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Sekretariat KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen) Jln. Jendral Sudirman Blok A No. 1/2/3 Kota Pematang Siantar, Sumatera Utara 21127
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Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Published by Sekolah Tinggi Ilmu Komputer Tunas Bangsa
ISSN : -     EISSN : 2720992X     DOI : 10.30645
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen) adalah sebuah jurnal peer-review secara online yang diterbitkan bertujuan sebagai sebuah forum penerbitan tingkat nasional di Indonesia bagi para peneliti, profesional, Mahasiswa dan praktisi dari industri dalam bidang Ilmu Kecerdasan Buatan. KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen) menerbitkan hasil karya asli dari penelitian terunggul dan termaju pada semua topik yang berkaitan dengan sistem informasi. KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen) terbit 4 (empat) nomor dalam setahun. Artikel yang telah dinyatakan diterima akan diterbitkan dalam nomor In-Press sebelum nomor regular terbit.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 419 Documents
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Faktor-Faktor Yang Menentukan Keberhasilan Produk Melalui Desain Logo Pada Produk Og Home Care Sahtriando Sijabat; Tiarmi Arta Indah; Fikri Ramadhan; Atika Ramadhani Pulungan; Sandi Hiskia Hasibuan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 4 (2021): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i4.82

Abstract

OC Home Care Soap is one of the products whose sales are offline and online at an affordable price. The more soap products that appear, it is required to be more creative in creating products with that made a logo design so that it becomes a trigger thing that will be seen by many people. Logo design not only displays the product's brand, but the logo design also presents the message or information of the product. In running a business, questions always arise about the importance of a logo for product success, this is what research will do. This research method uses the Google form feature to create a questionnaire which is then given to related parties.
Strategi Pengembangan Platform Global Transaction Syariah (GTS) dengan Design Thinking, Co-Creation dan Agile Software Development Setiawan, Fajar Ari; Wahyurini, Octaviyanti Dwi
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.411

Abstract

Banks are no longer a place where customers attend and make transactions, but banks are something that customers do. This is a response to the rapid advances in technology that have an impact on banking services. The aim of this research is to develop the quality and capability of the Global Transaction Sharia Platform (GTS) by taking a case study at Bank Syariah Indonesia (BSI). This research combines the Design Thinking approach with the Double Diamond Method, Co-creation and Agile Software Development (ASD). Design Thinking with the Double Diamond method is used to understand customer needs and develop appropriate features, Co-creation is the application of collaboration with various stakeholders in carrying out the design process, while ASD is used for rapid development. The results of this research are the development of the GTS platform which will provide solutions to customer transaction needs and increase bank transaction platform capabilities. The Co-creation and ASD approach can make the GTS development process produce a good platform/product with fast process.
Analisa Sentimen Twitter Vaksin Covid-19 di Indonesia dengan Metode Support Vector Machine Sulastri, S; Nur, Fahad Abdul
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.443

Abstract

In today's digital era, Twitter is very widely used by the public as a means of communication. These facilities provide freedom in expressing opinions and / or opinions on twitter social media. Opinions in social media twitter can be called tweets. Opinions that often arise are very diverse in expression and meaning in the context of the problem being discussed. Tweets analyzed in this study are related to the issue of the Coronavirus in Indonesia. The data used in this study, 500 tweet data with 350 training data and 150 test data. The tools used in the classification process is the Python programming language. Then for the method used in the classification is the vector support machine method with the sentiment data used, namely positive and negative. The results are given in the support vector machine method in a value of 66%, with a recall of 61% and a precision of 74%. Therefore, the support vector machine method is quite good in classifying.
Analisis Data Penjualan di Mobile Cell Menggunakan Triple Exponential Smoothing (TES) Putra, Arios Wardana; Pakereng, Magdalena A.Ineke
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.402

Abstract

The increasingly rapid development of digital technology has made the use of cellphones increasingly widespread and used by almost all groups, which makes cellphones one of the basic necessities coupled with accessories where these accessories protect cellphones from damage and make cellphones more attractive. A mobile cell shop is a shop that sells cellphones and their accessories, but over time, sales have gone up and down due to several problems that have occurred. This research uses the Triple Exponential Smoothing method to analyze and forecast sales at Mobile Cell Shops. The results of the research show that the MAPE (Mean Absolute Percentage Error) value obtained for the 3 existing sales items has an accuracy level of 50%, which means the forecasting is good and feasible. This can provide insight into making the right decisions in making sales.
Implementasi Chatbot dengan pendekatan Natural Language Processing dan Naïve Bayes dalam meningkatkan layanan perusahaan Sebayang, Alvin Christoper; Kharisma, Ivana Lucia; Sujjada, Alun; Kamdan, K
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.434

Abstract

The development of information technology has influenced how organizations provide services to users. Customer service is an activity aimed at ensuring customer satisfaction through the assistance provided by an individual in addressing issues and meeting their needs. However, in certain conditions, customer service may not be able to handle or serve customers, such as outside working hours and recurring general inquiries from users. In this context, Chatbots have become a promising solution to enhance service quality. This study aims to implement a Chatbot with a Natural Language Processing (NLP) approach and Naive Bayes classification method to improve the performance of the Mangcoding web service or PT Anugrah Kreasi Digital. The system development method in this study includes user needs analysis, Chatbot architecture design, NLP model development, and integration with existing web service platforms. The use of NLP methods is expected to improve accuracy so that the Chatbot can understand the users' natural language and provide relevant responses according to their requests. This study uses a qualitative approach to evaluate the performance of the Chatbot in enhancing web services. The results of this study are expected to improve the efficiency of web services through the implementation of a Chatbot with an NLP approach and Naive Bayes classification method, enabling the Chatbot to provide accurate answers. Additionally, it is expected to provide guidance for organizations in utilizing Chatbot technology to improve interactions with users in the context of web-based services.
Pengembangan Aplikasi Ojek Online (BLOON) Berbasis Android Studi Kasus Provinsi Bengkulu Hutagalung, Carli Apriansyah; Rizki, Sestri Novia
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.425

Abstract

Online motorcycle taxi services have become a trending topic as they are considered an innovative solution to enhance the efficiency of traditional motorcycle taxis. Many province in Bengkulu Regency face difficulties in finding reliable transportation services for delivery purposes due to the unavailability of online motorcycle taxi services like Gojek, Grab, or Maxim, which are common in larger cities. This research aims to design the Bengkulu Online Motorcycle Taxi (BLOON) application for Android using the Object-Oriented Analysis and Design (OOAD) methodology. OOAD is an analytical approach that evaluates requirements from the perspective of classes and objects within the problem's domain, surpassing traditional software architecture through the manipulation of system or subsystem objects. The Rapid Application Development (RAD) model is employed in this research. Through thorough analysis, design, testing, and implementation, the Bengkulu Online Motorcycle Taxi application demonstrates successful operation in line with the research objectives and plans. The application of the OOAD methodology proves effective in developing structured applications. 
Synergistic Machine Learning: Enhancing Diabetes Prediction with Hybrid Deep Learning and Ensemble Models Airlangga, Gregorius
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.457

Abstract

Diabetes, a growing global health concern, necessitates improved predictive strategies for early and accurate detection. This study evaluates the efficacy of various machine learning and deep learning models in predicting the onset of diabetes, employing a comprehensive dataset that includes clinical and demographic variables. Traditional machine learning models such as Decision Trees, Random Forest, KNN, and XGBoost provided foundational insights, with ensemble methods showing superior performance. Furthermore, we explored the potential of deep learning by analyzing a Simple Dense Neural Network (DNN), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN). While these individual models yielded valuable findings, particularly in identifying true positive cases, they did not surpass the ensemble techniques in overall accuracy. The pinnacle of our research was the development of a Deep Learning Meta Learner that combined Random Forest and Gradient Boosting predictions, achieving near-perfect classification metrics, and underscoring the strength of model integration. Our findings advocate for a hybrid predictive approach that merges the nuanced feature detection of deep learning with the robust pattern recognition of ensemble models, providing an impactful direction for future diabetes prediction research. This study contributes to the advancement of medical informatics and aims to support healthcare professionals in delivering proactive and personalized patient care.
Penggunaan Snort Sebagai Sistem Pendeteksi Serangan Pada Jaringan Menggunakan Notifikasi Telegram (Kasus Dinas Komunikasi Informatika Dan Persandian Kabupaten Sukabumi) Fergina, Anggun; Ikhsan, Sultan Alif Nur; Alamsyah, Zaenal
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.416

Abstract

Network security has become very important to protect individuals, companies, and agencies from threats such as cyberattacks, and data theft. Therefore, understanding the importance of network security is essential. Based on the interview results, there is a server in the Sukabumi District Command Center managed by DISKOMINFOSAN Sukabumi District, the server is used as an application server. The server does not have a network security monitoring system that provides alerts when there is an attempted attack on the server in real time. One way to improve security on the server is to use an Intrusion Detection System (IDS). IDS is a system intended to detect suspicious activity or attacks on the network. One of the main goals of IDS is to provide warnings against security threats that may occur. Snort is one of the open-source IDS tools. Snort was created to identify network attacks and provide realtime alerts to administrators when identifying certain behaviors or attack patterns. In this study the authors used the SPDLC development method. Security Policy Development Life Cycle (SPDLC) is a system development method that focuses on network security. After testing, it can be concluded that snort can be used as an IDS installed on ubuntu server 22.04, with the rules that have been made snort can detect when someone tries port scanning to the server using masscan and can detect ping attacks aimed at the server in real time. With the script that has been created, snort can send alerts to network administrators using telegram in realtime so that these alerts can be followed up immediately.
Analisis RFM dan K-Means Clustering untuk Segmentasi Pelanggan pada PT. Sanutama Bumi Arto Silamantha, Wiendha Artieka; Hadiono, Kristophorus
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.448

Abstract

This research aims to segment customers at PT. Sanutama Bumi Arto by applying RFM (Recency, Frequency, Monetary) analysis combined with the K-Means Clustering algorithm. RFM analysis is used to identify customer purchasing characteristics based on recency, frequency of purchases and total purchase value (monetary). Then, the K-Means algorithm is used to group customers into different segments based on the similarity of RFM characteristics. This research uses customer transaction data from PT. Sanutama Bumi Arto. The research results show that there are two customer clusters with different characteristics, namely customers with low purchasing levels and customers with high purchasing levels. Customer clusters with high purchasing levels have higher recency, frequency and monetary values compared to customer clusters with low purchasing levels. Cluster evaluation was carried out using the Silhoutte Score (0.44), WSS (972.19) and BSS (1112.73) metrics, which shows that clustering has good performance. It is hoped that the results of this research can provide valuable insight for PT. Sanutama Bumi Arto in understanding customer behavior and developing more effective marketing strategies.
Distribusi Produk Menggunakan Metode Travelling Salesman Problem (TSP) Dengan Konsep Algoritma Heuristik Yendrizal, Y
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.407

Abstract

Searching for solutions in determining the shortest route in product distribution is often found in everyday life. Solutions to solve problems can be designed in the form of diagrams consisting of lines and central points. Examples include finding the shortest route (Traveling salesman problem (TSP). The concept of the Traveling Salesman Problem (TSP) is a classic problem of finding the shortest route that a salesman can take when want to visit several cities without having to visit the same city more than once. The problem that often occurs is that the delivery of goods must be on time to the destination, however, because the locations to be addressed are so many and spread across each region, it makes it very difficult for distributors to deliver. goods according to the specified time, the research objective is expected to be able to help distributors in finding the smallest route for delivering goods both in terms of time and saving gasoline, providing distribution route solution options that can minimize delays in goods delivery and optimize human resource transportation facilities. The Heuristic Algorithm produces the best solution to problems which are part of a more complex problem where delivery of orders from distributors to consumers is maximized. The final result of the TSP process is 240 CBDA=240. This method can help in finding the smallest route solution in distributing goods so that it can be used as a reference to get the best results

Page 27 of 42 | Total Record : 419

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