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SAINTEK
Published by Universitas Pelita Bangsa
ISSN : -     EISSN : 29623545     DOI : 10.37366/SAINTEK
Core Subject : Science, Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering
Prosiding Sains dan Teknologi (SAINTEK) merupakan wadah publikasi dari hasil penelitian yang telah dipresentasikan pada Seminar Nasional Sains dan Teknologi (SAINTEK) yang diselenggarakan setiap tahun oleh Fakultas Teknik Universitas Pelita Bangsa. Penelitian yang dipublikasikan bersifat multi-disiplin dalam ruang lingkup Teknik tentang analisa dan implementasi perkembangan teknologi. 
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 355 Documents
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Analisa Prediksi Harga Saham Blue Chip Lq45 Dengan Metode Data Mining Backpropagation Neural Network (Studi Kasus Di Bursa Efek Indonesia) Puguh Ariyadi; M.Makmun Effendi; Sugeng Budi Raharjo
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366.SAINTEK0101.6876

Abstract

This research is a research on predictive analysis of LQ45 blue chip stock price with backpropagation neural network data mining method. This study aims to determine the stock price prediction process using the backpropagation neural network method on the LQ45 blue chip stock price. This research is in training and testing data using RapidMiner tools with 80% data sharing for training data and 20% for testing data. The parameters used are training cycle of 500, learning rate of 0.01 and momentum of 0.9. The results of the training and testing of the stock prices of 5 companies in LQ45 obtained the RMSE (Root Mean Square Error) value with the best result of 11.296 and the largest error of 61.925 which indicates the backpropagation neural network method is quite good in the process of predicting stock prices. The results of this prediction can be used as a reference for stock investors in determining the right strategy to minimize mistakes in making decisions to buy or sell the desired stock. Keywords: Data Mining, Backpropagation Algorithm, Neural Network, Rapidminer, Stock Price
Analisis Sentimen Terhadap Pemerintahan Ridwan Kamil Sebagai Gubernur Jawa Barat Menggunakan Algoritma Naïve Bayes U. Darmanto Soer; Sutrisno Sutrisno
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.7782

Abstract

The use of social media in the era of globalization is very necessary for some circles including the regional leader, in the period of his tenure, Ridwan Kamil received various inputs and criticisms, and in this case the authors conducted research to analyze public sentiments towards the elected governor. And in this study the authors use the Naïve Bayes algorithm to classify sentiments and look for the preference values because the algorithm has a pretty good accuracy. From the results of tests conducted using cross validation techniques and accuracy measurements using confusion matrix with 10 times the best accuracy testing obtained was 84.38% and the positive response obtained from the calculation of preference value was 49%. Thus it can be concluded that the Naïve Bayes algorithm can be used to classify quite well and be able to measure the community's response to regional leaders. Keywords: Sentiment Analysis, Twitter, Naïve Bayes Classifier, Cross Validation, Preference Value
Aplikasi E-Commerce Berbasis Web Untuk Umkm Kerajinan Tangan Di Cikarang Ergi Hermawan
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.8390

Abstract

The background of this research is the lack of promotional media for a product in Cikarang. Therefore, more and more means of marketing goods are starting to use the E-Commerce system as an online sales medium. In the process of building an ECommerce website, it uses a life cycle development technique or can be called a waterfall. The goal to be achieved from the development of this E-Commerce system is to make it easier for buyers to make transactions wherever buyers are without having to come to the store. Keywords: E-Commerce; Laravel; Web-based application; Online store
Dampak Game Terhadap Anak Usia Dini Edora Edora; Ahmad Turmudi Zy
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.9195

Abstract

Digital technology changes many aspects of the daily life of Indonesian people, from socializing to education, from formal and informal matters to all involving digital technology, and this also involves all age groups, from early childhood to the elderly. There are also many digital games that are loved by all ages. The problem is the impact of digital-based games using mobile phones or tablets. Here the author focuses on research on the impact of digital games on an early age in terms of benefits on the growth and development of early childhood, in this paper some research from various parties who are competent in this research will be presented. those it can be concluded that there are positive and negative impacts of digital games (games) in early childhood. Keywords: Digital Technology, Game, Childhood, Impact.
Implementasi Sistem Pengenalan Candi Kecil Di Yogyakarta Menggunakan Machine Learning Berbasis Cloud. Ahmad Fatih; Muhammad Najamuddin Dwi Miharja
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.96102

Abstract

In accordance with the national plan according to Presidential Regulation Number 58 of 2014 concerning the Spatial Plan for the Borobudur area, Borobudur is a national mainstay tourism area. As a result, data on visitors to Borobudur temple has increased greatly, the data for the last year of visitors to Borobudur temple every day can reach 55,000 people per day, especially during the national holiday season and school holidays, this has an impact on the condition of the temples and stupas which are increasingly exposed to friction between visitors. thus giving rise to new regulations regarding the daily visitor limit of only 1,250 per day. With the limitation of visitors to Borobudur temple, it is possible for tourists to change their tourist destinations to small temples around Yogyakarta which are less exposed by tourists, such as Sambisari temple, Gebang temple or Ijo temple and so on. one way to get to know more about the temples around Yogyakarta is to create a temple recognition system with the help of the implementation of cloud-based machine learning from nyckel.com, namely a platform as service for machine learning. from the test results on a dataset of 50 images with a distribution of 80 to 20. resulting in a confidence value of an average of 95% this number can prove that the temple recognition model with cloud-based machine learning can be used for temple recognition properly. Keywords: Recognation System, Machine Learning, Cloud
Implementasi Chatbot Deteksi Depresi Dini Pada Mahasiswa Dengan Phq-9 (Patient Health Questionnaire) Menggunakan NLP (Natural Language Processing). Muhammad Najamuddin Dwi Miharja; Shohibul Adhkar
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.103108

Abstract

One of the serious problems in public health according to the World Health Organization (WHO) is depression. According to WHO depression ranks fourth disease in the world. When someone experiences depression, it will have an impact on reduced productivity, especially for students. The Patient Health Questionnaire (PHQ-9) is a sequence of questions in the initial screening of depression to see the initial severity of depression. Chatbots are applications with artificial intelligence that can communicate with humans. Natural Language Processing is one of the subtopics of Artificial Intelligence, which is an application that can have the advantage of understanding human language normally. In this study, a chatbot service was implemented for Early Detection of Depression in Students with PHQ-9 (Patient Health Questionnaire) using NLP (Natural Language Processing). It was found that around 84% answered that chatbots can help for early detection of depression. Keywords: Chatbot, Natural language Processing (NLP), PHQ-9
Implementasi Sistem Informasi Pembayaran SPP Berbasis Web Dengan Metode SDLC Waterfall Studi Kasus Di SMA Al Maghfirah Siti Nurjanah Faujiah
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.109120

Abstract

One tangible form or realization of the use of dynamic web programming is in terms of making an information system that is used as a tool in the management of student payment administration in a school. In this case, the Administration or the finance department can later use it as inputting student payment data while carrying out learning activities at the school. At Al Maghfirah High School (SMA Al Maghfirah), in terms of recording student tuition payments, they still use recording in the ledger and Microsoft Excel assistance in their financial recap. Students will fill out a payment form then give it to the financial administration section. With these activities, from the financial officer's point of view, they will carry out a lot of work processes such as storing forms paid by students, recording them in a ledger, recapitulating them on the computer and even making reports that will be given to the principal. The results of this study are a student tuition payment information system that is able to manage student tuition payment information, facilitate payment information for students and make reports for payment officers or the finance department every period. By creating a web-based information system using the SDLC Waterfall system development method, it is hoped that it can help the process of paying tuition fees for students at SMA Al Maghfirah Cikarang Bekasi. Keywords: Waterfall, System Development Life Cycle, SDLC, Payment
Klasterisasi Data Penggunaan Layanan BPJS Kesehatan Menggunakan Algoritma K-Means Sandi Salvan N N; Wahyu Hadikristanto; Edora Edora
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.121127

Abstract

BPJS Health, which is organized by the government by upholding the principle of mutual assistance in equalizing public health insurance, many patients use these facilities. The clustering method is processed with the K-Means algorithm, where the results also show a new insight, namely grouping the use of BPJS health services based on 3 clusters. Cluster 1 is a category of health facilities with low or Low use of BPJS health services, which is 353 out of 1000 categories of health facilities based on the number of BPJS health service usages tested, then cluster 2 is a category of health facilities with moderate or Medium use of BPJS health services, which is 474 out of 1000 categories. the name of the health facility based on the number of health BPJS service usage tested, and lastly cluster 3 is the category of health facility name with the use of BPJS health services quite high or High, namely 173 out of 1000 categories of health facility names based on the number of health BPJS service usage tested. Tests using Rapid Miner tools can also produce similar insights, namely each cluster has cluster group members according to manual calculations such as Cluster_0 on Rapid Miner has 474 cluster members representing the Medium cluster, Cluster_1 has 353 cluster group members as the Low cluster representation, and Cluster_2 has 173 cluster members that correspond to the cluster representation of High. Keywords: Data Mining, K-Means, BPJS Health
Komparasi Algoritma Naïve Bayes Dan K-Nearest Neighbor Dalam Melihat Analisis Sentimen Terhadap Vaksinasi Covid-19 A. Yudi Permana; Hendri Noviyani
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.128134

Abstract

Twitter is often used to deliver messages in the form of public opinion or opinion about the topic that is being reported. The government's policy to vaccinate has received various comments, ranging from praise, criticism, suggestions, and even hate speech. With so many twitter users who express their opinion, it can be used to find information. However, its use requires proper analysis, so that the resulting information can help many parties in making decisions or choices. Therefore, in this study, we tried to analyze sentiment on Covid-19 vaccination using the Naïve Bayes and K-Nearest Neighbor algorithms using the Cross Validation technique. The purpose of this study is to find out whether the Naïve Bayes and K-Nearest Neighbor algorithms in classifying produce optimal accuracy, to determine the sentiments of twitter users towards the Covid-19 vaccination and how much influence preprocessing has to measure accuracy on the classification. Based on the research that has been carried out, it can be concluded that the application of preprocessing for sentiment analysis on Covid-19 vaccination using the Naïve Bayes and K-Nearest Neighbor algorithms accompanied by the use of the Cross Validation technique got quite good results. The Naïve Bayes algorithm produces an accuracy of 77.62% and the K-Nearest Neighbor algorithm produces an accuracy of 76.43. Then for the positive response rate of the community to the Covid-19 vaccination, it was 55.63%. Keywords: Comparison, Naïve Bayes, K-Nearest Neighbor, Sentiment Analysis,Vaccination, RapidMiner
Komparasi Machine Learning Memprediksi Phising Dalam Keamanan Website Aswan Supriyadi Sunge
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.135140

Abstract

The growth rate of online mobility is fast and increases sharply from desktop to mobile phone. Growth is recognized by users because of the ease of searching for information and dealing mainly in banking matters. Behind them, there is the most important issue of security on the Internet, one of them Phishing which means to resemble official or original websites when false with the intention of obtaining user information. There fore it takes a malicious web-based Phishing alias by using data set, then tested with some Machine Learning algorithms and then to compare the best and highest predictions. Computer simulation results have resulted an accuracy of up to 95.24% for the techniques used and the comparison with other models. Keywords: Predictions, Website, Phishing, Machine Learning

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