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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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Visualisasi Dashboard Business Intelligence Untuk Analisa Ketersediaan Tenaga Kesehatan Pada Saat Covid-19 Di Jakarta Menggunakan Tableau Panji Islami Anakku; E Erizal; Firman Noor Hasan
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.v4i4.251

Abstract

The Covid-19 pandemic in 2020 witnessed a significant increase in cases worldwide, claiming numerous lives. Despite having a substantial number of healthcare workers in several hospitals in DKI Jakarta, there remained a shortage of healthcare personnel during the Covid-19 outbreak. Consequently, there were still many deaths attributed to both diseases. This study aims to analyze self-data visualization from opendatajakarta in the form of a dashboard and utilize the storytelling feature available in Tableau for visualization. The research aims to determine the number of healthcare workers during the major Covid-19 outbreak in DKI Jakarta. To achieve this, the study employs a method called Business Intelligence using the interactive dashboard options provided by Tableau as a decision-making tool, which will be transformed into visualizations and combined into an information dashboard. The research obtained results in the form of a Business Intelligence dashboard displaying the number of healthcare workers in DKI Jakarta.
Penerapan Data Mining Dalam Menentukan Kelayakan Penerima Bantuan Sosial Pemko Dengan Algoritma C4.5 (Kasus Kantor Kelurahan Martoba) Winda Lidysari; Heru Satria Tambunan; Hendry Qurniawan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 3, No 1 (2022): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v3i1.97

Abstract

Social assistance, commonly known as Bansos, is a government program charged by the Regional Revenue and Expenditure Budget. According to the general provisions of article 15 of the Ministerial Regulation Number 32 of 2011 concerning the Provision of Subsidies and Social Assistance in the Regional Revenue and Expenditure Budget, the definition of social assistance applies to the provision of individuals, families, community groups that are unsustainable and selective in nature to prevent possible social risks. The Pematangsiantar City Government provides various kinds of assistance programs, one of which is the PEMKO Social Assistance which is distributed by the Martoba Village Office. In the selection process to determine the recipients of PEMKO Social Assistance at the Martoba Village Office, they still have not fully used information technology to support employee performance. So there are obstacles and it takes a long time. Therefore, we need a system that can help employees more easily determine beneficiaries. Application of Data Mining is a series of processes to find added value semi-manually in the form of unknown knowledge from a data set. In this study, it has parameters, namely, the number of dependents, work, income and home status. By applying the Data Mining Algorithm C4.5, it is hoped that it will make it easier and faster for employees to determine the recipients of PEMKO Social Assistance at the Martoba Village Office
Analisa Dan Perancangan Sistem Informasi Produksi (SiPro) PT. UPAP Hersatoto Listiyono; Anisa Istiqomah; P Purwatiningtyas; Zuly Budiarso
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.v5i1.294

Abstract

PT UPAP is a company engaged in printing services, more precisely screen printing or screen printing, printing services are often needed by textile garment. Until now, PT UPAP has had approximately 70 garments spread across the provinces of Central Java, West Java, Jabodetabek and DIY. The existing system at PT UPAP is still done manually, starting from customer data collection, production, approval, product quality control, production stock data collection, recap data collection of production quality control reports , production stock reports to storage of other data, so that it is possible that during the process there are errors in recording the inaccurate reports made and delay in searching for the necessary data. The design of this information system is the best solution to solve the problems that exist in this company, in order to achieve an effective and efficient activity in supporting activities in this company.
Analisis Persebaran UMKM Bidang Jasa Menggunakan Metode AHC Complete Linkage Lisna Zahrotun; Seftian Hadi Nugroho; Utaminingsih Linarti; Anna Hendri Soleliza Jones
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.v4i2.160

Abstract

Dinas Perindustrian Koperasi Usaha Kecil dan Menengah merupakan salah satu yang bertanggung jawab terhadap pertumbuhan dan kestabilan Usaha Mikro, Kecil dan Menegah (UMKM) yang berada di kota X. Banyaknya UMKM bidang jasa mengakibatkan perlunya penanganan khusus dalam menjaga pertumbuhan dan kestabilan dari UMKM tersebut. Oleh karena itu agar pihak Dinas dapat memberikan strategi dalam menjaga pertumbuhan dan kestabilan UMKM bidang jasa maka diperlukan analisis dan identifikasi persebaran UMKM tersebut.  Salah satu teknik yang dapat digunakan dalam melakukan analisis persebaran UMKM adalah pengelompokkan. Dimana dari hasil analisis pengelompokkan UMKM bidang jasa ini dapat dijadikan sebagai referensi dalam pertumbuhan dan menjaga kestabilan UMKM bidang Jasa. Tahapan dalam penelitian ini adalah Load Data, Data Cleaning dan Data Selection, Data Transformation, Proses Pengelompokan Dengan Agglomerative Hierarchical Clustering (AHC) complete linkage, pengujian menggunakan Silhouette Coefficient, dan Representasi Pengetahuan. Hasil dari penelitian ini menunjukkan bahwa metode AHC complete linkage dapat dilakukan pada UMKM bidang jasa dengan hasil pengujian terbaik yaitu 0,729 dengan jumlah kelompok 2. Dari 2 kelompok yang dihasilkan, kelompok 1 merupakan kelompok UMKM bidang jasa yang perlu mendapatkan perhatian khusus dari Dinas Perindustrian dan Koperasi karena usia berdiri sudah lama namun omsetnya masih dibawah 10 juta.
Perangkat Lunak Mata Pelajaran IPS Kelas XI Berbasis Mobile Di SMA LTI IGM Palembang Dengan Metode User centered design Fakhri Lambardo; Sutra Romadon
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.v5i1.348

Abstract

Education, especially vocational, currently needs to make various changes in the learning process, one of which is by applying different learning concepts  Where in this learning students become active and dynamic parties in finding and managing sources of information related to existing learning material, getting conclusions on the material learned, and being able to apply independently what has been learned. The development of sophisticated technology today many people who have mobile phones or smartphones that are used to communicate, even have more than one. This opportunity is what we can use to learn from building an application using mobile phone programming. There are so many mobile platforms that exist today, one of which is booming is Android mobile.  Android is a Linux-based operating system whose application programming language we can create using Java.
Klasifikasi Jenis Buah Kelengkeng Dengan Metode K-Nearest Neighbor (KNN) Berdasarkan Citra Warna Buah Muhammad Akbar Anugrah Illahi; Widiyanto Tri Handoko
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.v4i3.205

Abstract

In the study titled "Classification of Longan Fruit Types Using KNN Method Based on Fruit Color Images" with the use of the TensorFlow Framework, a series of system testing was conducted using various variations of longan fruit images, totaling 360 samples. The aim of this research was to classify longan fruit types based on the extraction of color features from fruit images. The test results showed the highest accuracy rate reached 98.7% and an average accuracy of 89.6% on the train and test data with an 80%:20% ratio. The developed application successfully distinguished five categories of longan fruit, namely diamond river longan, itoh longan, mata lada longan, red longan, and pingpong longan. This study used a multi-class dataset as the data source. By using the KNN method with a parameter k=5, the system was able to classify longan fruit images with 78% accuracy in the 80%:20% train-validation data split scenario. These findings provide a positive perspective on the potential application of the KNN method in classifying longan fruit types based on the extraction of color features from fruit images. This research makes a significant contribution to the development of automatic recognition and classification systems for longan fruit using image processing techniques
Analisis Kepuasan Konsumen Terhadap Pelayanan Bengkel Menggunakan Metode Algoritma C4.5 Ridho Hayati Alawiah; S Saifullah; Irfan Sudahri Damanik
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.v2i1.55

Abstract

Consumer satisfaction is one thing that is very important is assessing the level of service provided by the workshop to its consumers. The purpose of this study was to determine the quality of serviceto consumer satisfaction Zul Keluarga jaya workshop Pematangsiantar in terms of reliability, Responsiveness, Assurance, Emphaty, Tangibles to consumers Zul Keluarga Jaya workshop Pematangsiantar. In the Zul keluarga Jaya workshop Pematangsiantar the five aspects have not been measured with certainty, so the Zul Keluarga Jaya workshop Pematangsiantar found it difficult to determine which aspects should be improved. By using the C4.5 algorithm, the authors try to measure these five aspects so that a decision tree is formed. After doing a manual calculation, then the proof is done using Rapidminer software. Testing conducted with RapidMiner software using the apply model % performance. From the results of calculation using the C4.5 algorithm produced twelve (12) rule rules of the target to be achieved namely six (6) satisfied decisions and six (6) dissatisfied decisions, and the results of lesting with RapidMiner software resulted in an inspiration rate of 94,00%.
Data Communications and Computer Networks: Research and Impact Sinek Mehuli Br Perangin-angin
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.v5i2.380

Abstract

Science and technology have brought society to an advanced level. The use of human labor, which is becoming increasingly scarce, often results in people losing their jobs because their tasks have been replaced by equipment or machines. As a means of providing information and communication, computers can be used as a means of the Internet. Through the Internet, people can search for various information and communicate. Obtaining information for personal life, such as information about health, hobbies, recreation, and spirituality, is the role that this application of information technology can play. In addition to the benefits, it turns out that information and communication technology devices also have negative effects on their users. As a result of inappropriate or irresponsible use by users, these negative effects occur. Some of these negative effects are 1). Kids spend more time watching TV than doing other things (such as studying and playing sports), 2). Children lose the ability to mingle with society and tend to be comfortable with online life, 3) Copyright infringement, 4). Cybercrime, 5). Spread of computer viruses, and 6). Pornography, gambling, fraud, violence. The ways to overcome these negative effects are: 1). Build relationships with people you already know, 2). Find a positive community that often meets in the real world, 3). The need for law enforcement, which involves the establishment of Internet police, 4). Avoid the use of cell phones with sophisticated features by minors and supervise the use of cell phones, 5). Reading more books that are educational and faith-based as well as computer applications that are educational in nature, and 6). The need for time management in front of the computer or television.
Algoritma Support Vector Machine Untuk Analisis Sentimen Masyarakat Indonesia Terhadap Pandemi Virus Corona Di Media Sosial Mhd. Furqan; Mhd. Ikhsan; Rafizah Aini
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.v4i4.241

Abstract

The corona virus pandemic refers to the spread of coronavirus disease 2019 or what is known as coronavirus disease 2019 in various parts of the world. This outbreak is a change from a new type of coronavirus called SARS-CoV-2. The issue of this pandemic has become a hot topic of discussion, including on social media. The most frequently used platform among the public is Twitter. On social media, the corona virus pandemic has always been a topic of conversation that is often discussed, causing controversy. Controversy occurs because every day the opinions on social media Twitter regarding the corona virus pandemic are always increasing so that, when people read news on social media about the pandemic, it raises concerns because people's opinions are different. From this problem the author will create a system that analyzes opinions from Twitter social media to get opinion sentiment about what is happening in the community regarding the problem of the corona virus pandemic. This study uses the SVM method which is fast and effective for text classification. The results of this study will classify positive, negative and neutral sentences. The accuracy obtained from the model with the SVM algorithm is 98%. Testing is done by calculating precision, recall, F-measure..
Penerapan Algoritma Holt-Winters Exponential Smoothing Untuk Estimasi Dan Naïve Bayes Untuk Klasifikasi Produksi Kelapa Sawit Hanny Handayani Sucinta; Tedy Setiadi
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.v4i4.265

Abstract

This research optimizes oil palm production data in Kuantan Singingi Regency using Holt-Winters Exponential Smoothing and Naïve Bayes methods. With parameters alpha = 0, beta = 0.1, and gamma = 0.2, the estimation model successfully increases production in the upcoming months. Evaluation using MAPE shows estimation accuracy below 18%. The Naïve Bayes classification model achieves an accuracy of around 85%, indicating a good balance between accuracy and precision. This study provides a significant contribution to oil palm production planning and assists farmers and cooperatives in more efficient management.

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