4 No. 2 (2022): March 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (996.334 KB) | DOI: 10.34288/jri.v4i2.159

Abstract

Abstract When compared with other types of cancer, most of the population with cancer die from lung cancer.A person needs to do a screening test through X-rays, CT scans, and MRI to detect the disease. However, before carrying out the process, the doctor will ordinarily investigate a medical history and physical examination first to study the symptoms and possible risk factors for lung cancer. The lung cancer data set has a class imbalance that affects the performance of the random forest algorithm in predicting the risk of lung cancer. This study aims to employ the SMOTE technique to the random forest algorithm to increase accuracy in predicting lung cancer risk. In this research, data processing and analysis use the Python programming language. The test results show an accuracy value of 88% with an AUC value of 0.93. When employing the random forest method to forecast lung cancer risk, the SMOTE technique is useful in dealing with class imbalances in the data set.
Implementation of the Saw Method to Discover the Optimum Internet Service Recommendations for Online Gaming Gunawan Gunawan; Ita Yulianti; Ami Rahmawati; Tati Mardiana; Nanang Ruhyana
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (759.546 KB) | DOI: 10.34288/jri.v5i3.232

Abstract

Currently, the development and use of the Internet have a more complex function so that it can change the paradigm of people's lives, including in aspects of entertainment, especially games. With the rise of numerous ISPs in Indonesia, different internet service packages are now available, particularly for gamers, such as Indihome, Biznet, First Media, and My Republic. The variety of services makes it difficult for users to choose an internet package that suits their needs. Therefore, this research aims to build a decision support system that can facilitate users in choosing the ideal internet service for gamers based on five criteria: quota, network speed, connection, cost, and the number of users using the SAW method. The data collection methods used are observation, questionnaires, and interviews. The research results obtained from data processing using the SAW method through Microsoft Excel are then implemented into a website-based program. With this program, it is hoped that it can be a tool for users in determining the service package to be purchased.
Image Segmentation Analysis Using Otsu Thresholding and Mean Denoising for the Identification Coffee Plant Diseases Ami Rahmawati; Ita Yulianti; Siti Nurajizah
Jurnal Riset Informatika Vol. 6 No. 1 (2023): December 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i1.261

Abstract

In Indonesia, coffee is one of the plantation products with a relatively high level of productivity and is a source of foreign exchange income for the country. However, unfortunately, certain factors can threaten productivity and quality in cultivating coffee plants, one of which is rust leaf disease. This disease causes disturbances in photosynthesis, thereby reducing plant yields. Therefore, to maintain and control productivity in coffee cultivation, this research carried out the process of observing coffee leaf images through segmentation using the Otsu Thresholding and Mean Denoising methods. The entire series of processes in this research was carried out using the Python programming language and succeeded in providing output in the form of image comparisons showing areas affected by Rust Leaf disease using the Otsu thresholding method alone and the Otsu thresholding method combined with a non-local means denoising algorithm. The test results prove that the Otsu thresholding method with the non-local means denoising algorithm has a smaller MSE value. It is the most optimal method for handling coffee leaf disease image segmentation with an accuracy level of 88%. It is hoped that this research can support farmers in providing insight into early detection of coffee plant diseases and increasing productivity through visual analysis.