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Building of Informatics, Technology and Science
Published by Forum Kerjasama Pendidikan TInggi
ISSN : 26848910     EISSN : 26853310     DOI : -
Core Subject : Science,
Computer Science & IT
Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. This journal is managed by Forum Kerjasama Pendidikan Tinggi (FKPT) published 2 times a year in Juni and Desember. The existence of this journal is expected to develop research and make a real contribution in improving research resources in the field of information technology and computers.
Arjuna Subject : -
Articles 889 Documents
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Kombinasi Penerapan Metode WASPAS dan Rank Order Centroid (ROC) dalam Keputusan Pemilihan Teknologi Kamera Ponsel Terbaik Anwar, Badrul; Simatupang, Wakhinuddin; Muskhir, Mukhlidi; Irfan, Dedy; Nasyuha, Asyahri Hadi
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2655

Abstract

Smartphone camera technology is currently growing rapidly so that it has specifications that support it so that the results obtained are almost on par with the quality of digital cameras. Supported cellphone cameras can be used in learning photography, not necessarily with a digital camera. The increasing number of cellphone choices makes users who want to study photography confused in choosing a cellphone that has the best cellphone camera technology. So that a Decision Support System was applied in this study as a system for obtaining the best cellphone camera technology decisions. In making the right decision on selecting the best cellphone camera technology, it must meet the criteria for Number of Camera Features, Number of Main Cameras, Number of Front Cameras, Main Camera Resolution, Front camera Resolution, Optical Zoom and Quality of Video Recording. Therefore a Decision Support System is needed to solve the problem by applying the ROC (Rank Order Centroid) and WASPAS (Weighted Aggregated Sum Product Assessment) methods which can produce weight and preference values from the first ranking alternative. So that the selection of the best mobile camera technology for the best mobile camera technology can be found in table 7, namely the Samsung Galaxy S22 Ultra which is in the A5 alternative with the highest score of 3.8354 as the first rank
Implementasi Metode MAUT dalam Sistem Pendukung Keputusan Seleksi Penerimaan Stock Keeper Restoran dengan Pembobotan Rank Order Centroid Abdullah, Mohammad Aldinugroho; Aldisa, Rima Tamara
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2656

Abstract

In a restaurant that is running well, of course, it requires the best quality human resources. One of the human resources that is needed by a restaurant is a stock keeper. Stock keeper restoration is needed to ensure that supplies are maintained properly. The selection process for receiving stock keepers is still carried out conventionally so that the selection process is sometimes not appropriate in accepting the best stock keepers. In determining the selection of restaurant stock keepers, there are several criteria, namely work experience, education, ability to operate Microsoft, attitude, communication, psychological test, interview, personal vehicle and age. Because of these problems, a system is needed that can assist in obtaining reliable and targeted recommendations. The application of a decision support system in this study is used by implementing the Multi-Attribute Utility Theory (MAUT) and ROC methods where these methods are very helpful in producing the best weight and preference values ​​from alternative data and criteria so as to get the final result, namely the best restaurant stock keeper recommendations the Alternative A5 with a score of 1,005 on behalf of Lollymoci
Sistem Pendukung Keputusan Penentuan Pengangkatan Karyawan Kontrak Menjadi Karyawan Tetap Menerapkan Metode Preference Selection Index (PSI) Bani, Alexius Ulan; Prambodo, Yoga Listi; Azlan, Azlan
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2657

Abstract

Employees are the main and most important element in the running of a company. The quality of employees is a determinant of how an employee's foundation is. In order to improve the quality of each employee, it is necessary to separate employees, between contract employees and permanent employees. the large number of employees may make the management confused in determining who should be made permanent employees. Therefore, a system is needed that can assist the government in selecting permanent employees. The system is a decision support system. A decision support system is a system where the process is carried out using a unified system with a method or more than 1 (one) method that is carried out using a computer base. SPK is used to assist certain elements in choosing or making a decision. Many methods can be used in DSS, in this study the PSI method was used. PSI is a method used in solving problems where the problem has many alternative choices of attributes. With this study, the results were that the best alternative was Dicky as an alternative B15 with a value of 0.8977, which in the end was suggested to be a permanent employee
Sistem Deteksi Kecanduan Pornografi Berbasis Chatbot Menggunakan Pornography Addiction Screening Tool (PAST) Muhammad, Raditya; Ardimansyah, Mochamad Iqbal
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2660

Abstract

The use of the internet not only brings benefits but also harms the ease of access to pornographic content. Pornographic content is not solely available on adult websites but is also spread on social media accessed by many children to adults. As a result, problems arise due to pornography addiction, such as rape, sexual orientation deviation, and sexual crimes against children. Uniquely, pornography addiction is hard to detect objectively compared to drug or alcohol addiction. This study aims to develop a pornography addiction detection system in the form of a chatbot-based mobile application. The choice of chatbot is because this system supports interactive automatic communication patterns and guarantees the privacy of its users. This study adopts a psychological measurement technique Pornography Addiction Screening Tool (PAST), as a benchmark in developing application logic. Meanwhile, chatbot application development uses the waterfall method which has been tested by best practices as a software development method. Tests performed are in a developer environment. The system validation mechanism uses the Black-box testing method to observe the execution of the application when it runs the functionality that was designed beforehand. In addition, the usability measurement level application is adopted from the System Usability Scale (SUS) method. From the test results, it was found that the pornography addiction detection system operates normally and can be used as a supporting medium for handling pornography addiction by psychiatrists.
Deteksi Kesehatan Janin Menggunakan Decision Tree dan Feature Forward Selection Sulihati, Indah; Syukur, Abdul; Marjuni, Aris
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2672

Abstract

Fetal health is very important, it is important for prospective mothers to know from an early age, until now a mother’s sense of ignorance abpout fetal health is very lacking and can result in fetal death. This is due to the lack of curiosity possessed by prospective moyhers and the lack of socialization and infrastructure from related parties about fetal health. Basically, the growth and development of a prospective fetus is very important so that it can be born healthy and without any obstacles at all.The pupose of this study was to detect fetal health using a decision tree classification algorithm with forward feature selection. This experiment was conducted using a public dataset of 2.126 patient data. The results showes that classification using a decision tree algorithm using a decision tree algorithm without feature selection resulted in an accuracy of 89.84%. While the use of the forward selection feature in this decision tree algorithm produces an accuracy of 91.06%.This shows that the use of the forward selection feature can increase accuracy by 1.22%.
Penerapan Pemilihan Model Arsitektur Terbaik pada Neural Network pada Prediksi Jumlah Siswa SD di Kecamatan Siantar Barat Ramadhani, Cerah Fitri; Siregar, Muhammad Noor Hasan; Rahadjeng, Indra Riyana; Windarto, Agus Perdana
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2676

Abstract

The use of the artificial neural network (Backpropagation) method can be used in determining the best architectural model for predicting the number of elementary school students in the Siantar Barat District. The dataset used is a dataset on the number of Elementary School (SD) students in West Siantar District, Pematang Siantar City in 2017-2021 obtained from the Website of the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia (https://dapo.kemdikbud.go.id /pd/3/076303). The dataset is then divided into 2 parts, namely the training and testing dataset. In the training datasets, attribute X1 is a dataset for 2017, X2 is the dataset for 2018, X3 is a dataset for 2019, and attribute Y (target) is the dataset for 2020. For the test datasets, attribute X1 is the dataset for 2018, attribute X2 is a dataset for 2019, attribute X3 is a dataset for 2020 and attribute Y (target) is a dataset for 2021. The results obtained from the analysis of the Backpropagation and virtualization methods using the MatLab application can be generated with a valid dataset and produce an accuracy rate of 87.5% in architectural models 3-9-1. So that the Backpropagation method can be used as a prediction method that makes it very easy to find predictions.
Application of Deep Learning LSTM in Online Power Prediction on Three-Phase Power Transformer Pratama, Destra Andika; Nabila, Sinta
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2690

Abstract

Electrical energy plays an important role in daily life, especially companies. The 3 Phase Power Transformer is one of the important electrical components that is very influential in distributing electrical energy to companies as is the case in PT. Semen Baturaja (Persero). 3-phase power transformers require attention because they are one of the components that are prone to interference, this interference can hinder the effectiveness of using electrical energy as a company support for employees to work. As one of the disturbances for 3-phase power transformers is overload or excessive power usage, overload can raise the temperature at the winding and reduce its service life. Artificial intelligence can be one of the keys to predict the use of power transformers in the future, especially deep learning by utilizing the LSTM algorithm. Optimal power prediction requires a lot of maximum input variables so that in this study, it not only adds an offline learning mode but adds a learning mode that can directly access the company's Power Quality Monitoring (PQM) website online with an average accuracy value of 86.62%.
Analisis Kepuasan Pengguna Sistem Informasi E-Campus Menggunakan Metode E-Servqual Dan Model Kano Nurhadi, Muhammad; Hamzah, Muhammad Luthfi; Ahsyar, Tengku Khairil; Jazman, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2691

Abstract

This study aims to identify the dimensions and service attributes that need to be improved, as well as improvements related to the quality of services provided by the e-campus system to students at UIN Mahmud Yunus Batusangkar. It also aims to identify the quality of services provided by the e-campus system to students. in order to provide advice or consideration to improve the quality of the e-campus system to the campus or developer, which in turn will produce a solution to improve the quality of the e-campus system for user satisfaction. The procedures used include 5 stages are planning, gathering information processing information analysis and the latest reporting review. The research results created calculations using e-servqual procedures of 0.92 ≤ 1, showing that the quality of the services provided could be said to be unable to fulfill students' expectations. If the level of performance is met, it will bring about a very large increase in user satisfaction. But if not fulfilled, it will reduce the level of satisfaction. Whereas the canoe model gets eight attributes included in the must-be category, eight one-dimensional attributes and six attractive attributes. The ranking level obtained is a source of attributes that are prioritized to be improved. Every attribute that has a very large negative value will also be less effective in achieving user satisfaction
Sistem Pendukung Keputusan Pemilihan Instruktur Bimbingan Belajar Menggunakan Metode PSI (Preference Selection Index) Fauziyah, Fauziyah; Nugroho, Fifto; Buulolo, Efori
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2695

Abstract

Service activities aim for the long term in creating HR (Human Resources) who have knowledge and creativity in the field of computers, especially in graphic design and multimedia applications. This training aims to train students in using tools in graphic design applications, for example. Corel Draw, so students are expected to know how to plan and develop students' creative abilities in designing. This activity is carried out using the social method of graphic design applications using the Corel Draw application, and an instructor who is an expert in the field of graphic design. to guide the operation of the application, thereby helping trainees in the practice of making designs. Decision support system, is a system that is used to facilitate decision making in selecting a graphic design training instructor, where the decision making process is basically choosing alternative decisions in determining the eligibility of a person to become a design training instructor, the assessment can be seen from several assessment criteria, namely experience, consistent, creative and communicative. In facilitating the selection process, a decision support system is used using the PSI (Preference Selection Index) method to produce the best weights and preferences. So that the final result obtained as a tutoring instructor is alternative A11 on behalf of Sriwulan with the first rank with the highest score of 0.9196
Analisa Penerapan Metode MOOSRA dan MOORA dalam Keputusan Pemilihan Lokasi Usaha Sudarsono, Bernadus Gunawan; Zulkarnain, Iskandar; Buulolo, Efori; Utomo, Dito Putro
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2696

Abstract

In the world of work, competition certainly exists. Especially in the selection of the location of the business being run. The better the location of the place of business, of course, the more competition. In this study, we will discuss the selection of a strategic and appropriate business location. The location of the business greatly affects the development of the business being run, many businesses do not develop (loss) so they have to stop their business because the location of the business is far from residential areas, the location is narrow and so on. To avoid this, we need a system that can solve the problem which is called a decision support system. Decision support system is a structured system in making effective business location selection decisions using methods such as WASPAS, SPI, TOPSIS, WP, SAW, MOORA, MOOSRA, EDAS and many others. The selection of business locations used the MOOSRA and MOORA methods. Both methods are very simple and easy to understand with the assessment based on the criteria used, namely Number of Competitors, Crowd Center, Location Size, Place Rent Price and Location Cleanliness. The results obtained after applying the two methods in the selection of business locations, namely the highest alternative or the first rank is Alternative A1 with a reference value of 0.564

Page 33 of 89 | Total Record : 889

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