Building of Informatics, Technology and Science
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.
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889 Documents
<![CDATA[Prediksi Persediaan Bahan Baku Makanan Menerapkan Algoritma Apriori Data Mining ]]>
<![CDATA[Salmon, Salmon]]>;
<![CDATA[Azahari, Azahari]]>;
<![CDATA[Yusnita, Amelia]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2563
<![CDATA[The company's operational activities are inseparable from the supply of raw materials that must be met every day to meet consumer demand. The restaurant uses raw materials, namely vegetables, raw meat which includes beef and chicken, yellow noodles and soun noodles, and the main seasoning. Sales of food at this restaurant quite a lot in a day. This will produce sales data that will continue to grow every day, but this data is useless if it is not processed again to get the knowledge contained in the data. The Apriori algorithm is a method for finding patterns of relationships between one or more items from a dataset. Thus the pile of data that has been collected can produce a sales pattern, from which the customer's buying interest in food can be identified. From the results of research using a data sample of 18 items with a minimum of 20% Support and 50% Confidence, it produces 5 interesting rules with the highest Support reaching 33.33% and the highest Confidence reaching 100%.]]>
<![CDATA[Penerapan Data Mining Untuk Prediksi Perkiraan Hujan dengan Menggunakan Algoritma K-Nearest Neighbor ]]>
<![CDATA[Nursobah, Nursobah]]>;
<![CDATA[Lailiyah, Siti]]>;
<![CDATA[Harpad, Bartolomius]]>;
<![CDATA[Fahmi, Muhammad]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2564
<![CDATA[Rain is a condition where water droplets fall from clouds to the earth. In life, the presence of rain is highly anticipated, rain can help people who have a profession as farmers. Rain that occurs on a large scale will really provide obstacles for the community, in addition to hampering activities or activities especially those carried out on outdoor rain can also cause disaster for the community in the form of flooding. Estimating rain for the community is very important, knowing whether it will rain or not can make it easier for the community to anticipate the possibilities that may occur due to rain. However, in the process of delivering forecasts, there is often an uneven distribution of information and delays in conveying information to the public regarding whether or not rain will occur. The community should be able to independently predict whether or not rain will occur. Data processing should be done properly and correctly. Data mining is a way that can be done to assist in data processing. In this study, the settlement process will be carried out using the K-Nearest Neighbor (K-NN) algorithm. The results obtained show that the data testing decision is NO. In other words, data mining and the K-Nearest Neighbor algorithm can help the problem solving process]]>
<![CDATA[Klasifikasi American Sign Language Menggunakan Convolutional Neural Network ]]>
<![CDATA[Israldi, Tino]]>;
<![CDATA[Haerani, Elin]]>;
<![CDATA[Sanjaya, Suwanto]]>;
<![CDATA[Syafria, Fadhilah]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2570
<![CDATA[Communicating is a necessity for all groups or individual because each individual should communicate with their surroundings. Communicating can also make us get information so that it can be used as a reference to be able to adapt. Verbal language used by speaking out loud is a way of communicating with individuals, but not all individuals can communicate with it, especially there are some individuals who have hearing limitations. Because of these limitations, another program that can be used is through sign language. Language requirements are languages that are usually used by people with disabilities in terms of hearing or speaking and sign language also has a fairly well-known sign language standard, namely the American Sign Language (ASL) standard. Unlike languages in the world, sign language is also often of little interest to most people because people's interest in sign language is still lacking so that most people are unable to understand their language. Sign language has many types, one of which is sign language by using hands to form letters and numbers. In overcoming these problems, the solution is to create a system that can be used to recognize sign language, the system developed is a system that used machine learning technology. This study will propose an ASL classification approach through data preprocessing and a convolutional neural network model. The proposed model can classify ASL hand posture images to be translated into the alphabet. The result of this study is an model with accuracy of 99.8% obtained from the process of merging preprocessing data and the convolutional neural network model.]]>
<![CDATA[Pengaruh Data Preprocessing terhadap Imbalanced Dataset pada Klasifikasi Citra Sampah menggunakan Algoritma Convolutional Neural Network ]]>
<![CDATA[Resa Arif Yudianto, Muhammad]]>;
<![CDATA[Sukmasetya, Pristi]]>;
<![CDATA[Abul Hasani, Rofi]]>;
<![CDATA[Sasongko, Dimas]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2575
<![CDATA[Garbage is one of Indonesia's most significant problems with an increase in waste each year reaching 187.2 million tonnes/year. Various efforts to reduce the amount of waste such as Garbage Banks have been encouraged. However, this program has not run well, because some people have difficulty distinguishing the type of waste. One solution to overcome this problem is that need a system that can classify the type of waste. The deep learning approach with the CNN algorithm is currently widely used to solve classification problems. This method requires a large number of datasets to increase the level of accuracy. Getting a garbage dataset is a particular problem in the training process because the dataset is unbalanced. The dataset used amounted to 2527 data consisting of 6 classes. Several treatments such as undersampling and image augmentation are applied to overcome imbalanced datasets. Other treatments such as the type of input image channel and the use of filters are combined into 24 experimental scenarios to achieve the highest accuracy. The results of the experiment get the best scenario, namely, the dataset is undersampling and then augmented with 5 geometric transformation parameters with the input image being RGB and applying a sharpening filter to get an accuracy value of 0.9919 with 20 epochs.]]>
<![CDATA[Implementasi Algoritma K-Nearest Neighbour dalam Memprediksi Stok Sepeda Motor ]]>
<![CDATA[Desyanti, Desyanti]]>;
<![CDATA[Wulandari, Denok]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2579
<![CDATA[PT. Dasatama Cemerlang Motor is a company engaged in the automotive sector. With the increasingly fierce competition among the automotive industry, companies are required to be able to handle inter-industry competition. Sales system PT. Dasatama Cemerlang Motor uses a cash or credit system. For every motorcycle sale, the admin inputs sales data using Ms.Excel. Even though Ms.Excel has many features and functions that are used to process numbers, it cannot predict annual motorcycle sales for the future as a reference in marketing strategy. Because of that, forecasting is needed which will help the company to find out the trend in the number of motorcycle sales for the coming year. The KNN algorithm is one of the methods used for classification analysis, but in the last few decades the KNN method has also been used for prediction. KNN looks for the shortest distance between the data to be evaluated and its K closest neighbors. The results achieved in this study resulted in the number of motorcycles for each brand that will be sold in 2022 obtained from the addition of 5 motorcycles for each sale of each motorcycle brand. Based on the research results, the prediction accuracy rate using the KNN method is 97%.]]>
<![CDATA[Pengembangan Model Sistem Informasi Geografis Angkot Online Berbasis SCRUM: Ujicoba Kelayakan ]]>
<![CDATA[Rifa’i, Mochamad Fikri]]>;
<![CDATA[Ghazali, Dexsa Muliana]]>;
<![CDATA[Riyan, Ade Bani]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2581
<![CDATA[Angkot drivers can compete with online transportation in getting passengers via smartphones. This application is based on a geographic information system, which is a system that can show the location of a person or place online, using this system to be integrated with public transportation makes it possible to add or pick up passengers more efficiently not only by waiting in one place but can pick up passengers according to the location of the passenger and the transportation route. To overcome the above problems, making applications with a technology theme is one of the right solutions for innovative methods that will be applied to public transportation drivers so they can get passengers efficiently. The purpose of this study is to determine the user's response to the application that has been developed. The research method used is research and development with a 4D development model with “define, design, development, and dissemination stages”. Data collection was carried out by distributing questionnaires to several respondents, while the trial stages carried out included alpha version trials, beta versions trials, Version Release, and Implementation. The results of the study show that the indicators of language, appearance, and accessibility of applications that have been developed are classified as "very feasible". The developed online angkot application is expected to be a solution in dealing with technological developments that can be applied to public transportation]]>
<![CDATA[Sistem Pengukuran Detak Jantung Berbasis Visual Menggunakan Plane Orthogonal to Skin dan Peak ]]>
<![CDATA[Nasrudien, Fahmi]]>;
<![CDATA[Yulian, Dhany Eka]]>;
<![CDATA[Lubabsyah, Ahmad Naufal]]>;
<![CDATA[Firmansyah, Riza Agung]]>;
<![CDATA[Pambudi, Wahyu Setyo]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2585
<![CDATA[Measurement of vital signs is a procedure that is usually done when health workers carry out screening. The vital signs in question include body temperature, heart rate, blood pressure, oxygen saturation and others. The equipment used to measure these vital signs should generally be touched to the subject (by contact). However, due to the COVID-19 pandemic, contact measurements need to be avoided. So it is necessary to make a non-contact measuring system for vital signs. In this study, the only vital signs measured were heart rate. In this study it is proposed to make a non-contact heart rate meter with a plane orthogonal to skin (POS) that uses a peak detection algorithm to determine the heart rate value. In general, the POS method using the fast Fourier transform (FFT) requires longer data which makes the process take longer. So in this study, a peak detection algorithm will be used to calculate the heart rate value that has been extracted using POS which has a faster process. Based on the testing of the POS-FFT method and the POS-peak detection method, it was found that POS-peak detection gave stable results at all data lengths. The smallest mean absolute error generated is with a data length of 128 which is 5.19 bpm]]>
<![CDATA[Pendekatan Algoritma Tree dalam Prediksi Populasi pada Smart Poultry ]]>
<![CDATA[Wahyu Nugroho, Nicolaus Euclides]]>;
<![CDATA[Ramadhan, Nur Ghaniaviyanto]]>;
<![CDATA[Wibowo, Merlinda]]>;
<![CDATA[Pramono, Sigit]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2609
<![CDATA[Intelligent systems for monitoring poultry in kennels are experiencing an increasing trend in several studies. Monitoring poultry is very important in the cage so that you can find out the chickens' condition and environment in the cage. Conditions that can be monitored include the weight of the chickens, whether or not there is enough water in a day, CO2 levels in the cages, air temperature, and humidity in the cages. Several studies have been conducted studies on monitoring poultry cages using IoT-based sensors. However, people have yet to predict the poultry population for tomorrow. So this study aims to predict the number of poultry populations in kennels based on related parameters. The prediction method used in this research is a decision tree and Support Vector Machine (SVM) to see which prediction method is better. The results evaluation techniques used in this study are Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R2. The experimental results show that using the decision tree method, and the results are MSE 61987.202, RMSE 248.972, MAE 85.086, and R2 0.969. Overall the results of the decision tree method are superior to SVM.]]>
<![CDATA[Sistem Pendukung Keputusan Dalam Rekomendasi Kelayakan nasabah Penerima Kredit Menerapkan Metode MOORA dan MOOSRA ]]>
<![CDATA[Kusmanto, Kusmanto]]>;
<![CDATA[Nasution, Mhd Bobbi Kurniawan]]>;
<![CDATA[Suryadi, Sudi]]>;
<![CDATA[Karim, Abdul]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2610
<![CDATA[In selecting credit recipients, it is necessary to have a recipient selection system that can overcome the problem of bad credit that often occurs (loans that are not repaid by the debtor). Based on this problem, a decision support system is needed that helps identify the wrong recipient. The method used in this study is the Moora method and the Moosra method, namely the method for determining priorities. A decision support system is a computer-based system consisting of interacting components: a language system component, a knowledge system component, and a problem-handling system component, and uses data and decision-making models to create semi-structured problems. It solves structured problems and semi-structured problems. and assist in decision making. Structured and unstructured problems, this system helps you get information about your customers, the results are more accurate and on target]]>
<![CDATA[Pengatur Suhu Otomatis Pada Solar Water Heater Berbasis IoT ]]>
<![CDATA[Rosiana, Elfirza]]>;
<![CDATA[Abdurahman, Abdurahman]]>;
<![CDATA[Gunastuti, Dwi Anie]]>;
<![CDATA[Aditya, Sugeng]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i3.2612
<![CDATA[Humans in everyday life really need energy. Energy use is expected to be sustainable, safe and clean. Solar is a renewable energy source that sustains life on earth, it can be utilized through photovoltaic and solar thermal systems. Solar thermal systems that capture solar energy can be used directly for water heating purposes. So that an environmentally friendly water heater can be created. This water heater is a solar water heater. Another problem is that the temperature setting for hot water is still manual, causing waiting time and wasted energy when mixing water is not according to your wishes and needs. The solution requires an automatic temperature regulator is needed on a solar water heater. The DS18B20 temperature sensor is used to read the water temperature, the Wemos D1 R2 microcontroller will consider whether the temperature read is appropriate or not according to the user wishes. If it is not suitable, it will instruct the relay to be active and turn on the water pump to circulate water to the heating collector. Setting the desired temperature can be done remotely using Internet of Things technology. From the results of testing the tool, the solar water heater that has been made is capable of providing hot water temperatures of 50.25 °C, 46°C, 43.12 °C when the tank contains 10 liters, 20 liters and 30 liters of water. The set point setting was successfully done using the blynk platform]]>
