Analysis and Implementation Machine Learning for YouTube Data Classification by Comparing the Performance of Classification Algorithms

Every day, people around the world upload 1.2 million videos to YouTube or more than 100 hours per minute, and this number is increasing. The condition of this continuous data will be useless if not utilized again. To dig up information on large-scale data, a technique called data mining can be a solution. One of the techniques in data mining is classification. For most YouTube users, when searching for video titles do not match the desired video category. Therefore, this research was conducted to classify YouTube data based on its search text. This article focuses on comparing three algorithms for the classification of YouTube data into the Kesenian and Sains category. Data collection in this study uses scraping techniques taken from the YouTube website in the form of links, titles, descriptions, and searches. The method used in this research is an experimental method by conducting data collection, data processing, proposed models, testing, and evaluating models. The models applied are Random Forest, SVM, Naive Bayes. The results showed that the accuracy rate of the random forest model was better by 0.004%, with the label encoder not being applied to the target class, and the label encoder had no effect on the accuracy of the classification models. The most appropriate model for YouTube data classification from data taken in this study is Naïve Bayes, with an accuracy rate of 88% and an average precision of 90%

Analisis Faktor Yang Mempengaruhi Penerimaan Pengguna Aplikasi Elektronik Renumerasi Kinerja (E-RK) Menggunakan Metode UTAUT dan SDT (Studi Kasus : Pemerintah Kabupaten Musi Rawas)

The E-RK application is an application that has an impact on government employee performance assessment through an electronic system. The purpose of this study is to determine the level of acceptance and users of the use of the E-RK application within the Musi Rawas Regency Government by using the Unified Theory of Acceptance and Use Technology and Self Determination Theory approach. . The type of data used is primary data obtained from questionnaires. The number of samples was 100 employees, then the data obtained were analyzed using the Structured Equation Model-Partial Least Square (SEM-PLS) method using smartPLS software. The results showed 3 out of 10 hypotheses that had a significant positive effect, namely the variable perception of the relationship to behavioral intention with a path coefficient value of 0.273 and a t-statistic value of 3.199, an anatomical perception variable on behavioral intention with a path coefficient value of 0.200 and a t-statistic value of 2.161, and the variable behavioral intention to use behavior with a path coefficient value of 0.544 and a t-statistic value of 5.23

A Comparison Between Naïve Bayes and The K-Means Clustering Algorithm for The Application of Data Mining on The Admission of New Students

The process of admitting new students at Universitas Islam Negeri Raden Fatah each year produces a lot of new student data. so that there is an accumulation of student data continuously. The purpose of this study is to compare the K-Means Clustering Algorithm and Naïve Bayes on the admission of new students as well as being one of the bases for making decisions to determine the promotion strategy of each study program. The data mining method used is Knowledge Discovery in Database (KDD). The tools used are Rapid Miner. The attributes used are national examination score, school origin, and study programs. The new student data used from 2016 to 2019 was an 18.930 item. The results of this study used the K-Means Clustering Algorithm to produce 3 clusters, while the Naïve Bayes results resulted in an accuracy value of 9.08%

Perancangan Sistem Informasi Kolaborasi Kampus Pendamping Bumdes Sumatera Selatan Dengan Menggunakan Metode Extreme Programming

Berkembangnya teknologi dengan begitu cepat pada era sekarang yang juga memberikan dampak pada berbagai aspek kehidupan. Begitu juga pada pertumbuhan ekonomi yang semakin tinggi. Masyarakat juga dituntut untuk menggunakan teknologi agar dapat berkembang didunia pemasaran dan mengenalkan produk atau usaha mereka. Adapun pada penelitian ini menggunakan metode extreme programming karena pengembang dan pengunjung website dapat saling memeberikan informasi sehingga dapat memudahkan dalam melakukan pengambangan sistem tersebut. Tahap-tahap yang kerjakan yaitu perencanaan(planning), perancangan desain(design), dan melakukan uji coba(testing). Adanya website Kolaborasi Kampus Pendamping Badan Usaha Milik Desa (KKP Bumdes Sumsel) masyarakat desa dapat bergabung dan mengenalkan berbagai produk mereka kepada masyarakat sekitar maupun luar daerah mereka

Classification of the Fluency Multipurpose of Bank Mandiri Credit Payments Based on Debtor Preferences Using Naive Bayes and Neural Network Method

One that has an important role in generating bank profits is providing credit to customers, but credit also carries a very high risk. For this reason, in providing credit to debtors, of course the bank will utilize the personal data of prospective debtors in detail to avoid the risk of problems that will arise in the future. One of the appropriate risks for banks in providing credit is the behavior of customers who do not pay installments at the time which causes bad loans. To overcome and overcome the many bad events, there is an algorithmic calculation method with an intelligent computing system that helps banks in selecting prospective debtors who will be given credit. There are many algorithmic methods that can be used in this kind of research. This study analyzes the classification of staffing credit based on the criteria that become the Bank's standard.The data used by the author in this study uses existing debtor credit data from 2017 to 2020, the modeling process is carried out using split validation with the Naive Bayes algorithm and Neural Network, with this algorithm the 1,314 datasets is divided into 2 parts, namely 80% used as training data and 20% used as testing data. The results showed that the Neural Network algorithm has better results with a correct value of 84.13%, while the Naive Bayes algorithm only produces a value of 72.62

Perancangan UI/UX Aplikasi Forum Diskusi Mahasiswa Universitas Bina Darma Dengan Menerapkan Metode Design Thinking

Information on academic activities at Bina Darma University can be obtained via WhatsApp messages to PPM, however, these contacts can only be contacted according to working hours, while students need a medium to exchange information quickly. Student discussion forum applications can meet these needs, where fellow students can exchange information without being limited by time, principal, or semester. The UI/UX design of the student discussion forum application was carried out by applying the Design Thinking method by going through the stages of empathize, define, ideate, prototype, and test. In the design process, gestalt principles are also applied to increase user convenience in using the application. The usability testing results show that 60% of respondents stated that the application was easy to use, while 30% said it was straightforward, and the remaining 10% said it was quite easy to use

Analisis Data Twitter: Ekstraksi dan Analisis Data G eospasial

Data geospasial pada media sosial Twitter dapat dimanfaatkan untuk mengetahui informasi spasial (lokasi) yang merupakan lokasi sumber munculnya persepsi publik terhadap sebuah isu di media sosial. Besarnya produksi data geospasial yang dihasilkan oleh Twitter memberikan peluang besar untuk dapat dimanfaatkan oleh berbagai pihak sehingga menghasilkan informasi yang lebih bernilai melalui proses Twitter Data Analytics. Proses pemanfaatan data geospasial Twitter dimulai dengan melakukan proses ekstraksi terhadap informasi spatial berupa titik koordinat pengguna Twitter. Titik koordinat pengguna Twitter didapatkan dari sharing location yang dilakukan oleh pengguna Twitter. Untuk mengekstrak dan menganalisis data geospasial pada Twitter dibutuhkan pengetahuan dan kerangka kerja tentang social media analytics (SMA). Pada penelitian ini dilakukan ekstraksi dan analisis data geospasial Twitter terhadap suatu isu publik yang sedang berkembang dan mengembangakan prototipe perangkat lunak yang digunakan untuk mendapatkan data geospasial yang ada pada Twitter. Proses ekstraksi dan analisis dilakukan melalui empat tahapan yaitu: proses penarikan data (crawling), penyimpanan (storing), analisis (analyzing), dan visualisasi (vizualizing). Penelitian ini bersifat exploratory yang terfokus pada pengembangan teknik ekstrasi dan analisis terhadap data geospasial twitte

Aplikasi Prediksi Kesehatan Menggunakan Machine Learning

Based on data stated by the Ministry of Communication and Information, the level of use of mobile devices and the internet in Indonesia is very high. One application of mobile device technology is in the body health monitoring system. This health care monitoring system will help people monitor their health conditions to prevent and control chronic diseases and allow the medical team to monitor and assist when needed. In this study, a health prediction model and mhealth application were developed using one of the machine learning techniques, namely Naïve Bayes. Mhealth which has been integrated with machine learning can determine the possibility of individuals being healthy, moderately healthy, less healthy, and unhealthy. The body health prediction information data sent are in the form of body temperature, heart rate, systolic and diastolic blood pressure, respiration, and saturation, which are then displayed on a smartphone. With the help of the Health detection app, an individual can find out and deal with it at an early stage, to prevent the situation from getting worseAbstrak   Berdasarkan data yang dinyatakan oleh Kementerian Komunikasi dan Informasi yang menilai tingkat penggunaan perangkat seluler dan internet di Indonesia sangatlah tinggi. Salah satu  penerapan teknologi perangkat seluler ada pada sistem monitoring kesehatan tubuh. Sistem pemantauan perawatan kesehatan ini akan membantu orang memantau kondisi kesehatan mereka untuk mencegah dan mengendalikan penyakit kronis dan memungkinkan tim medis untuk memantau dan membantu saat dibutuhkan. Pada penelitian ini, sebuah model prediksi kesehatan dan aplikasi mhealth dikembangkan dengan menggunakan salah satu teknik machine learning yaitu Naïve Bayes. Mhealth yang telah diintegarsikan dengan machine learning dapat menentukan kemungkinan individu menjadi sehat, cukup sehat, kurang sehat, dan tidak sehat. Data informasi prediksi kesehatan tubuh yang dikirimkan berupa berupa suhu tubuh, detak jantung, tekanan darah sistolik dan diastolik, respirasi, dan saturasi, yang kemudian ditampilkan pada smartphone. Dengan bantuan aplikasi deteksi Kesehatan, seorang individu dapat mengetahui dan mengatasi pada tahap awal, sehingga dapat mencegah situasi menjadi lebih buruk.  Kata Kunci— mHealth, Machine Learning, Classification, Naïve Baye

Analisis Kinerja Private Cloud Computing Menggunakan Metode Reability, Maintanability, Availability dan Security

SMK Negeri 2 Palembang is a school based on technology techniques, the technology used is cloud computing, measurements using the RMA method performance analysis testing using the RMA scanning method were carried out on peak hours from 08.00-10.00 am obtained the availability level of ping sensors is 43.09%, http sensors are 25.32%, imap sensors are 30.8%, pop3 sensors are 36.1% then ping jitter sensors are obtained 61.4%,  From the results  of monitoring with a percentage of  the measurement table from various sensors during peak hours, there are several sensors that have decreased, such as imap and http sensors with availability values of 30.8% and 25.32% so that it affects sensor performance so that a total of 196.71% is classified as Sufficient. tomudian on the security side obtained scanning results using Owasp ZAP Vulnerability is 8 Alerts consisting of 3 medium level risks, 2 low risk levels and 3 risk level information and scanning using NESSUS obtained vulnerabilities, namely: Http server / web server version, scanner port,  Based on the results of the analysis that  network traffic is very vulnerable at 08.00-10.00, so to get a more stable quality, users should access it at 13.00 – 15.00 then on security issues to minimize security gaps can add proxies to the web, upgrade libraries, activate ip and  ports  filter, upgrade http sever.Keywords - RMA, Private Cloud, Nessus, Owasp ZAP

Pelatihan Maintenance, Repair Komputer dan Sumber Daya Manusia pada Lembaga Pembinaan Khusus Anak (LPKA) Kelas 1 Palembang

Universitas Bina Darma  memiliki program tri dharma perguruan tinggi yaitu suatu kegiatan yang bertujuan membantu masyarakat dalam beberapa aktivitas. program ini dirancang oleh berbagai perguruan tinggi di Indonesia untuk memberikan kontribusi nyata bagi bangsa. Untuk mewujudkan hal tersebut maka universitas melalui unit kerjasamanya melakukan kesepakatan kerja sama dengan lapas anak kelas 1 palembang adapun wujud dari kegiatan tersebut maka Dosen Universitas Bina Darma berinisiatip melakukan sharing ilmu dalam berntuk pelatihan selama 5 hari tentang proses maintenance, repair komputer dan Sumber Daya Manusia untuk anak-anak di Lembaga Pembinaan Khusus Anak (LPKA) kelas 1 palembang