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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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Pemanfaatan Media Pembelajaran Berbasis AI Untuk Meningkatkan Minat Belajar Siswa SD Negeri 060972 Simalingkar B Medan Baringbing, Elsinta Karolina Br; Rahim, Robbi
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.473

Abstract

The development of time and technology has brought significant progress in the world of education, including the use of AI-based learning media. Many schools are now using technology to facilitate the teaching and learning process, help teachers improve student achievement, and attract learners. This qualitative research uses content analysis to evaluate the use of AI learning media at SD Negeri 060972 Medan. The results show that AI-based learning media is effective in increasing students' interest in learning science subjects in class III. However, the obstacle faced is the lack of available learning media, which hampers teachers' creativity in the learning process
Prediksi Prestasi Siswa SMAN 1 Muntok Berdasarkan Motivasi, Kedisiplinan, dan Sosial Ekonomi dengan Naïve Bayes Endraswari, Putri Mentari; Tou, Nurhaeka
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.505

Abstract

This study aims to predict the achievement of class X students at SMA Negeri 1 Muntok by classifying socio-economic data (parents' income), student learning motivation, and student discipline using the Naive Bayes machine learning method. The approach taken in this study is quantitative, with a total of 104 students from 286 class X students who have gone through the data cleansing stage. Data collection was carried out through distribution and documentation. The Naïve Bayes method is used as a prediction analysis technique with the Python programming language. This study shows that the use of this method has an accuracy of 71%, with the prediction results of socio-economic variables, motivation, and discipline on student achievement showing that the discipline variable shows a stronger correlation with student achievement, compared to other variables.
Analisis Data Mining Menggunakan Algoritma C 4.5 Dalam Memprediksi Penerima Bantuan Sosial Yemi, Leonardo; Defit, Sarjon; Sumijan, S
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.496

Abstract

Poverty is one of the highest problems most often experienced by various developing countries, there are many ways to overcome the purpose of social assistance is to overcome poverty, social assistance is usually provided by the government and non-profit organizations to groups of people who have economic limitations. The purpose of this study was to help recipients of social assistance to be right on target and can help people with limitations. One of the techniques used in data analysis is data mining. This study identifies recipients of social assistance using data mining efficiently and fairly. and testing the rapidminer application in the prediction process using the C4.5 algorithm. This research dataset uses 80 data based on data on recipients of social assistance in the Jati sub-district, Padang city. The results of the C4.5 algorithm performance test were able to present prediction analysis output with a very good level of accuracy, namely 93.75%. These results are quite evident that the C4.5 algorithm is able to present maximum prediction output in determining recipients of social assistance in the Jati sub-district, Padang city for the next period. Based on these results, it can facilitate and accelerate decision-making related to determining the receipt of social assistance by applying the C4.5 algorithm and can provide more accurate results.
Optimalisasi Database Mysql Pada Sistem Perancangan Sistem Housekeeping Transaction History Dengan Pentaho Data Integration Simanjuntak, Yohanes Albryan; Wowor, Alz Danny
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 6, No 1 (2025): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v6i1.542

Abstract

The volume of transaction data in the banking industry is growing with the increase in customers and transaction complexity. Ineffi-cient data management can lead to server overload, affect system performance, and hinder the delivery of fast, accurate services. Housekeeping processes are needed to move inactive data to sepa-rate storage, allowing the main server to function more efficiently. Pentaho Data Integration (PDI) offers an effective solution for man-aging the ETL (Extract, Transform, Load) process, which is crucial for data housekeeping. This research aims to optimize the manage-ment of banking transaction data using PDI to reduce server load and improve operational efficiency. This quantitative study applies an experimental method, with the ETL process managing Bank XYZ’s transaction data older than six months. The study uses trans-action data from Bank XYZ’s MySQL server, which will be trans-ferred to a data warehouse. The analysis applies clustering algo-rithms to filter and separate active from inactive transactions. The implementation of PDI for housekeeping effectively reduces server load and improves data management efficiency, significantly lower-ing processing time. The combined use of clustering algorithms and PDI delivers substantial improvements in managing banking transac-tion data, enhancing operational efficiency while significantly re-ducing the load on the main server
Implementasi Sistem Odoo Proses Planning Menu dan Reporting Menggunakan Metode RAD Pada UMKM Dapurbeta Bagir, Syeikh; Budiyono, Avon
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.487

Abstract

Currently, many small and medium enterprises (SMEs) in the food and beverage sector are growing; however, most face challenges in sustaining their businesses, particularly due to competition, poor management, and a lack of technological knowledge. Digitalization has become a crucial solution to address these issues, especially in data collection and analysis that support business decision-making. Dapurbeta, a restaurant offering traditional Indonesian dishes that frequently change monthly, faces challenges in menu planning and reporting processes due to the lack of an integrated system. To address these issues, Dapurbeta implemented an Enterprise Resource Planning (ERP) system using the Odoo application and the Rapid Application Development (RAD) method. The outcomes of this research include the design of business processes tailored to Dapurbeta’s needs, as well as the implementation of a menu planning module and dashboard configured in Odoo. This system is expected to improve the company's operations and facilitate decision-making, enabling Dapurbeta to remain sustainable and competitive in the long term.
Implementasi Binarisasi Citra Menggunkan Metode K-Nearest Neighbor Untuk Mengindentifikasi Bawang Bombay Merah dan Bawang Bombay Putih Rahmad, R; Syafril, S; Ramadhanu, Agung
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.519

Abstract

The processing of digital image data is increasingly being developed and applied in various fields, one of which is object identification based on shape and color. This research aims to implement an image binarization method using the K-Nearest Neighbor (K-NN) method to identify two types of onions, namely red onions and white onions. The binarization method is used to convert color images into binary images, facilitating the feature extraction process. In this study, the features extracted from onion images include texture, shape, and color. K-NN is used as a classification algorithm to differentiate between the two types of onions based on these features. The results of the research indicate that the image binarization method and K-NN can identify red onions and white onions with a fairly high level of accuracy. The results of this implementation are expected to contribute to the development of an automatic recognition system for the classification of agricultural commodities.
Prediksi Klasifikasi jumlah Pembaca Sebuah Artikel pada Jurnal Biram Samtani Dengan Metode Bayesian Classification S, Richasanty Septima; Zulfa, Ira; Gemasih, Husna; Saputra, Mahmuda; Israk, Al
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.478

Abstract

One of the open access Open Journal System (OJS)-based reading media is the Biramsamtani Journal, which is the official publication media of scientific articles published by the journal manager, namely the Institute for Research and Community Service of Gajah Putih University, Central Aceh, Indonesia. Until now, the number of scientific articles that have been published is 76 articles with a total of 26,938 viewers read in 10 editions, 7 volumes, and for 5 years of publication. In the Biram Samtani Journal, an uneven and erratic number of readers was found. Where the causative factors that cannot be determined are due to too many abstracts, the position of the article in the published edition or the category of the article that needs to be adjusted to the month of publication. This problem will be studied using data mining by analyzing data using Bayesian Classification. From the test results obtained to predict the number of readers, the best obtained is model 2 with the composition of training data and 80:20 test data with an accuracy of 79.92%, accuracy of 80.15% and recall of 72.36% while for the classification of the number of readers in Biramsamtani journal articles based on the probability value of 47.7% (Low), 30.76% (High), and 21.53% (Medium).
Analisis User Exprience Pada Web Dapodik Dinas Pendidikan Oku Selatan Menggunakan Metode System Usability Scale (SUS) Apriliansyah, Rendi; Halim, R. M. Nasrul
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.510

Abstract

The Dapodik application is a web-based data collection application which is one of the main sources for formulating government policies. In the Dapodik application, there is several data that is managed, including school data, infrastructure, students, teachers and education staff. The data or information produced is influenced by the quality of the Dapodik application itself. This research aims to analyze the user experience of the South OKU Regency Dapodik website using the System Usability Scale (SUS) method. This method is used for user interface and user experience (UX) from the perspective of usability and user satisfaction. The evaluation results are then analyzed to identify problems found in the user experience.  The final SUS score from the responses of 30 respondents was 53.4, indicating that overall this application is in the OK category with an adequate level of usability. Ease of use, data input processing speed, and interface display received high ratings from respondents, reflecting that the application is well designed in terms of functionality and user friendliness
Rancangan Sistem Informasi Barang Inventaris Berbasis Website Pada Sekolah Tinggi Ilmu Manajemen Sukma Siregar, Yulia Rahma; Rahim, Robbi
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.469

Abstract

This research aims to design a website-based inventory information system at Sukma College of Management. This system is expected to assist in managing inventory data efficiently and effectively. The methodology used in this research includes requirements analysis, system design, implementation, and testing. The result of this research is an information system that is able to record, monitor, and report inventory items in real-time. The system is also equipped with search, grouping, and automatic notification features to facilitate inventory management. With this system, it is expected that the administration process of inventory goods at Sukma College of Management can run more structured and integrated, thereby increasing accuracy and efficiency in managing inventory data.
Penggunaan YOLOv8 untuk Deteksi Penyakit Daun Kopi Bitra, Marcelino; Dewi, Christine
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.501

Abstract

One of the products of plantation with a significant role in economic activities in Indonesia is coffee. But, coffee production in Indonesia is experienced a decline, where one of the causes is pest and disease attacks. Artificial intelligence can be a solution to help farmers detect diseases in coffee plants using object detection algorithm. This research uses the YOLOv8 object detection algorithm to carry out detection of the state and diseases of coffee plant leaves which are divided into four classifications, namely miner, rust, phoma and healthy. The research was conducted in three experimental scenarios which were differentiated based on a comparison of data distribution in the test set, validation set, and test set, where in sequence of train, validation, and test, the first scenario had a comparison of 80:10:10, the second scenario 70: 15:15, and third scenario 70:20:10. The research process using the YOLOv8s model got a model with the best performance results in data comparison of 70% train set, 20% validation set, and 10% test set. The best performing model has a mAP value of 97.8%, precision 95.2%, recall 96.6%, and f1-score 96%.

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