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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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Sistem Pendukung Keputusan Pemilihan Kartu Internet Smartphone Menggunakan Metode MOORA dan WASPAS Sulistya Kusuma Wardhani, Annisa Risqi; Yahya, Sitti Rachmawati; Tanwir, Tanwir; S, Usanto; Ahyuna, A
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3039

Abstract

Currently the internet is the most widely used source of information among the public to find the information needed. The use of the internet can meet the needs of information sources that are fast, easy, precise, accurate and inexpensive. Through the internet can access a variety of information and knowledge according to relevant needs. The internet also has several advantages that are not shared by other conventional sources of information, access to information can be done with restrictions on distance, time and space which is part of the advantages of the internet. Making it possible to get the source of the information obtained. Thus, based on the results of a survey conducted by the previous author, involving 30 respondents who had used internet service packages before, the result was that 90% of respondents had difficulty making the right choice, according to the criteria they wanted. With a decision support system using the MOORA and WASPAS methods, it will be easier to find a solution to the problem of choosing an internet package based on the conditions offered by the various internet operators themselves. These criteria include speed, signal, internet quota, active period and price. Based on the calculations of these two methods, the best smartphone internet card title is alternative A1 with the name Telkomsel with a value for the MOORA method, which is 0.437, while the WASPAS method is 0.942 as the best alternative. So that people don't need to worry about choosing an internet card for smartphones that are good and have good access speeds
The Application Of Multi-Sensor Data Fusion Method with Fuzzy Time Series Model to Improve Indoor Water Prediction Accuracy Quality Khoiri, Isfa' Bil; Erfianto, Bayu
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3082

Abstract

There is a lot of indoor air pollution, especially from cigarette smoke, wall paint, air fresheners and gas. With this situation, the room uses Air Box WP6003 air quality detection device by transmitting information about air quality through visualization index. This study aims to improve prediction accuracy with fuzzy time series methods processed through 2 naïve and moving average models using forecast transformers and without transformers. The level of prediction accuracy is calculated through several metrics, namely Mean Absolute Percentage Error (MAPE), Sum of Squares Error (SSE), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). These results can be calculated between the actual value and the predicted value. The data used is 204584 data from 4 parameters including Temperature, TVOC, HCHO and CO2. The test results with the difference from the forecast transformer and without transformer are comparable. Temperature value obtained using naïve with transformer from RMSE of 0.158866 and naïve without transformer of 0.782397, data using moving average with transformer obtained by 0.147546 and moving average without transformer of 0.772570. This can be explained by the error analysis that was tried, where the error rate continued to increase so that the experimental results continued to be far from the actual number. From the test results it can be concluded that the accuracy of air quality prediction using naïve forecast transformer is pretty accurate.
The Anomaly Detection in Time Series Data of VOC (Volatile Organic Compound) To Generate Indoor Air Quality Alerts Nusantara, Hadi Dharma; Erfianto, Bayu
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

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

Abstract

Indoor air quality is a very important factor and needs to be considered for health. Poor indoor air quality can trigger illness, reduce productivity, and disrupt the comfort of people in the space. In residential areas, hospitals, schools, nursing homes and other specialized environments, indoor air pollution can affect groups that are more vulnerable to health problems due to their health conditions or age. This research aims to predict indoor air quality using the Long Short-Term Memory (LSTM) method and provide alerts when the prediction results exceed a predetermined limit. The accuracy level is measured using Mean Absolute Percentage Error (MAPE) by calculating the difference between the original data and the prediction results. In this study, a system was created that utilizes Internet of Things (IoT) technology that can monitor the state of indoor air quality such as temperature, TVOC, CO2 and HCHO gas levels. The system uses the WP6003 Air Box Reader tool as an indoor air quality detector that is connected to the website created. This website can display data that is being recorded, download datasets that have been recorded, visualize predictions of temperature, TVOC, CO2 and HCHO and notify if any data crosses a predetermined limit. The results obtained are quite good prediction accuracy by getting a MAPE value of 0.30452, RMSE 0.023475 and the average value of the test data is 24.035 which means that if the RMSE value is close to 0, the prediction results will be more accurate. Anomalies result in values of room temperature and HCHO that are above normal limits.
Hoax Detection Using Long Short-Term Memory (LSTM) and Gate Recurrent Unit (GRU) on Social Media Putra, Dion Pratama; Setiawan, Erwin Budi
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3084

Abstract

There are negative effects of the ease of obtaining information in today's society, one of which is the rise of hoaxes on the internet. As much as 92.40% of social media platforms such as Twitter are used to spread hoaxes. Launched on July 13, 2006, Twitter is a microblogging service where users can spread information at no cost to themselves or others. In this study, the authors will conduct hoax news detection on Twitter social media using the Long Short - Term Memory (LSTM) method and Gate Recurent Unit (GRU) and gloVe feature expansion. with a dataset of 25,234 data which produces accuracy results in TF-IDF on each model, namely 97.33% in LSTM and 96.75% in GRU, and an increase in accuracy of 0.22% in the tweet corpus on LSTM and an increase in accuracy of 0.15 in the BeritaTweet corpus on GRU.
Aspect-based Sentiment Analysis on Social Media Using Convolutional Neural Network (CNN) Method Ramadhan, Ananta Ihza; Setiawan, Erwin Budi
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3103

Abstract

Social media are a platform for people to express their opinions on various topics, one of which is Twitter. Movie reviews are a frequently found topic on Twitter that contains a person's opinion of a movie that has been watched. But since opinions are subjective, it is difficult to determine an accurate assessment of a movie. In addition, the diverse aspects of a movie make it difficult to judge whether a review is positive or negative. Referring to that problem, a method is needed to perform sentiment analysis of the problem. In this study, sentiment analysis of movie reviews was carried out based on aspects of plot, acting, and director. This research also performs classification using a CNN model and combines several techniques, namely TF-IDF feature extraction, FastText feature expansion, and SMOTE to calculate the accuracy value and F1-Score. The final results obtained in this study are in the aspect of the plot getting an accuracy of 73.81% (+12,22%) and F1-score 73.72% (+15,93%), the acting aspect obtaining an accuracy value of 89.30% (+0,54%) and F1-score 89.26% (+50,80%), and in the aspect of the director having an accuracy of 87.37% (+0,28%) and F1-score 87.35% (+84,39%). Based on these results, each application of techniques such as TF-IDF, FastText, and SMOTE can increase the accuracy value and F1-Score of the model built.
Aspect-Level Sentiment Analysis on Social Media Using Gated Recurrent Unit (GRU) Kamil, Ghani; Setiawan, Erwin Budi
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3105

Abstract

Twitter is one of the popular social media for sharing opinions, one of which is about movie reviews. There are many opinions related to movie reviews on Twitter social media so the assessment of a movie can vary. Therefore, aspect-level sentiment analysis is needed to classify movie reviews to provide optimal results. This research was conducted by building a system using the Gated Recurrent Unit (GRU) method to perform sentiment analysis at the aspect level on movie reviews taken from Twitter. The aspects used in this research are plot, acting, and director. This research also conducted experiments by combining three techniques, which are feature extraction using TF-IDF, feature expansion with GloVe, and the application of SMOTE to improve model accuracy. The results show that each test scenario can improve the accuracy and F1-Score values of each aspect. The final value of each aspect is the accuracy value for the plot aspect is 70.40%(+7.62%) and F1-Score is 70.35%(+9.70%), the accuracy value is 93.75%(+6.28%) and F1-Score is 93.70%(+65.19%) for the acting aspect, and the accuracy value is 90.44%(+4.60%) and F1-Score is 90.17%(+122.80%) for the director aspect.
Sistem Monitoring dan Kontrol Aeroponik Menuju Smart Greenbox untuk Tanaman Selada berbasis IoT Karna, Nyoman; Naufal, Rangga; Raniprima, Sevierda; Putra, I Kadek Andrean Pramana; Rahyuni, Dewa Ayu Putu; Parti, I Ketut
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3125

Abstract

Horticultural commodities are agriculture that has a lot of demand in the market. Based on this, a planting system with the aeroponic method was made with an IoT-based monitoring and control system so that its growth is maintained. A system with complex planning is needed to simplify human life. Then a remote monitoring and control system was designed with IoT technology in the aeroponic method. The way this tool works is to send sensor data from the Node MCU via the internet to the cloud and the data is stored in real-time in the Firebase, the data is sent to the Android platform so that the data can be read by the user and the data is sent to a Google spreadsheet automatically which will later be analyzed. Will update data every 15 minutes. In this study, calibration of the DHT11 sensor with HTC Digital obtained an accuracy of 95.5% humidity and 97% temperature, the LDR sensor with LUX meter obtained an accuracy rate of 75.163%, pH sensor with pH meter 97.33%, ultrasonic sensor and ruler. get 100% accuracy, the bandwidth used is 20 Mbps. The network quality test is delayed, with 3 different test times, busy hours (19.00 - 23.00 WIB), empty hours (01.00 - 03.00 WIB), normal hours (12.00 - 14.00 WIB). From network testing, the minimum delay is 0.255 seconds, and the maximum is 0.291 seconds. The results of testing tools during seeding, lettuce plants can grow well.
Undersampling dan K-Fold Random Forest Untuk Klasifikasi Kelas Tidak Seimbang Qadrini, Laila
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3141

Abstract

Classification in Data Mining is a process of modelling that explains and differentiates data classes intending to estimate the class of an object whose class is unknown. Classification can be applied in various aspects so over time quite a lot of classification algorithms have been developed, but some problems are often encountered in classification, namely the problem of data imbalance. An imbalanced class is a condition where there are several data where the number of classes is not balanced or there is a significant difference in each number of classes. Most classification datasets do not have the same number of classes. However, the class imbalance is not a problem when the comparison between classes is not much different. Class imbalance can cause problems if left untreated because the resulting model predictions will tend to the majority group so that the contribution of the minority class to the model is small. One of the algorithms that are often used to handle unbalanced classes is the resampling algorithm. The purpose of this research is to apply the Resampling Undersampling Random Forest and Random Forest K-Fold Undersampling Algorithms to the Breast Cancer Diagnostic dataset from UCI Machine Learning. Undersampling was chosen because it produces better accuracy than oversampling. Recall accuracy for the K-Fold 10 Random Forest Algorithm is 83% and for Recall Undersampling Random Forest is 65%.
Penerapan Data Mining Pada Analisa Pola Pembelian Obat Menerapkan Algoritma Hash Based Aldisa, Rima Tamara
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3142

Abstract

Along with the times, human life is also developing. Both from the mindset, perspective and way of life. The development of the times requires society to participate in developing following an increasingly sophisticated era. One of the developments that cannot be denied in social life is the development of increasingly sophisticated technology. So that in doing a business skills are needed in managing and managing a business in accordance with technological developments. The business of selling drugs or often called pharmacies is a business that is spread in almost all corners of the world, including in Indonesia. Pharmacy is a business engaged in medicine. Pharmacies sell various types of drugs that are likely to be prescribed by a medical doctor, or other drugs that are commonly purchased by the public. Here the author's case study is one of the pharmacies in the East Jakarta area. The sustainability of a business can be influenced by several aspects, but the main aspect that is very influential is business management. The database is information about all transactions that have been carried out in the business. Where with the previous sales database, business owners can assess which products are of great interest to consumers and which are not of interest to consumers. This can help business owners prevent losses in terms of expiration dates and manage stocks of goods. This management should be done by optimizing data mining by applying a hash-based algorithm. The Hash Based Algorithm is an algorithm that aims to find combination patterns of several alternatives with criteria or attributes that are used as comparisons by calculating using filtering techniques so as to produce an itemset combination pattern. Based on the results of research using a hash based algorithm, 3 itemsets were produced which became the top priority, namely B = Amoxiline, E = Amyl Nitrite and G = Biotin with a support value of 20% and 50% confidence
Sistem Pendukung Keputusan Pemilihan Tablet PC Menggunakan Metode WASPAS dan MOORA Syam, Syahriani; Waworuntu, Alexander; Ayuningtyas, Astika; Harun, Rofiq; Nadjamuddin, Lukman
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3147

Abstract

Tablet Pc is a personal computer with a portable design that is equipped with a main input device, namely a touch screen and is designed for individual use. The use of the screen as an input intermediary can use a fingertip and a digital pen. Thus making the production of personal tablet pc increasingly improve its quality so as not to lose competitiveness. Decision Support System is a computer-based information system created to determine decisions so that they are more in solving problems that are structured and unstructured, so the resulting decisions are more appropriate. The system created is a system by utilizing the WASPAS and MOORA methods. A system that utilizes the WASPAS and MOORA methods so that it is suitable in determining the best type of Tablet PC. So the one that gets the title of the best Tablet PC is the A1 alternative with the name Samsung Galaxy Tab S8 Ultra with the value for the WASPAS method, which is 0.456, while the MOORA method is 0.439 as the best alternative

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