cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Nurchim
Contact Email
nurchim@udb.ac.id
Phone
+62271-719552
Journal Mail Official
senatib@udb.ac.id
Editorial Address
Jl. Bhayangkara No 55 Serengan Surakarta 57154
Location
Kota surakarta,
Jawa tengah
INDONESIA
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis
Published by Universitas Duta Bangsa Surakarta
ISSN : -     EISSN : -     DOI : https://doi.org/10.47701/senatib.v2i1
Core Subject : Economy, Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics
Prosiding SENATIB adalah kegiatan seminar berskala nasional yang diselenggarakan oleh Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta dalam rangka diseminasi hasil penelitian tentang teknologi informasi dan bisnis. Diharapkan pada tahun 2022 melalui penerbitan prosiding ini dapat terwujud berbagai alternatif solusi dalam menghadapi era industri 4.0 dan society 5.0 di Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 490 Documents
 13   14   15   16   17 
Analisis Metode K-Nearest Neighbor Menggunakan Rapid Miner Untuk Memprediksi Hujan Kota Surakarta Alvian Ahmada Akhbar; Dwi Hartanti
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/senatib.v3i1.2996

Abstract

This study aims to implement the K-Nearest Neighbor (KNN) algorithm using the Rapid Miner application to predict rain in Surakarta City. Rainfall has an erratic pattern making it difficult to predict manually. Rainfall cannot be determined with certainty but this can be estimated. Thus, the existence of Data Mining can enable machines to recognize and study complex data patterns. Therefore program learning can learn patterns of rainfall data to make some predictions. This study uses three variables as criteria, namely temperature, wind speed, and humidity. The test results using the K-Nearest Neigbor (KNN) algorithm and the Rapid Miner application with a value of K = 3, found an accuracy of 83.87%. From 31 data taken in July 2023. The results of the analysis prove that the KNN method using the Rapid Miner application can be used to predict rain in Surakarta City.
Prediksi Harga Rumah di Kabupaten Karanganyar Menggunakan Metode Regresi Linear Ashary Vermaysha; Nurmalitasari Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to apply linear regression method in predicting house prices in Karanganyar Regency, using land area, building area, number of bathrooms, number of bedrooms, and electricity capacity as independent variables. A dataset consisting of house prices and the independent data was used in the analysis. The research results show that the predicted house prices have a relatively low level of accuracy, with an error of 651614542,27. To improve the prediction accuracy, three steps are recommended. First, adding data variations from several real estate websites to expand the sample and covered house characteristics. Second, expanding the dataset by adding supporting variables such as dates, which provide information about market trends and fluctuations. Finally, exploring alternative prediction algorithms that are more supportive than linear regression. The conclusion of this research is that although linear regression can be used to predict house prices in Karanganyar Regency, the accuracy level still needs to be improved. Therefore, the proposed recommendations need to be implemented to improve the prediction model. Thus, it is expected that house price predictions in Karanganyar Regency will become more accurate and useful for use in the property market.
Penerapan Algoritma Fuzzy C-Means untuk Analisis Tingkat Pendidikan Sekolah Dasar di Karanganyar Daffa Rizki Putra Noordi; Irfan Agus Prastowo; Nadia Amalia Putri; Zariel Ardian Ekovih; Dwi Hartanti
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The use of the Fuzzy C-Means (FCM) algorithm is an interesting topic in the analysis of elementary school education. Karanganyar is an area that has many elementary schools and we need a method that can classify data with high accuracy to understand elementary school data effectively. Therefore, this study aims to apply the FCM algorithm in data mining to analyze elementary schools in Karanganyar. The research began by collecting data on elementary schools in Karanganyar which included attributes such as the number of study groups and students. The FCM method is then used to process the data. The data clustering technique is enabled by this algorithm. Experimental findings indicate that the application of FCM algorithm in data mining to analyze an elementary school in Karanganyar produces information grouping. In rapidminer's calculations, 6 clusters were obtained, namely cluster 0 consisting of 45 elementary schools with the lowest educational level category, cluster 1 consisting of 3 elementary schools with the highest educational level category, cluster 2 consisting of 73 elementary schools with the lowest educational level category, cluster 3 consisting of 14 elementary schools with the higher education level category, cluster 4 consisting of 39 elementary schools with various levels of education categories, cluster 5 consisting of 27 elementary schools with the medium education level category. The DBI value acquired by the FCM method is -0.471, and since this number is near to 0, it can be argued that the cluster that the algorithm generated is excellent. This can help the government and the educational system. in formulating sensible development plans and policies. Karanganyar's educational system.
Penerapan Metode Knowledge-Based Recommendation Dalam Menganalisis Makanan Legendaris Solo Diffani Salzadila; Tasya Mutiara Diva; Ibrahim Fahmi
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this study is to apply the Knowledge based recommendation method for typical Solo food. This method is used to provide users with accurate and relevant recommendations about famous Solo specialties. This study uses a knowledge-based approach to collect and organize information about the legendary dish, including its properties, ingredients, method of preparation, and where it is served. the research phase involves identifying legendary dishes through literature studies and interviews with culinary experts, gathering knowledge about these dishes, organizing the knowledge into recommender systems, and developing appropriate algorithms or methods for knowledge-based recommendations. The recommendation system developed is evaluated and verified using test data and user feedback. The results of this study aim to provide legendary nutritional recommendations that are relevant and in accordance with user preferences. Using the Knowledge-based recommendation methodology, users can better discover and explore Solo culinary delights. The benefit of Knowledge based recommendation is the ability to set user priority levels based on user needs by calculating the similarity score between customer needs and food attributes. Knowledge based recommendation modeling for food choice recommendation systems can provide five search attributes for food product choices, namely type of food, price, ingredients, full menu, and instructions. Based on the results of the Knowledge-based recommendation modeling method with 10 data samples, food recommendations can be given according to the criteria required by customers by calculating the similarity value between customer needs and the attributes of each food. Foods with the highest similarity values are displayed according to food recommendations, namely. H. The highest similarity score is 0.77 for Soto Gading food. The results of this Knowledge-based recommendation model can be used as a reference in developing a legendary food selection recommendation system in Solo
Analisis Kemiskinan Menggunakan Metode Algoritma Clustering K-Means Dwiki Rasya Rahadian; Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Poverty has a broad and serious impact on the lives of individuals and society. When people live in poverty, they may face difficulties meeting basic needs, such as adequate food, adequate housing, and proper education. These limitations can negatively impact physical and mental health, education, employment opportunities, and overall quality of life. The purpose of this study is to find out the grouping of districts/cities that have similar characteristics based on the 2019 poverty indicators. This research uses data obtained from the BPS (Central Bureau of Statistics). The method used is the k-means clustering method which is a clustering partition method for grouping objects into k clusters. Based on the research results, the characteristics of each cluster were grouped based on the poverty indicator values in several districts/cities in 2019 as many as 2 clusters. Formed from 20 districts/cities in cluster 1 and 29 districts/cities in cluster 2. Cluster 1 has the characteristics of Low Work Challenges, with Low Per Capita Expenditure Rates and Low Unemployment Rates while Cluster 2 has the characteristics of High Job Challenges, with Per Capita Expenditure Levels High and High Non Working Rate.
Sistem Informasi Pengaduan dan Pelayanan Berbasis Web pada Dinas Pekerjaan Umum dan Tata Kota di Kota Surakarta Labib Dewa Saepudin; Moh. Muhtarom; Faulida Ely Nastiti
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The cleanliness and beauty of the city is one of the attractions to visit a city. Maintenance of cleanliness, beauty and suitability of urban planning is the responsibility of each level II region, namely the city / or regency itself. In Surakarta City, the responsibility for cleanliness, beauty and urban planning is the responsibility of the Public Works and Spatial Planning Office, formerly known as DPU. This study aims to build an information system for the management and data collection of administrative information for facilities and infrastructure at SMP Negeri 15 Surakarta. This research uses UML as a system development method The results of the study provide results that the complaint and service information system is made to facilitate the community in providing complaints and requests for services, especially people in Surakarta City, system development is carried out using the UML method, the system is built by analyzing the shortcomings of the ongoing system, database design, system flow design and implementation system, with the application of the complaint and service system, public satisfaction with the services provided by the Surakarta City Government will increase so that public trust will also increase, and the system that has been formed is tested with the blackbox method. From the results of blackbox testing, from the login page, to the reporting page provides the expected results, so this system can be used.
Analisis Faktor-Faktor yang Mempengaruhi Produksi Padi di Sumatera Menggunakan Metode Regresi Linier Mohammad Yusuf Nugroho; Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In research data must go through a processing process so that it can be used in the research. The data used must be valid to be able to produce an appropriate solution. This study aims to analyze the factors that influence rice production in paddy fields. The island of Sumatra has more than 50 percent of agricultural land in each province with the most dominant main food commodity being rice, while the remainder is corn, peanuts and sweet potatoes. Agricultural products in Sumatra are very vulnerable to climate change which can affect cropping patterns, planting time, production and yield quality. Climate change can have a negative impact on the production of these basic commodities. Moreover, an increase in the earth's temperature due to the impact of global warming which will affect the pattern of precipitation, evaporation, water runoff, soil moisture, and climate variations which are very fluctuating as a whole can threaten the success of agricultural production. Predictions of agricultural yields for food commodities are heavily influenced by climate change. The method used for analysis is Linear Regression and also uses the python library.
Analisis Faktor Utama Penentu Harga Rumah di Surakarta Menggunakan Principal Component Analysis Muhammad Rais Ramadhani; Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Residence is often referred to as one of the primary needs. Therefore, it is important to formulate a well-planned series of actions to ensure that every family has a dwelling of their own. In this planning process, an analysis of the factors determining house prices is necessary to serve as a basis for finding suitabel housing. The objective of this research is to conduct a Principal Component Analysis (PCA) on the main factors determining house prices using the dataset from Surakarta. The identified factors that contribute to house prices include the number of bedrooms, the number of bathrooms, the size of the house, the distance from the house to the city center, and the distance from the house to the nearest hospital. The analysis is performed using the PCA library in Python, resulting in two main factors with a variance above 90%. The first component represents accessibility factors, specifically the distance from the house to the city center and the distance from the house to the nearest hospital. On the other hand, the second component represents spatial and accommodation factors, including the number of bedrooms, the number of bathrooms, and the size of the house.
Penerapan K-means Clustering pada Penjualan dan Pajak BBM di DKI Jakarta Pramudya Aziz Wisnuadi; Bagus Irfanzah Arda Nugraha; Hiskia Kus Setiawan; Dwi Hartanti
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Fuel oil (BBM) is part of the main merchandise originating from refined petroleum and natural gas, either through direct extraction or processing of crude oil. Tax is an obligation that must be paid by an individual or company to the state based on coercion by law. In this study, the method used is K-Means Clustering data mining, which functions to group data that has been collected into several parts, the K-Means Clustering mechanism is implemented with the RapidMiner tool. Sources of data recorded on the Jakarta Open Data website, especially data on fuel sales and taxation for DKI Jakarta are used in this study. The criterion used is the determination of the center of gravity randomly. The iteration process is carried out 7 times, so that the first cluster with the highest number of elements is formed, including 195 items and the second with 9 items.
Sistem Informasi Pengelolaan Aset Berbasis Web Pada UPT Balai Latihan Kerja Karanganyar Toni Iksanudin; Hanifah Permatasari; Faulinda Ely Nastiti
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Asset management is one of the important factors in an institution. Therefore, every asset owned must be managed optimally, effectively and efficiently in order to provide decent profits for the institution. UPT Karanganyar Job Training Center is one of the government job training institutions under the auspices of the Department of Trade, Industry and Manpower of Karanganyar Regency. UPT Karanganyar Job Training Center has many assets to support its operations such as computers, air conditioners, vehicles, laboratory equipment and others. Currently, the asset management system at UPT Balai Training Kerja Karanganyar still uses Microsoft Excel. This causes the process of asset maintenance, asset recording and asset reporting at the UPT Karanganyar Work Training Center to be less than optimal, taking longer to track asset data. The purpose of this research is to solve these problems and an information system is needed. This research applies the Waterfall method. The creation of this asset management information system is done using PHP programming language with Codeigniter Framework and MYSQL as the database. Based on tests that have been carried out using black box testing, the system designed can help the problems faced at the UPT Karanganyar Job Training Center.

Page 15 of 49 | Total Record : 490

 13   14   15   16   17 

Filter by Year

2022 2025


Reset
Filter By Issues
All Issue Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2025 Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023 Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2022 Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB)