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Analisis Penggunaan Aplikasi Kasir “Majoo” Dalam Sistem Informasi Penerimaan Kas di Mencari Kopi Della Puspita; Jamil Azhari; Rera Zetira; Dinda Ayu Alifia; Nita Syahputri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 3 (2024): Agustus : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i3.3787

Abstract

This research aims to analyze the use of the cashier application software "Majoo" in the cash receipt information system Mencari Kopi. The object of this research is the use of the cashier application in cash receipts in Mencari Kopi. The subjects in this research were employees, owners of Mencari Kopi and consumers of Mencari Kopi. This research uses primary data used in this research, namely the source comes from the finance department through observations, interviews and documentation carried out on employees or owners of Mencari Kopi and consumers of Mencari Kopi who pay by cash or digital wallet (e-wallet). ). Secondary data used in this research are documents or notes regarding cash receipts and presentation when using the cashier application on Mencari Kopi. The results of this research. The cash receipt system at Mencari Kopi is run with the help of the “Majoo” cashier application system. The results of the research that has been carried out, in recording cash receipts, payments via cash and non-cash (e-wallet) are equally efficient as long as you still use the "Majoo" cashier application. The results of research conducted and interviews by users of the cashier application and consumers of Mencari Kopi, the recording of cash receipts recorded in Mencari Kopi and those received by consumers of Mencari Kopi are appropriate.
Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Pada Toko Dimsum Madani Menggunakan Algoritma Apriori Ahmad Syah Lubis; Shella Alivia Ahmad Siahaan; Nurul Nazli; Nita Syahputri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 3 (2024): Agustus : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i3.3805

Abstract

Data mining is a technique for extracting new information from data warehouses, information is seen as very important and valuable because by mastering information it is easy to achieve a goal, this makes everyone compete to obtain information, as is the case with the Dimsum business at Dimsum Madani.toko. This is located on Jalan Lampu gg. Pelita 4, Brayan Bengkel, East Medan, the location is close to many Brayan Resident's Houses. This of course affects sales levels. Increasing daily sales activity results in an accumulation of sales transaction data that continues to increase, thereby burdening data storage. Unfortunately, this data is only stored without further processing. In fact, this data collection holds valuable information.This research uses Market Basket Analysis with the Apriori Algorithm to find association patterns based on consumer shopping behavior. The goal is to identify items that are often purchased together. The research results showed that the combination of Seaweed Dimsum with Tofu Skin Spring Rolls had the highest support value (50%) and the highest confidence (75%).
Sistem Informasi Perpustakaan SMP HKBP Medan Berbasis Web Menggunakan Metode Framework For The Application System Thinking (FAST) Gusti Masari Pangaribuan; Nikita Br. Nababan; Bremi Br Ginting; Nita Syahputri
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i2.2044

Abstract

One of the key components that helps the school's teaching and learning process is the library information system. The objective of this study is to apply the Framework for the Application of Systems Techniques (FAST) approach to the design and development of an online library information system for SMP HKBP Medan. This system is expected to increase efficiency in managing book data, borrowing and returning books as well as making it easier to access information for students and school staff. The use of the FAST method in developing this system involves several stages, including feasibility studies, needs analysis, system design, implementation, and evaluation. The result of this research is a web-based library information system that is user-friendly and able to improve the performance of the HKBP Medan Junior High School library.
Perancangan Dan Implementasi Caesar Chiper Untuk Meningkatkan Keamanan Sistem Informasi Akademik Sekolah Berbasis Android Alif Azhar Amsyari; Bayu Gunawan; Rizky Hamdani; Sri Panca Rani; Nita Syahputri
Saturnus : Jurnal Teknologi dan Sistem Informasi Vol. 2 No. 3 (2024): Juli : Saturnus : Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v2i3.205

Abstract

This research focuses on the design and implementation of the Caesar Cipher method to improve the security of an Android-based School Academic Information System. In this digital era, data security is a major concern, especially in school academic information systems that manage important data. The Caesar Cipher method, as a simple and easy to implement encryption technique, is used in this research. The research results show that the implementation of Caesar Cipher has succeeded in increasing data security in the system. While this method does not provide a very high level of security, it can be part of a more complex security approach. Overall, this research shows that the design and implementation of Caesar Cipher is an effective step in improving the security of Android-based school academic information systems.
Analysis of the Impact of Backpropagation Hyperparameter Optimization on Heart Disease Prediction Models Nita Syahputri; Putrama Alkhairi; Enok Tuti Alawiah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6473

Abstract

Heart disease is a major global health issue, highlighting the need for early and accurate prediction to reduce complications and improve patient outcomes. The Backpropagation Neural Network (BPNN) is a widely used method for heart disease prediction, but its performance relies heavily on proper hyperparameter selection, including neuron count, activation function, optimizer, and batch size. This study analyzed the impact of hyperparameter optimization on BPNN performance. A standard BPNN model was compared with an optimized version, where key hyperparameters were fine-tuned to enhance predictive accuracy and stability. Both models were trained and tested on the same dataset, and their performance was evaluated using Accuracy, Precision, Recall, Mean Squared Error (MSE), and Mean Absolute Error (MAE). The results show that the optimized model achieves a slightly better accuracy (99.11% vs. 99.09%) and lower error rates (MSE and MAE of 0.0089 vs. 0.0091). It also demonstrates higher precision, reflecting an improved capability in correctly identifying heart disease cases. Although the performance gap was small, the optimized model showed a more balanced and consistent outcome. These findings highlight the importance of hyperparameter tuning for improving neural network models for medical prediction. This study contributes to the development of more accurate and reliable AI tools for the early diagnosis of heart disease. Future studies may apply advanced optimization techniques, such as Bayesian Optimization or Genetic Algorithms, and use larger and more diverse datasets to enhance model generalization.
Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Pada Toko Iblite Luxury Menggunakan Algoritma Apriori Anggi Canita Simanjuntak; Miranda Elisabet Sitanggang; Muhairoh Indah Cahyani; Nita Syahputri
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 3 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i3.106

Abstract

Data mining is a technique to dig up new information from a data warehouse, information is seen as very important and valuable because by mastering information it is easy to achieve a goal, this makes everyone compete to obtain information, as well as in trading businesses such as the Iblite Luxury store. This store is located in Medan close to residents' houses, Sales transaction data will continue to grow, causing data storage to be even larger. Sales transaction data is only used as an archive without being properly utilized. Basically, a dataset has very useful information. Market basket analysis with a priori algorithm is one of the data mining methods that aims to find association patterns based on consumer shopping patterns, so that it can be known what items of goods are purchased in a At the same time, the results of this study found that the highest support and confidence values were Ysl and Chanel with a support value of 50% and confidence of 75%.