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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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A Study of Feature Selection Method to Detect Coronary Heart Disease (CHD) on Photoplethysmography (PPG) Signals Faizal Akbari Putra; Satria Mandala; Miftah Pramudyo
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2259

Abstract

Coronary Heart Disease (CHD) is a condition in which the heart's blood supply is blocked or disrupted by fat in the coronary arteries. This disease is the most significant cause of death in Indonesia. CHD can be detected based on the Heart Rate Variability (HRV) index of the Photophletysmograph (PPG) signal taken from a smartphone's camera. However, the use of PPG from smartphone to detect CHD is still rare in real-world applications. Moreover, studies on CHD detection based on PPG signal are also difficult to be found in the scientific literature. Currently, the Electrocardiogram (ECG) signal still dominates as a signal for detecting CHD. This research fills this research gap by proposing a study on the feature selection of PPG signal to detect CHD. There are three feature selection methods studied in this research, i.e., Analysis of Variance (Anova), Pearson Correlation, and Recursive Feature Elimination (RFE). Furthermore, a classification algorithm, called as K-Nearest Neighbors, has also been chosen to create a machine learning model based on the PPG features. The experimental results show that the Pearson Correlation feature selection method produces better CHD detection performance compared to the other two algorithms (Anova and RFE). CHD detection performance using the Pearson Correlation produces an accuracy of 90.9%, sensitivity of 75%, and specificity of 100%.
Analisis Kinerja Algoritma Machine Learning Untuk Klasifikasi Emosi Sudianto Sudianto
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2261

Abstract

Social media is a place to express or share daily activities. Various new events are often discussed on social media, such as on Twitter. Frequently, the conversations conducted by Twitter users when giving a review or opinion have various emotions, such as anger, sadness, fear, or joy. Emotions are difficult to describe the challenges that occur, sometimes leading to multiple interpretations and misunderstandings leading to debates and reporting to the authorities. So this shows that emotions in reviews and opinions are essential for classification because emotions that come from texts are difficult to understand. In addition, the classification of emotions needs to be done to speed up the identification of emotions. The purpose of this study is to find out which algorithm has optimal performance in the classification of emotions. Machine Learning methods are the Naïve Bayes algorithm, Random Forest, and Support Vector Machines; this is done to determine the dominant algorithm in classifying emotions. The results of the modeling and classification using the Random Forest algorithm obtained a dominant accuracy with an accuracy value of 81.3%, followed by the SVM algorithm with an accuracy value of 76.6% and an accuracy value of 79.1% Naïve Bayes algorithm. In addition, from the speed of time in completing the classification, the Random Forest algorithm has the fastest time of 1.27 seconds
Sistem Pendukung Keputusan Kelayakan Penerima Bantuan Dana KIP Kuliah Menggunakan Metode ROC-EDAS Agus Iskandar
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2265

Abstract

Education is one of the keys in achieving the ideals of the nation's children, there are often economic or financial constraints for the Indonesian people who are unable to be able to attend higher education stages, this makes the ideals of the nation's generation to be smart and have the potential to build the nation. being more advanced becomes hampered, this phenomenon makes the government take action in making an assistance program in the form of a card called the smart Indonesia card or (KIP), the provision of scholarship funds in the smart Indonesia card program of course has terms and conditions that can be met to get the right and disbursement of funds, the number of students who want to get KIP (Smart Indonesia Cards) aid funds makes the manager really have to manage the eligibility of recipients of KIP (Smart Indonesia Cards) funds, a procedure that often happens fraudulently and requires a process of calculating the eligibility of receiving aid. ana KIP (Smart Indonesia Card) which is still less accurate makes the manager of the selection of aid recipients have to take into account the eligibility of the beneficiary very well so that the beneficiary is really the right person. A decision support system is used to obtain more precise and accurate results based on the calculation of a hybrid method which is a combination method so that the results obtained are of higher quality, the method used is the ROC-EDAS hybrid method. The results obtained in using this method are found an alternative named isty with the highest score of 0.207622 who became a student who deserved to receive tuition assistance KIP funds
Implementasi Algoritma Resilient untuk Prediksi Potensi Produksi Bawang Merah di Indonesia Nurhayati Nurhayati; Mhd. Buhari Sibuea; Dedi Kusbiantoro; Martina Silaban; Anjar Wanto
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2269

Abstract

Shallots are seasonal horticultural crops with high economic value. They are one of the horticultural commodities prioritized by the Director General of Horticulture and the Ministry of Agriculture in their development and handling. Therefore, it is necessary to predict the potential of shallot production in Indonesia so that the government has benchmarks and information in determining the right economic policy so that shallot production can continue to be increased or at least be unstable every year. In this study, the prediction algorithm used is the Resilient algorithm. The research data used are shallot production data obtained from the Indonesian Central Statistics Agency. This research will be analyzed using four network architecture models: 6-5-1, 6-10-1, 6-17-1 and 6-29-1. Based on the analysis of the four models used, the results show that the 6-17-1 model is the best because it has a lower Mean Square Error (MSE) value than the other three models, which is 0.0337792, and the accuracy level is quite good. Of 79% with an error rate of 0.04 used. This architectural model will be used to predict the potential for shallot production in Indonesia. Based on the overall prediction results from each province, the potential for Indonesian shallot production at the end of 2022 tends to decrease compared to 2021. The conclusion can be drawn that the application of the Resilient algorithm to the problem of red onion production data in Indonesia is quite good, but the accuracy is not too high, so a more profound study is needed
Implementation of Spatial-Level Augmentation on Pneumonia Classification with Convolutional Neural Network Wahyu Andi Saputra
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2270

Abstract

Pneumonia is a disease with symptoms of difficulty breathing, fever, dry cough, and chest pain. As an indication that a person has COVID-19, it is necessary to immediately identify pneumonia by a doctor whether the lung X-ray image of the patient is classified as pneumonia or not. The importance of early diagnosis can reduce the risk of death in patients. Convolutional Neural Network is one of the fields of study in the realm of Computer Science that can perform image-based object classification. CNN can be used to identify pneumonia based on thorax images based on the features or features displayed on the image. One of the important elements in CNN is the amount of data that can be used for training, validation, and testing. Generally, the more data entered, the more learning material for the CNN system so that the system can classify more accurately. This study aims to measure the accuracy of the CNN model on thoracic-pneumonia images with spatial level augmentation changes. Image augmentation is implemented to increase image variance with initial data of 5856 images. The applied augmentations are Affine, Flip, Pixel Dropout, Random Size Crop, and Shift Scale Rotate. The stages of this research are manually grouping images, implementing augmentation on images, applying training-validation-testing on CNN, and analyzing the output results of the developed system. By using 5 types of augmentation, the dataset used as learning material can be increased up to 5x the original amount. From the research carried out, it was found that the Random-sized Crop type augmentation gave the highest accuracy value of 94.719% or an increase of 3.808% from the non-augmentation testing data. From this research, it is hoped that studies related to augmentation can be a reference regarding the type of augmentation process and its results in finding the CNN accuracy value, especially in the case of pneumonia classification
Two Factor Authentication Sistem Inventarisasi Barang dan Manajemen Dana Bantuan Operasional Sekolah Dinas Pendidikan Nasional Neneng Nuryati; Carolina Magdalena Lasambouw; Djoni Djatnika; Linda Lina Meilinda; Farida Agoes; Muhammad Rizqi Sholahuddin; Maisevli Harika
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2297

Abstract

Inventory of goods at large institutions is a complicated activity; one solution is to create a structured web application system that can be accessed anywhere. At the National Education Office, it is not only inventory management that is a problem but also the management of the School Operational Assistance Fund (BOS). Data security must be a priority because it involves significant funds and can be misused by irresponsible parties. This study aims to apply Two Factor Authentication to the Goods Inventory System and BOS Fund Management. The first stage is verification by the DISDIKNAS admin at each level of education. Next, a verification email will be sent to the registrant for verification. The results showed that the use of 2FA did not interfere with the performance of the web-based application or its users. The approval rate for the system is 97.4%. This research contributes to the implementation of website security and can be applied to similar systems
Penerapan Algoritma Apriori Data Mining Untuk Menentukan Penyusunan Layout Barang Pada Toko Ritel Agung Triayudi
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2303

Abstract

Retail is an activity that includes the sale and purchase of goods. For retail stores, the continuity of the business processes that are carried out is very dependent on the sale of goods or the purchase of goods from consumers. Retail stores today must have a strategy or a way to increase sales of their goods. One strategy that can be applied in increasing sales is the preparation of the layout of goods. Errors in the preparation of the layout of goods are of course very detrimental to retail stores, these errors can lead to a stagnant sales process or also decreased sales. The arrangement of the layout of goods can be done by looking at the characteristics of the goods purchased by consumers or commonly referred to as goods associations. Data mining is a technique that can be used to process data. In data mining itself there are many ways that are used to solve problems, one of the ways used to solve problems in data mining is the a priori algorithm. The combination of items obtained by consumers buying item A will also buy Item B with a support value of 20% and a confidence value of 50%. Another combination of items is that consumers buying item A also buys item D with a support value of 10% and a confidence value of 25%. The last combination of item sets, namely Consumers buying item B will also buy item D with a support value of 20% and a confidence value of 50%
Penerapan Metode VIKOR dan WASPAS Dalam Pemilihan Handphone Bekas Agung Triayudi
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2308

Abstract

Mobile is a sophisticated telecommunication tool to be able to interact with fellow human beings where the communication does not look at near or long distances between people who use the cellphone in communicating well. Mobile phones also have very high capabilities, which can be similar to computers, but mobile phones can be taken anywhere because they have a very minimal size and weight compared to computers. For Mobile Users, it seems to be a need for the whole community that has been widely used by all groups ranging from children, teenagers to the elderly. There are new cellphones and there are also used ones, many prefer to buy used cellphones because besides the prices are much cheaper, even the quality is still good. Therefore, a decision support system is needed to make it easier for used cellphone enthusiasts to get cellphones with good quality and specifications. The methods used are VIKOR and WASPAS methods. The selection of used cellphones is carried out based on predetermined criteria. The results of the application of the VIKOR method with the best alternative are on A3 of 0.793 while based on the WASPAS method the best alternative is on A4 with a reference value of 0.886
Hotel Selection Decision Support System with the Simple Additive Weighting (SAW) Method Utami, Annisaa; Usman, Muhammad Lulu Latif; Ramadhani, Ike Fitria; Syam, Siti Nur Fadilah; Fauzan, Fikrian Akmal
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.v4i3.2262

Abstract

Purwokerto as the city center in southwestern Central Java which is one of the tourism places in Central Java with a fairly large number of enthusiasts. Purwokerto City has a wide selection of tourist attraction destinations that can be visited by tourists. There are not a few tourists who come from outside the city and do tours for more than one day. If you look at these conditions, a temporary stopover place is needed, namely a hotel. Purwokerto City provides so many choices of hotels spread across various locations with lodging classes, rental prices, facilities and services that are diverse. With the existence of many and different hotel facilities, of course, visitors will find it difficult to find and determine a hotel that matches the desired criteria. In addition, they will also find it difficult in finding the location of the desired hotel. The calculation results using the SAW (Simple Additive Weighting) Method found that Java Heritage Hotel got a value of 0.9, Resort and Hotel Atrium by 0.77, Surya Yudha Hotel by 0.65 and Trisno Hotel by 0.55. And get the same result between manual calculations and calculations from the system.. Based on the description above, in this study a decision support system was developed that can help tourists to determine hotels according to the wishes and needs of tourists using the SAW Method (Simple Additive Weighting)
Penerapan Algoritma Decision Tree Untuk Penentuan Pola Penerima Beasiswa KIP Kuliah Arfyanti, Ita; Fahmi, Muhammad; Adytia, Pitrasacha
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.v4i3.2275

Abstract

The Indonesian Smart College Card (KIP Lecture) is a government program that has been implemented from 2020 until now. KIP Lectures are distributed by the Ministry of Education, Culture, Research and Technology through universities in each region. Where each university gets a different quota - based on the level of progress of the college. The provision of quotas for each university based on the accreditation at each university raises its own problems for these universities. The problem faced is that the number of new prospective students who register to take the KIP Lecture program exceeds the quota set for each university. The provision of KIP Lecture assistance to the wrong person will lead to misuse of assistance and also inappropriate targets. The acceptance of the selection process for new prospective students can be seen from the previous process that has been carried out. Data mining is a technique used to solve problems in large data processing. Decision Tree is an algorithm that is included in the classification technique in data mining. The process in the decision tree aims to group or classify data against their respective classes. The results of the Decision Tree algorithm are in the form of decision trees and rules, the results obtained are in the form of rules that can be used for future decision-making processes

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