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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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Implementasi Data Mining Dalam Mengelompokkan Jumlah Penduduk Miskin Berdasarkan Provinsi Menggunakan Algoritma K-Means Yuni Radana Sembiring; S Saifullah; Riki Winanjaya
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 2 (2021): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i2.67

Abstract

Poverty is a certain condition that is below the standard line of minimum needs, good for food and non-food. Poor households generally have a greater average number of members compared to households that only have members who have fewer members. This situation is followed by the low level of education of household heads and workers who generally only work in the agricultural sector. Factors such as education, labor, health, fertility, housing, and the environment are a picture of the level of people’s welfare which is tought to affect the amount of proverty. This study used data sourced from the Central Bureau of statistics the year 2007-2019. The method used is Datamining the K-Means Clustering, Clustering is a method used in datamining the how it works find and classify data that has a semblance and characteristics of data between one another with the data. Using this algorithm the data already obtained can be grouped into Clusters based on this data. This data can be entered to the local Government to recommend to the Government so that the Government can handle the number of poor people in this country.
Perancangan Aplikasi Kamus Bahasa Indonesia-Sentani Berbasis Android Agung Dwi Saputro; Feby Seru
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.v4i4.254

Abstract

Sentani is one of the regional languages in Papua which is experiencing a shift and signs of extinction due to the decreasing number of speakers and no longer being used in both formal and informal forums. Even many Sentani children who live on villages far from urban areas are starting don’t understand the Sentani language. The aim of this research is to create an Android-based Indonesian-Sentani dictionary application that can be used as a learning tool. The research method used in this research is a qualitative method that focuses on a case study of creating a Sentani language dictionary application. The research began by collecting data consisting of observation, interviews and literature study.
Identifikasi Pemenang Tender Pengadaan Barang Menggunakan Metode TOPSIS Handayani Metha Putri
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.v4i1.112

Abstract

PTBA UPO is one of the companies that opens tender opportunities for other companies to meet their needs. To facilitate the decision-making process, a Decision Support System is needed. This study aims to assist companies in determining tender winners in the supply of goods with suitable criteria. This study will select one of the companies that bid with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Based on the guidebook that has been set by the company, the criteria used in this study are the company's work methods, goods selection system, workforce that meets the requirements and work experience of companies participating in tenders. Companies that meet the criteria and have the highest ranking from the TOPSIS process can become tender winners. This research can be used as input to the implementing committee as a basis for making decisions in selecting the tender winner.
Perancangan User Interface Untuk Meningkatkan User Experience Menggunakan Metode Human Centered Design Pada Web E-Commerce CV. Cipta Karya Meubel Jepara Kartiko Haryanto; Widiyanto Tri Handoko
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.v5i1.338

Abstract

E-commerce is the use of communication networks and computers to conduct business processes. Currently, many independent businesses facilitate sellers and buyers by providing convenience in digital transactions, including businesses in the furniture sales sector. With e-commerce, the target audience spans across different regions and generations, making furniture sales at CV. Cipta Karya Meubel not limited to the local population alone. CV. Cipta Karya Meubel Jepara requires an e-commerce platform with a user interface that is easily understandable by people from various backgrounds to enhance the user experience. To address and identify usability issues specifically, a user interface design process is needed, utilizing the Human-Centered Design method and evaluating usability using the Heuristic Evaluation (HE) method. This evaluation and design process is conducted to improve the comfort of using the e-commerce application. From the research findings, it can be concluded that the Human-Centered Design (HCD) and Heuristic Evaluation methods can simplify the application design process and align it with user needs.
Sistem Informasi Manajemen Aset (SIMASET) Berbasis Web Herdian Afrody; Wida Prima Mustika; Andi Sanjaya
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.v4i2.163

Abstract

Assets are the most important resource for an individual or an organization that owns them, because assets are tools that support the activities of an organization. As time goes by the assets in the company will experience many changes (increase and decrease) that apply very quickly and that also happens to PT. Asiamadya Selaras. To support operational activities, PT. Asiamadya Selaras still uses a semi-computerized system, namely using Microsoft Excel in managing existing assets. This is less efficient in terms of time, effort and cost. As technology continues to develop, it can be used to overcome some of the obstacles currently faced, such as by creating a system that assists in asset management to prevent data damage or loss. Web-based system development is used with system modeling, namely UML (Unified Modeling Language), including use case, activity, class, and sequence diagrams. The asset management system development methodology uses the waterfall model, PHP programming with the Laravel framework, and MySQL database.
Analisis Kinerja Jaringan Menggunakan Metode PCQ pada Jaringan Internet Kelurahan Butuh Andika Wahyu Kurniawan; Rissal Efendi
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.v5i2.351

Abstract

The aim of this research is to improve and analyze internet network performance by applying the PCQ (Per Connection Queue) method in the bandwidth management system. The PCQ (Per Connection Queuing) method is a network traffic management technique that allocates bandwidth fairly to each active connection. This method allows network administrators to control network traffic and prioritize low-bandwidth connections. The PCQ method is used to overcome problems that often occur in internet network performance, such as unfair distribution of bandwidth. In analyzing computer network performance using the PCQ method, research is carried out to measure network performance using various parameters such as throughput, delay, jitter, packet loss. This research often compares network performance with and without using the PCQ method, as well as comparisons with other network traffic management methods. Using the PCQ method can fix problems that often occur in internet network performance which has an imbalance in bandwidth usage between one network user and another. The results of this research can be concluded that the use of the PCQ method greatly influences network performance for the better due to the distribution of bandwidth evenly. For this reason, this research is an important contribution in improving bandwidth management that is more effective and efficient
Sistem Pendukung Keputusan Pembuatan Pusat Oleh-oleh Menurut Kecamatan di Temanggung menggunakan Metode SAW Bramastya Arya Gandhi Rusmantara; Adi Nugroho
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.v4i3.208

Abstract

Indonesia's economic condition, especially in Temanggung Regency, has experienced a significant increase, including in the tourism sector after the COVID-19 pandemic. This study aims to find out the best sub-districts in the Temanggung district as places for the construction of souvenir centers that can support the tourism sector. This study uses the SAW method and quantitative methods to determine the best decision. Data processing in this study was assisted by using Microsoft Excel. The data for this study used 19 sub-districts in the Temanggung district. The data that has been processed produce the best decision for the construction of souvenir centers in Temanggung district, namely, Ngadirejo District (A12; 129.16667), Kedu District (A9; 126.6667), and Parakan District (A13; 126.6667). Further researchers can develop this research by combining several decision support methods such as AHP, ELECTRE, or PROMETHEE with the SAW method. This research is expected to help related parties to develop the development of a souvenir center as a support for the tourism sector in Temanggung district
Penerapan Algoritma Backpropagation Dalam Memprediksi Jumlah Pengguna Kereta Api Di Pulau Sumatera Vivi Auladina; Jaya Tata Hardinata; M. Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.58

Abstract

The purpose of this study is to analyze and test whether the number of train passengers in Indonesia can be predicted by using artificial intelligence techniques. In this study, the artificial intelligence technique used is the Artificial Neural Network Technique (ANN) with the Backpropagation method. Artificial neural network is a method that has been widely used to solve forecasting cases. The main difficulties in implementing neural network methods in forecasting are finding the right architectural combination, determining the appropriate learning rate parameter values and selecting the optimal training algorithm. The research data is secondary data sourced from the bps.go.id website from 2006 - 2019. The data in this study were computerized using the matlab application. From the 5 architectural models used, the best model based on computerized results with the Matlab application is 3-3-1 with an output value of 0.0215923 MSE. The accuracy of the truth obtained is 92%.
Comparative Analysis of Machine Learning Models for Emotion Classification in Textual Data Gregorius Airlangga
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.v5i2.383

Abstract

This research presents a comprehensive comparative analysis of various machine learning models for emotion classification within textual data, aiming to identify the most effective architectures for understanding and interpreting emotional undertones. With the increasing prevalence of digital communications, the ability to accurately classify emotions in text has significant implications across numerous domains, including social media analysis, customer service, and mental health monitoring. This study evaluates traditional algorithms, such as Logistic Regression, and advanced deep learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), Convolutional Neural Networks combined with Recurrent Neural Networks (CNN-RNN), Autoencoders, and Transformers. Through meticulous cross-validation, hyperparameter tuning, and performance evaluation based on accuracy, precision, recall, and F1 scores, the research elucidates the strengths and weaknesses of each model. LSTM and GRU models demonstrated superior performance, highlighting the importance of sequential data processing capabilities. In contrast, the Autoencoder model underperformed, underscoring the necessity for careful model selection tailored to the task's specifics. Surprisingly, Logistic Regression showed notable efficacy, advocating for its potential utility in scenarios prioritizing computational efficiency. This study enhances the understanding of affective computing within natural language processing, offering insights into the strategic deployment of machine learning models for emotion recognition and paving the way for future advancements in the field.
Analisa Dan Optimasi Pada Teknologi Jaringan Wireless Pada Ruangan Laboratorium Dan Kantor Gedung Mangudu Universitas Telkom Menggunakan Wireless Site Survey Hasrinaldi Hasniman Harun; Umar Yunan K.S.H; M. Teguh Kurniawan
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.v4i4.244

Abstract

The Mangudu Building is a facility at Telkom University designed to accommodate the university's industrial engineering department, primarily for the needs of introducing manufacturing production. The building is equipped with an internal network to accommodate internet access. However, the building is relatively old and has been left in its current state. The networking equipment in use can also be considered outdated. Therefore, a reevaluation is necessary to determine the extent of wireless network implementation and to identify network issues in the building. The condition of the wireless network in the Mangudu Building yields results indicating that the signal strength emitted by the Cisco Aironet 1700i access point on the first-floor receive a less favorable indicator value as their signal strength is above -60 dBm. Therefore, the author proposes replacing the access point with the Ruijie RG-AP880-AR and adding a second access point. The proposed changes result in the majority of rooms on both the first and second floors having a very good indicator value, with readings below -50 dBm for both the 2.4 GHz and 5 GHz frequencies

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