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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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Sistem Informasi Pengarsipan Surat Berbasis Website Pada Dinas Koperasi UMKM Perdagangan dan Perindustrian Kabupaten Cianjur Fajriati, Dhila Rakhma; Maulana, Haisyam
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.v5i3.404

Abstract

Advances in information technology have created changes in the management of various aspects in various sectors, including letter archiving. In this context, this research aims to overcome the challenges of manual letter filing at Department of Cooperatives for Micro, Small and Medium Enterprises, Trade and Industry, Cianjur Regency. This research proposes a web-based application development method using the Laravel framework with a focus on storing, searching and managing mail. The main feature is to make it easier to quickly search for letters and provide convenience in archiving processing. It is hoped that the application of this application can provide an effective solution to the challenges of letter archiving at Department of Cooperatives for Micro, Small and Medium Enterprises, Trade and Industry, Cianjur Regency, as well as contribute to the development of information technology in the field of letter archiving.
Analisis Performa Raytracing dan MCMC Pada Realisme Visualisasi Obyek 3D Dengan Terintegrasi MIPMapping Budet, Vincensa Woytimena; Himamunanto, Agustinus Rudatyo; Budiati, Haeni
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.v5i3.436

Abstract

The development of computer graphics has resulted in an increasingly realistic and immersive digital world, especially in the field of 3D object representation. One of the techniques for image presentation is ray tracing, however, regular ray tracing requires long computation time. To achieve high realism in 3D objects, complex computational operations and the use of appropriate algorithms are required. In this research, Markov chain Monte carlo (MCMC) algorithm has the potential to achieve realism on a 3D object. This research analyzes the performance comparison between ordinary ray tracing and MCMC algorithm in achieving realism on 3D objects and integrating Mipmapping technology to improve the visual quality of 3D objects. The results are measured by calculating the PSNR value on the rendered object and comparing the noise level of a 3D object rendered with ordinary ray tracing, and ray tracing using the Monte carlo algorithm. The number of samples used were 50 samples of 3D objects tested with Monte Carlo and obtained a result of 94%, and with ordinary ray tracing of 6% which is indicated by the level of distortion or error that occurs in the processed object. This shows that by rendering using the MCMC algorithm the image quality of the rendered object is better than rendering using ordinary ray tracing
Model Penjawab Pertanyaan Otomatis Berdasarkan Peringkat Relevansi Kalimat Menggunakan Model BERT Wibowo, Jati Sasongko; Februariyanti, Herny; Listiyono, Hersatoto
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.v5i3.427

Abstract

This research develops an Automatic Question Answering System based on sentence relevance ranking using BERT model and SQuAD dataset. Performance evaluation is done with F1 Score and Exact Match to assess the accuracy and precision of the answers. This research includes four main approaches: question understanding and keyword identification, sentence relevance ranking using techniques such as cosine similarity or TF-IDF score, use of BERT model to enrich text representation and understand the context in depth, and performance evaluation with F1 Score and Exact Match. The results show F1 Score value of 0.6 and Exact Match value of 0.5. The research objective is to develop a system that excels in answering questions with more accurate and contextualised sentence relevance. The main contribution of this research is the advancement in natural language processing (NLP) by integrating the BERT model, SQuAD dataset, and performance evaluation using rigorous metrics. The system is expected to improve users' access to information with more precise and contextualised answers.
Enhancing Concrete Compressive Strength Prediction with Deep Learning: A Comparative Analysis of Model Architectures 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.v5i3.459

Abstract

The imperative to predict concrete compressive strength accurately is a crucial aspect of modern civil engineering, with significant implications for the safety and cost-effectiveness of construction projects. This research explores the application of deep learning techniques to enhance predictive accuracy in this domain. We conducted a comprehensive comparative analysis of five machine learning models: a Basic neural network model, a Dropout model, a Batch Normalization model, a Deep Dense Neural Network (Deep DNN), and a Convolutional Neural Network (CNN). Utilizing a dataset reflective of various concrete mixtures and their corresponding compressive strengths, each model underwent rigorous evaluation through a five-fold cross-validation scheme. Performance metrics, including Mean Squared Error (MSE) and R-Squared (R²), were computed to assess each model's predictive capabilities. The results indicated that models employing batch normalization and deeper architectures provided superior predictive performance, suggesting that these features are instrumental in understanding the complex relationships between the components of concrete mixtures. The Batch Normalization and Deep DNN models demonstrated remarkable accuracy and consistency, surpassing traditional and CNN models. This study not only enhances the current understanding of material property prediction through machine learning but also paves the way for the development of more efficient and robust predictive tools in civil engineering. The findings underscore the transformative potential of deep learning in material science, emphasizing its ability to deliver nuanced and precise predictions for critical engineering properties.
Perancangan Sistem Deteksi Objek Menggunakan Deep Learning Untuk Mengetahui Ketersediaan Parkir Berbasis Web Fergina, Anggun; Somantri, S; Ayulianti, Radita
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.v5i3.418

Abstract

Parking systems often use visual monitoring by parking guards via CCTV, who sometimes experience problems in finding available empty parking spaces. This can cause inaccuracies in directing parking users to available spaces, increasing traffic congestion around the parking area. Therefore, this research aims to design an object detection system using deep learning technology to ensure the availability of parking spaces through a web-based application using the Yolo v8 and prototype methods. Testing the essence of the system shows that object detection is carried out effectively, with box boundaries that correspond to the presence of vehicles in the parking lot. Web test results show consistency between the number of vehicles detected and the numbers displayed on empty and occupied parking slots. Usability testing involving 60 respondents showed a high level of satisfaction, with an average percentage of 91.20%, indicating the level of suitability of the system to user needs.
Machine Health Monitoring Using An Innovative Mechanical Approach Romayasari, Vera; Auliana, Sigit; Aryono, Gagah Dwiki Putra
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.v5i3.450

Abstract

In today's world, machines are essential in daily life, requiring efficient and safe operation. Tools have been developed to assess machine health by monitoring power usage, temperature, noise, and vibrations. Anomalies in these parameters can indicate potential defects. FFT analyzers, commonly used for vibration measurement, are often too costly for small businesses and may lack the ability to measure speed, temperature, or power usage. This project aims to create a low-cost alternative for health monitoring systems, capable of measuring vibrations, noise, temperature, speed, and power consumption. Integrating an Arduino Uno R3 with sensors and a MATLAB 2018b GUI provides an affordable solution, catering to small firms unable to invest in expensive FFT analyzers
Artificial Neural Networks Pengenalan Pola Pasword Angka Menggunakan Metode Heteroassociative Memory Silvilestari, S `
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.v5i3.409

Abstract

Every important data must be kept confidential so that it is not misused by people who do not have the right to access the data. Data security can be used using the Heteroassociative Memory Method. The Heteroassociative Method is used to collect data from each combination and then become a complex system so that it can be mapped into a system with the resulting values. The problem that often occurs is data security which is often stolen by unauthorized people because the data security key in the form of a numeric password can be hacked easily. The aim of the research is to help maintain data confidentiality by providing a password pattern lock on the system so that it is difficult for data thieves to enter the system. How the Heteroassociative Memory Method works uses weight values determined in such a way that the network can store groupings of patterns. Each group is a pair of vectors. The research results of 8 number patterns with input 1111 0110 1100 1000 0011 1100 1111 1011 produce 4 patterns that match the target, namely pattern 1 to pattern 4 and 4. Patterns that do not match the target, namely pattern 5 to pattern 8. Recognition of number patterns depends on the input target. .
Analisa Manajemen Resiko Keamanan Sistem Informasi Baznas Kampar dengan Metode Failure Mode And Effect Analysis (FMEA) Alriwanda, A; Saputra, Eki; Megawati, M; Ahsyar, Tengku Khairil
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.v5i3.441

Abstract

Risk management is a key element in an organization's activity strategy, one of the existing risk management methods is Failure mode effect and analysis (FMEA). Many researchers use this method to determine the risks that exist in the company. This research was conducted at the National Zakat Amil Agency (BAZNAS) Kampar using FMEA to determine the risks that exist at BAZNAS. In the research, the Risk Priority Number (RPN) was calculated by multiplying Severity, Occurance and Detection. The results obtained in research using FMEA produced 5 failure modes, namely Data, Hardware, Software, People / Human Error and Network and provided recommendations to BAZNAS
Perancangan Berorientasi Objek pada Pembangunan Aplikasi Pemasaran dan Pengolahan Ikan Gusriva, Revi; Sentosa, Rio Bayu; Randa, Dimas 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.v5i3.432

Abstract

The development of information technology has made significant contributions to various fields, including the fishing industry. The Marine and Fisheries Office of West Sumatra Province, particularly in the Field of Enhancing Marine and Fisheries Competitiveness, requires an effective and efficient fish marketing and processing application to improve the competitiveness and productivity of fishermen in West Sumatra. This study aims to design a fish marketing and processing application using an object-oriented approach. This approach is chosen for its ability to model systems more naturally and intuitively, as well as facilitate system maintenance and future development. In the design of this application, the Unified Modeling Language (UML) method is used to visualize the system design. UML provides a set of diagrams that can comprehensively depict the structure and behavior of the system. Some of the diagrams used include use case diagrams, class diagrams, and activity diagrams. This application is built based on the information needs regarding fish prices, ornamental fish, restaurants, fish exports, and various fish products by the community, business actors, and the government, monitoring all fishery products online, and facilitating field officers in data entry.
Penerapan Algoritma Genetika Untuk Mencari Optimasi Kasus TSP Pada 20 Gerai Indomart Rosanti, Yerika Puspa; Triana, Iwel; Pancahayani, Sigit
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.v5i3.423

Abstract

In the delivery of a package, goods, and conducting business, location is a crucial factor to manage. A common issue is the late arrival of packages because delivery couriers cannot find the fastest or most efficient route. This study aims to apply a genetic algorithm to optimize the traveling salesman problem (TSP) for the distribution of goods to 20 Indomaret outlets in the Dago area of Bandung City. TSP is a classic optimization problem that seeks to find the shortest route that visits each city once and returns to the origin city. The genetic algorithm, as a population-based search and optimization method, is used due to its capability to find near-optimal solutions for complex and large problems. This algorithm leverages natural selection mechanisms such as selection, crossover, and mutation to develop solutions from one generation to the next. Initial parameters were set with a population of 100 and a maximum of 500 generations to increase the variety of solutions without taking too much time. The fitness value was obtained by taking the negative of the total distance traveled, and after the iteration process, an optimal result with a fitness value of -0.10 was achieved. It only took 50 seconds to run 500 generations for selecting the distribution route of 20 Indomaret outlets.

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