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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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Penerapan Metode K-Means Dalam Mengelompokkan Banyaknya Desa/Kelurahan Menurut Jenis Pencemaran Lingkungan Hidup Berdasarkan Provinsi Agus Tiranda Sipayung; S Saifullah; Riki Winanjaya
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 4 (2020): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i4.35

Abstract

Environmental pollution is hazardous for every living thing; environmental pollution can cause an imbalance in the environment or existing ecosystem. This study discusses the grouping of villages according to the type of environmental pollution based on the provinces in Indonesia. The method used is DataMining with the K-means Clustering algorithm. By using this method, the data obtained can be grouped into 2 clusters. This study uses secondary data, namely data obtained through intermediary media recorded on the Central Bureau of Statistics website with the URL address: http://www.bps.go.id. The results obtained in this study are grouping environmental pollution into 2 clusters, namely the highest cluster and the lowest cluster. In this research, it is hoped that it can provide input to related government parties to pay more attention to the provinces included in the highest cluster to tackle environmental pollution in the province.
Penerapan Teorema Bayes Pada Sistem Pakar Untuk Mendeteksi Dini Penyakit Tuberkulosis (Studi Kasus Di Rs. Tentara Dr. Reksodiwiryo Padang) Fadil Idensia; Y Yuhandri; Billy Hendrik
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 2 (2024): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i2.369

Abstract

Tuberculosis (TB) is an infectious disease that is still a global health problem, including in Indonesia. Early detection of this disease is crucial for effective treatment. In order to improve early detection of TB, this research aims to apply the Bayes Theorem method to the development of an expert system. The case study was conducted at Dr. Reksodiwiryo, Padang, where the percentage of Tuberculosis based on the method has been identified. The Bayes Theorem method is implemented in an expert system to provide early diagnosis to patients suspected of having TB. Expert system testing was carried out to evaluate the accuracy of the diagnosis, with an average calculation result using Bayes' theorem of 80%. The results of this research indicate that the application of Bayes' Theorem in an expert system can be an effective tool in early detection of Tuberculosis. The practical implication of this research is to increase the capabilities of the Dr. Army Hospital. Reksodiwiryo Padang in treating TB early and accurately, as well as contributing to efforts to prevent and control this disease more efficiently.
Pemutakhiran Sistem Virtualisasi Penuh (Hypervisor) Dalam Segi Perfoma Dengan Metode GPU Passtrough Nanda Maulana; Jeffri Alfa Razaq
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 4 (2023): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i4.230

Abstract

This research aims to update the full virtualization system (hypervisor) by utilizing GPU passthrough method to enhance system performance. Hypervisor is a software that enables the use of multiple virtual machines on a single physical system. Despite being a popular solution in virtualization environments, challenges related to performance still exist. In this study, the GPU passthrough method is employed to provide direct access to the graphics card for virtual machines, which can significantly improve system performance. The methodology used in this research includes an analysis of virtualization system performance when utilizing GPU passthrough. Several tests and performance measurements are conducted to compare the system's performance with and without the GPU passthrough method. The results of this research are expected to provide a better understanding of the utilization of GPU passthrough method in full virtualization systems and its impact on performance. Furthermore, this study can also offer practical guidance to virtualization system developers in upgrading their systems with more efficient methods. In this context, the GPU passthrough method allows virtual machines to directly utilize graphic resources from the physical graphics card, meaning virtual machines can enjoy higher graphical performance compared to conventional approaches. Using this method provides opportunities to enhance visual quality, speed, and responsiveness of applications run in virtual environments. Overall, this research holds the potential to address performance constraints associated with hypervisors and provide a significant advancement in virtualization technology. By gaining a deeper understanding of the implementation of GPU passthrough, virtualization system developers can optimize their system's performance and deliver a better experience for virtual machine users. It is also hoped that this research will serve as a foundation for further advancements in the field of virtualization and contribute positively to the development of future computing technologies.
Perancangan Mobile Game Edukasi Pengenalan Buah-Buahan untuk Sekolah Dasar Michael David; Eunike Insani; Daniel Tumangger; Siti Aisyah
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.v2i4.81

Abstract

The purpose of this research is to look into the design of an educational mobile game for the introduction of fruits in elementary schools. This fruit recognition educational mobile game is a modern learning application that uses Android technology to make learning more convenient anywhere and at any time. Learning activities are more effective when there are media that can attract the senses and attract interest, as there are image objects, attractive displays, and pronunciation of the letters of the alphabet in this educational mobile game. This game application also includes exercises to help you improve your learning spirit. This application employs a qualitative methodology. The goal of this study is to assist elementary school students who are having difficulty learning.
Metode Adaptive Neuro-Fuzzy Inference System (ANFIS) Untuk Memprediksi Kelulusan Mahasiswa F Fauziah
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 1 (2023): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i1.121

Abstract

To assure the quality of graduates, it is required to estimate the graduation rate of active students based on variables that influence it, such as first-through-sixth-semester GPAs, the number of credits taken each semester, etc. Graduation rate is a criterion for evaluating the accreditation of study programs and institutions, making it one of the benchmarks for higher education management policies. In order to forecast student graduation rates, an artificial neural network algorithm based on the Adaptive Neuro-Fuzzy Inference System approach was used to analyze data in this study. This technique is commonly employed for problem prediction. In the implementation of this technique, the sample data consist of around 627 student data from the classes of 2015 through 2018. With the result that predicts the number of years and months till student graduation. Good accuracy results were obtained with the approach utilized, which included the kind of membership function, namely gauss mf, gbell mf, trim mf, and traf mf. On average, it provided a R value of 0.99 at epoch values between 50 and 500, an MSE value of 0.04, and an accuracy rate of 96.97%
Analisa Penerimaan Tekhnologi Artificial Intelligence Generative Dengan Menggunakan Metode UTAUT 2 Ibnu Alfarobi; Sofian Wira Hadi; Amin Nur Rais; W Warjiyono; Wawan Kurniawan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 1 (2024): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i1.329

Abstract

The rapid development of information and communication technology has changed various aspects of human life and the impact of current technological developments is that there are many new technologies and of course new technology can provide benefits for users and developers. AI has had an impact on aspects of economics, politics, science and education in the current era. One of the most popular forms of AI is ChatGPT. The success of a new technology will of course be assessed and felt by users who will later be assessed whether the new technology will help and meet their needs. Several previous studies tested AI using Google Trends, Analysis of Trends in Indonesian People's Interest in Artificial Intelligence in Welcoming Society 5.0: Study using Google Trends. Analyzing the acceptance of Generative AI technology using the UTAUT 2 model is the main objective of this research. Factors that have a very positive and significant influence are the habit factors on behavior intention and habit on use behavior
Sistem Rekomendasi Jurusan Kuliah dalam Pengambilan Keputusan Menggunakan Metode MOORA Ade Rizka; Ranti Eka Putri; Yanti Yusman; Maulana Fajar
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 2 (2023): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i2.172

Abstract

The dependence of the current generation Z on technology is a momentum to develop technological facilities in various aspects of life. In the educational aspect, it is important to take advantage of technological facilities by implementing systems and methods to provide maximum results. The level of education has several stages that have different concentrations and are increasingly conical. SMK students often experience difficulties or obstacles in choosing a college major. This is because students focus more on popular majors, even though there is a possibility that these majors are not appropriate. The research uses the MOORA method to help provide alternative recommendations for majors based on criteria of knowledgeability, skills ability, professional interest, object interest, and talent in decision-making. The MOORA method processes criteria optimally with rules that are appropriate to the problem and data. Alternative college majors based on 14 choices of college majors. The results of the MOORA method research based on alternative data on college majors that match the criteria can provide recommendations for college majors that Panca Budi Vocational School (STM) students can choose to continue their education in tertiary institutions. System testing produces an alternative with the largest y value, namely 31.2 for the Law major. The alternative with the largest y value will be the system's recommended alternative. The recommendation system for college majors can overcome difficulties or obstacles for students in choosing a college major, thus facilitating the lecture process because students can focus more on studying.
Penerapan Metode Moora Dalam Menentukan Parfume Terbaik Berdasarkan Kepribadian Halimatusakdiah Pohan; Dwita Elisa Sinaga
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 2 (2020): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i2.21

Abstract

Parfume is one of the distinctive scented liquids that people use to eliminate body odor, in the use of parfume, people tend to have different types of parfume according to their personality type. Based on many personalities that exist in society, the writer uses one personality Sangunis where someone who has this personality is cheerful, friendly, warm and friendly but prefers a pungent aroma because usually someone with a Sangunins personality likes to socialize wherever they are. In this article the author uses one of the SPK methods MOORA, which has the advantage of being simple, stable and easy to implement, so it is hoped that the Moora method can help someone in making a perfume selection decision.
Penerapan Algoritma K-Means Dalam Pengklasteran Hasil Evaluasi Akademik Mahasiswa Fitri Safnita; Sarjon Defit; Gunadi Widi Nurcahyo
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 2 (2024): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i2.360

Abstract

Several institutions that have utilized computer-based information systems for many years certainly have quite large amounts of data. The data generated and stored in a computer system is designed to be fast and accurate in both operation and administration. This data is designed for reporting and analysis that uses that data. It turns out that there is a lot of data available, with so much data we are increasingly faced with the question, "What knowledge can we gain from this data?" The K-Means algorithm is an iterative clustering algorithm that partitions a data set into a number of clusters that are initially determined. The K-Means algorithm is an iterative clustering algorithm that partitions a data set into a number of clusters that are initially determined. The K-Means algorithm is easy to implement and run, relatively fast, easy to adapt, commonly used in practice. The parameter that must be entered when using the K-Means algorithm is the K value. The K value is generally used based on previously known information regarding how many clusters appear in This research aims to group students based on academic evaluation results. The method used to manage student academic data uses the Data Mining method with the K-Means Clustering Algorithm. The dataset processed in this research comes from the Faculty of Engineering, Informatics Engineering Study Program, Islamic University of Riau. The dataset consists of 180 student data starting from semester 1 to semester 4. The results obtained from this research are in the form of grouping students based on the achievement student cluster, there are 104 students with a percentage of 57.72%, the student cluster with potential for achievement is 62 students with a percentage of 34 .41%, the potentially problematic student cluster has 10 students with a percentage of 5.55%, and the problematic student cluster has 4 students with a percentage of 2.22%. Therefore, it is hoped that the results of this research will provide new knowledge that can be used as a source of information and function as a reference model for academic planners to monitor and predict the development of each student's academic performance.
Sistem Pendukung Keputusan Penerima Beasiswa Menggunakan Metode Simple Multi Attribute Rating Technique (SMART) Muhammad Risco Ramadhan; Fiftin Noviyanto
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 3 (2023): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i3.217

Abstract

Scholarships is a form of appreciation and giving in the form of financial support distributed to individuals with the aim of fulfilling the sustainability of the level of education being undertaken. University has provided various scholarships with various criteria for its students, but scholarships have their own goals and targets, namely, students who really fit the criteria required by the scholarship so that scholarships can be right on target according to the wishes of the organizers. For these purposes, proper analysis and calculations are needed, but scholarship selection is still done manually, so it takes quite a long time and the results calculated manually are less objective and not transparent. To solve this problem, a decision-support system was built to determine the selection of scholarship recipients. The system built using a decision support system using the simple multi-attribute rating technique (SMART) method was used to handle multi-criteria problems. The decision-making method is aimed at criterion problems that have many values owned by each alternative in each of the criteria that have calculated weight values. The research process was carried out using the Waterfall Modified approach to ensure that the output of the research product can run well, and the usability value and user experience are good. The process of evaluating the research output was carried out using the Blackbox approach and System Usability Scale approach. The results of the evaluation of the system achieved an average value above the standard to achieve usability and user experience goals.

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