Jurnal Infra merupakan jurnal nasional yang diterbitkan dua kali dalam setahun (Februari dan Agustus) oleh Program Studi Informatika, Universitas Kristen Petra, Surabaya sejak tahun 2013. Jurnal Infra memuat artikel penelitian di bidang Teknologi Informasi yang berfokus pada Artificial Intelligence, Game Development, Cyber Security, Mobile Application Development, Enterprise Information System, dan Business Intelligence.
Pengamatan IP Cycling Pada VPN Menggunakan GRC Fingerprints dan DNSLeakTest
As information technology has evolved within the modern era, the needs of information rises along with it. Where every individual need information quickly and accurately, a supporting medium must support it. One of these medium is fast internet. Many are paranoid towards the idea of the government stealing their private information and using it for what they see fit. The objective of this research is to determine whether or not the stability of said VPN is of acceptable levels. The data will be taken hour-by-hour for 30(thirty) days from www.dnsleaktest.com and www.grc.com/fingerprints.htm. The results will then be forwarded to the Google Sheets website that has been programmed to receive the IP, Hostname, ISP and Country tags from the source code from said page. Commercial VPNs are private networks that allow its users to appear to be connecting from another network. This is however not without risk, for those services may not be safe. In this experiment, we have concluded that some VPNs are unstable when used at certain times.
Hybrid Recommendation System untuk Peminjaman Buku Perpustakaan dengan Collaborative dan Content-Based Filtering
The development of technology is growing rapidly and followed with the growth of digital data in the internet. Therefore, recommendation system was invented and can be used in many aspects of human life. For example, a book recommendation system can be used to help user to choose a book to be read which is suitable with their preferences. Using a recommendation system can help to reduce the required time to choose a book because of the massive choices of books. This research using hybrid recommendation system which combined collaborative filtering and content-based filtering method. The purpose of this study was to achieve a better recommendation outcome. To measure how well the result of the recommendation, mean reciprocal rank and mean average precision was used. The results showed that weighted hybrid yields a better score than the other two methods. The score was 0.2113 and 0.0988 respectively
Penerapan Linguistic Inquiry and Word Count dan Random Forest Dalam Klasifikasi Personality Berdasarkan Data Posting Twitter Sehingga Dapat Ditentukan Gaya Belajar yang Sesuai
Big Five Personality is a powerful personality model for understanding the relationship between personality and various academic behaviors. Students' personality is very important for learning and has the potential to determine their academic achievement and learning style. However, not all students have the same knowledge, personality, and learning styles where these criteria affect learning. To find out, we usually use online tests and it takes a long time. In this study, a system was created to determine personality and learning style automatically based on Twitter post data. The method used in this research is LIWC or Linguistic Inquiry and Word Count and Random Forest. Random Forest was chosen because this method can classify class imbalances where in classifying the Big Five personalities from text data, not all of the data have the same number of personalities (extraversion, agreeableness, openness, conscientiousness, and neuroticism). The data text that will be used is data text from social media, namely Twitter with a total data of 9546 data. The results of Random Forest accuracy for balanced and imbalanced datasets are not very significant, such as the imbalanced CON personality has an accuracy of 0.499 while the balanced CON has an accuracy of 0.502 or also the imbalanced NEU personality has an accuracy of 0.502 while the balanced NEU has an accuracy of 0.519. While the results of learning style can be determined from the Big Five Personalities with an average Kendall Tau correlation value of 0.21. According to the compatibility survey of the respondents, respondents felt that the external web was more suitable with the average value of the respondent's suitability with the results of the external web of 4.5 for Big Five Personality and 4 for learning style results. Meanwhile, for the results of the program, the average obtained for the Big Five Personality is 3 while for the learning style it has an average value of 3.25
Sistem Registrasi Dan Identifikasi Wajah Untuk Akses Fasilitas Universitas Kristen Petra Dengan Kombinasi Facenet Dan Hierarchical Navigable Small Worlds
The Identity Cards of students are used to access the facilities and participate in events of Petra Christian University. The problem which arises from these cards is the misuse by the irresponsible group. For this, the university needs the face identification system as the alternative. This thesis is meant to build a fast, accurate, and easy to use face identification system. The methods used to solve the problem is a combination of Facenet and Hierarchical Navigable Small Worlds (HNSW). Facenet is used to process the face into a 128-dimension vector which will be used for searching. HNSW is a k Nearest Neighbor search method which is used in a large-scale search. Using the method, the system takes an average time of 1 second to identify faces.
Analisis Sentimen Mahasiswa di Surabaya Terhadap Pelayanan Vaksinasi COVID-19 Menggunakan Beberapa Classifier
Indonesia is one of the countries that are currently struggling to deal with the COVID-19 virus pandemic by providing vaccination. The government is currently trying to persuade the public to do vaccination by maximizing COVID-19 vaccination services. In reality, vaccination services still have problems with some aspects. To see various insights on vaccination services that have been implemented, therefore a research was conducted in the field of sentiment analysis to analyze public opinion. In this research, classifiers that will be used are Naïve Bayes, Support Vector Machine (SVM), Random Forest, and Light Gradient Boosting Machine (LGBM) to perform text classification and their performances will be compared with evaluation metrics. There are two types of datasets used, namely questionnaire dataset and social media dataset. The questionnaire model will be tested using a social media dataset, while the social media model will use social media dataset that will be split. The testing results show that the model trained with the social media dataset produces better performance than the questionnaire model. Of these four classifiers, the best model for aspect and sentiment classification is Random Forest
Aplikasi Monitoring Pada Tanaman Aglaonema menggunakan IOT
Aglaonema plants are quite difficult to cultivate because the keeper must know what Aglaonema plants need in order to thrive and be beautiful. Aglaonema plants have high sensitivity to roots and stems, as well as leaves. Aglaonema plants require a soil moisture level that is not too moist and not too dry, a soil pH of 6-7, and a placement that is not exposed to direct sunlight. The solution is made by utilizing advanced technology which makes an application that can monitor and maintain the fertility of soil conditions on the Aglaonema plant on a mobile basis and use IOT as a sensor tool to retrieve data which will later be sent to the android application. The trial was carried out by using 2 aglaonema plants to be treated simultaneously. Plant 1 will be treated by volunteers who have just touched Aglaonema so that it provides care like other plants in general, plant 2 will be treated using a monitoring application, trials are also carried out by adjusting the data obtained from aglaonema experts. From the test results, it was found that the effectiveness of the application in monitoring Aglaonema plants has an accuracy rate of 100%.
Sales Management Support and Analytics untuk Meningkatkan Koordinasi Pekerja dan Pelayanan Pembeli UD. XYZ
UD. XYZ is a business that sells products with a wholesale preorder system. The products offered are handicrafts such as of invitations and souvenirs. In running a business, especially in order processing, each salesperson is tasked with interacting with the customers. This causes customers to have a different contact numbers regarding UD. XYZ. Matter of separate information, it becomes difficult to track orders. The method used in charge on designing information system is the V-Shaped Model. The VShaped Model method is one of the SDLC (System Development Life Cycle) models. Meanwhile, the testing method used is White box testing and User Experience Questionnaire (UEQ). Based on the research that has been done, white box testing the results are 98.5%. On the other hand, the User Experience Questionnaire (UEQ) based on 6 UEQ scales resulted in 5 categories above the average and 1 category with good scores.
Game RPG Berbasis Android untuk Mendorong Pengguna Berolahraga
With the lockdown period due to Covid-19, maintaining stamina and body health is a priority. People are advised to reduce activities outside the home and work from home. Working from home is often done behind a desk, and after work people do activities to relieve boredom such as watching television, playing games, and other sedentary activities that cause them to be unhealthy. Playing games on a smartphone is becoming more popular because they are easily accessible and only require a smartphone that has many features already on it. This thesis research aims to create a game application on a smartphone to overcome this problem. This RPG game application, is hoped to increase people's interest in exercising by playing on a smartphone that detects motion using the accelerometer sensor and calculates calorie burned using the MET formula. The results of testing the game show that 40% of respondents are more interested in exercising. In addition, the calculation of calories is quite accurate compared to other tools. And it is also proven that this game can meet the recommended daily exercise.
Aplikasi Self Management untuk Mencatat Jadwal Kegiatan Dengan Speech to Text Menggunakan Google API Berbasis Android
Self Management is a person's ability to control himself against an action. But there are still many people who underestimate this, especially in terms of scheduling activities. People tend to only rely on memory and organize activities incorrectly. This makes people think a lot and tend to forget things. Thus, a scheduler app can be a perfect solution for busy people. This paper was made to create an application for scheduling using speech to text. The features of the application are calendars, to-do lists, notes, and speech to text. Speech to text using the Google Speech API. Calendar connects directly to Google Calendar using the Google Calendar API. Other features are stored in a local database in the form of SQLite. The application was tested by measuring the speed of making a schedule using a stopwatch. The result is that the schedule can be made in 10.426 seconds using speech to text. By using the Google Speech API in making the schedule, the accuracy obtained reaches 96.45%.
Sistem Pendukung Keputusan Pemberian Kredit berdasarkan Klasifikasi Kelancaran Pembayaran Kredit Menggunakan Metode VIKOR pada Bank XYZ
Banks must carry out complex assessments before being able to determine who is the most eligible prospective debtor who can be given a loan. This is due to limited funds and the risk of bad credit cases. The limited manpower and manual processes cause the whole process of lending at XYZ Bank to be prone to human error and become inefficient. As a solution for XYZ Bank to overcome existing problems, a credit decision support system is needed that can assist XYZ Bank in selecting and determining prospective debtors who can be given loans. Therefore, in this study, the KNearest Neighbor method was used to assist XYZ Bank in predicting the smoothness of credit payments of a prospective debtor. Then, this research continues with ranking using the VIKOR method to determine who is the most ideal debtor candidate to be given a loan. Based on the results of the classification test using both training data and new data, the highest accuracy is obtained at 100% for each type of loan. Based on the results of the ranking test, the accuracy of the business loans ranking is 83.33%, the accuracy of the consumer loans ranking is 80.33%, and the accuracy of the various-purpose loans ranking is 70%. The results of the questionnaire evaluation in system testing conducted by 6 respondents assessed that the application design was 76.67% good, the application functionality was 86.67% good, the ease of use of the application was 83.33% good, the application answered the needs was 86.67% good, and the overall application was 90% good.
Aplikasi Channel Management dan Point of Sales pada perusahaan retail PT. XYZ dengan menggunakan metode Cross-channel dan Market Basket Analysis
PT XYZ is a company engaged in the retail and distribution of baby equipment located in Surabaya. Generally, the company has many stores ranging from physical stores and online stores. The problem faced at this time is that there is no system that can connect the company's internal systems including the cashier system, warehouse system, sales calculation system with the existing system in online stores such as in this case the Shopee system. To answer these problems, PT XYZ requires a website-based channel management system so that it can be integrated both on mobile and desktop. It is hoped that by using this technology, it can help companies improve the performance and sales performance of stores both physical stores and online stores. An integrated Multichannel Management System and Point of Sales Application can record every sale, stock management practically and efficiently so that when a stock transaction occurs it will always be synchronized along with transaction data from between online stores and offline stores.
Sistem Pakar Diagnosa Penyakit Ikan Arwana dengan Menentukan Tingkat Kualitas Air Menggunakan Forward Chaining dan Simple Additive Weighting
arwana fish always has its own charm for the people of Indonesia, as well as foreign countries. But every living thing must have been stricken with disease, including the arwana fish itself. Diseases in arwana are often not well identified by hobbyists and beginners because there are many parameters that must be considered. One of the problems in identifying arwana disease is the problem of the suitability of water parameters with arwana fish. This expert system is equipped with Forward Chaining and Simple Additive Weighting methods. Forward Chaining allows the expert system to ask only the questions it needs. Simple Additive Weighting is used to determine the level of suitability of parameters in arwana fish. This method allows us to determine whether the water quality is suitable for the arwana fish by performing calculations based on the weight of the water parameters quickly. Tests were carried out by 2 experts on 20 arwana fish. The test results on the expert system for diagnosing arwana fish disease obtained an accuracy level of conformity with the expert with an accuracy value of 95%.
Deteksi Rompi dan Helm Keselamatan Menggunakan Metode YOLO dan CNN
Construction workers face a high risk of injury and are prone to accidents while performing their duties. Several factors increase the chance of accidents, including open and heated environmental conditions, building heights, sharp objects, and others. The use of personal protective equipment (PPE) is essential to anticipate or reduce the risk of accidents that may occur. However, it is not uncommon for construction workers to forget or purposefully disregard personal protective equipment. To address these problems, a system capable of detecting personal protective equipment for construction workers is required. This study used the You Only Look Once (YOLO) method to detect the head and body parts of the inputted image. The detected body parts were then cut and processed using the Convolutional Neural Network (CNN) method with the ResNet50 model for classification. The training process with the ResNet50 model was modified on hyperparameters including learning rate, epoch, dense layer, dropout layer, data augmentation, and freeze layer to compare its performance with the model before modification. The results showed that the YOLO model has a very high level of detection speed with good accuracy. Meanwhile, the modified CNN model performed well with an average accuracy value of 96%
Sistem Pakar Diagnosa Penyakit pada Anjing Menggunakan Metode Forward Chaining dan Certainty Factor
Dogs' diseases have different treatments which affect the owner on how to treat them. If the treatment given is not proper, even a minor disease could be fatal, which will be very detrimental to the dog owner and also the dog itself. The problem that the author wants to address is by utilizing a website that functions to diagnose common dog disease by using an expert system based on the forward chaining method and the certainty factor method to diagnose if there are any symptoms in dogs. Tests were also carried out on a collection of interview data and also from the expert in the form of disease symptoms and the program that was made are able to diagnose dog disease with the results of the method test being able to achieve an accuracy value of 80%.
Adaptive Sparse Transformer untuk Meningkatkan ROUGE-1 Score pada Text Summarization Scientific Paper
Technology advancement and internet causes lots of information that can be accessed at any time. Journal article is one of such many information that’s available that requires time to read thereof in need of automatic summary. Automatic Text Summarization (ATS) basically a process of making a new text that’s smaller than the original text without removing the meanings from the entire input text. The process of making automatic text summarization can be done in extractive and abstractive way. A summary that was made by an extractive method only able to generate a summary with a word that’s included in the original text, whereas summary that was made by an abstractive method can generate a summary that include word that does not exist in the original text. In the previous research in abstractive summarization is found is not optimal thereof need an improvement. The method used in this research is an abstractive summarization with Adaptive Sparse Transformer. Things that will be done in this research are scraping dataset arxiv machine learning, making the dataset, processing the data and trials on hyperparameter configuration in the model to see ROUGE-1 precision performance. The dataset used is Arxiv Scientific Paper dataset and Arxiv Scientific Paper+Machine Learning dataset. The results of this research showed that the method used capable to compete with state of the art methods with average R-1 precision score of 39.4 for Arxiv Scientific Paper+MachineLearning and 42.5 for Arxiv Scientific Paper.
Sistem Rekomendasi Pembelian Laptop dengan K-Nearest Neighbor (KNN)
Over a decade, the number of people who needs a laptop for their job is increased because of its slim design and internal battery that makes it easier to carry anywhere, if compare to an old-fashioned computer. However, the choices of laptop specifications are various, namely the laptop model, brand of the processor, the speed of processor, size of the screen, RAM, price, etc. Not all people knows the indicator of choosing the laptop that fit to their wants and needs. In this study, the process of recommendation system is used a methods namely K-Nearest Neighbor Collaborative Filtering. This method will estimate the distance with Euclidean formula between the users' criteria and the survey. The closest distance is considered as the recommendation. The data testing is done through counting the accuration based on the recommendation's result which is given to the user. The survey is used for counting the total of valid recommendation. he results of this study using a satisfaction survey that has been surveyed to 10 laptop shop employees. Based on the survey results, average accuracy of testing the recommendation results is 84%. Testing the appearance of the website is also quite good because most users give a value or rating of 4 or 5. Based on the testing results, it can be concluded that the appearance of the website and the results of recommendations with the K-Nearest Neighbor method is pretty good because they are in accordance with the criteria and needs of users.
Prediksi Kebutuhan Darah Menggunakan Metode ARIMA Dengan Mempertimbangkan Faktor Deterioration
Blood has various uses that are very important for the human body. However, blood can only be donated in limited quantities because it can only be produced by humans. This blood donation activity is organized by the Blood Transfusion Unit (UTD), one of which is UTD PMI Surabaya. UTD PMI Surabaya also produces and stores blood products and distributes them to hospitals or directly to patients who need blood. Due to the uncertain amount of blood demand, UTD PMI Surabaya needs to make predictions in order to meet the blood needs. But blood has an expiry that also needs to be considered. Meanwhile, the blood demand prediction system still uses human estimates. Therefore, an information system is needed that can assist in predicting the need for blood by considering the expiration date of the blood. The application made in this research is a web application that can assist in making predictions using the ARIMA method. Then a calculation will be carried out by considering the deterioration of the blood to determine the need for blood in the next month. Based on the test results, the application is able to predict blood needs. The ARIMA model used to predict WB blood components is ARIMA (7,0,6) with a RMSE of 58,91. While the ARIMA model used to predict the TC blood component is ARIMA (5,0,6) with a RMSE of 272,46.
Sistem Pakar Diagnosa Kerusakan Pada Mobil Toyota Innova Dengan Metode Backward Chaining Dan Certainity Factor
Car is one of the transportation that used commonly by human. Toyota Innova is one of the most favorite family car in Indonesia. Toyota Innova has a lot of type and variations that need to be handled. There is Manual transmission and Automatic Transmission. Damage to car cannot be taken so easily, Not only big damage that can cause breakdown. But small problems or damage to car can cause breakdown or failure, Small damage is need to handled too as important as big damage so it would not become fatal damage. Diagnostics on the car for people who don't really understand cars can be really confusing and the number of repair shops that are not honest in diagnosing damage will cause losses for car owners. If in an urgent situation this system can be used to find out what damage has occurred and make it possible to check and repair the damage to the car that occurred. This Expert System for Damage Diagnosis on Toyota Innova is using Forward Chaining and Certainty Factor as it’s method. Backward Chaining on this expert system is for collecting symptoms and facts that come into some conclusions so users don't have to answer all the questions. And the usage of Certainty Factor on this system to show the percentage of system belief on the diagnosis. So user can trust on the result of diagnose. The results of tests that have been carried out 20 times from tests by experts, There is 19 results that suitable with expert opinion. There is 1 result that is not suitable with expert opinion because of the inaccuracy of the CF percentage. As of that result user can still look for the solution in the damage encyclopedia. In this test, the percentage for detecting damage to the Toyota Innova car using the Backward Chaining method and Certainty Factor is 95% in accordance with expert opinion.
Algoritma Goal Programming untuk Driver Assignmentpada Simulasi Taksi Online
Taxi is one of the most common means of public transportation. Assignment of drivers to passengers in online taxi can be done by of ering passenger orders to all drivers closest to the pick-up location. This method has high time ef iciency. However, this causes an increase in the cancellation rate because drivers don't have enough time to view order details, just as long as they accept orders. This can lead to a decrease in the level of passenger satisfaction and online taxi revenue. Therefore, other factors such as driver rating, driver order cancellation rate, number of orderscompleted by drivers are important to consider in the assignment process to produce an ef icient assignment. The process of assigning drivers and passengers will be carriedout using the Goal Programming method because this methodissuitable for problems in decision making that involve morethanone goal (multi-objectives). The results showed that Goal Programming resultedinthehighest total calculation time. In addition, the average waitingtime for passengers and pick-up distance are the lowest. TheHungarian Algorithm method has a faster calculationtimecompared to the Goal Programming method, however, thenumber of assignment is lower. In addition, the average waitingtime for passengers and their pick-up distances is higher. TheRandom Assignment method has the fastest calculation timeandthe highest assignment success rate. However, the averagewaiting time for passengers and the distance to pick themupisfarabove the two comparison methods. The addition of factors otherthan time and pick-up distance in a low percentage can af ect theaverage value of these factors for the better. But, the averagepick-up time and distance is increasing.
Form Evaluasi Online Mata Kuliah Pra Skripsi Dan Skripsi Berbasis Android
In order to support the vision of "Green Campus" implemented by Petra Christian University Surabaya as well as to accommodate the evaluation interests of courses in the new curriculum, namely pre-thesis and thesis. At the evaluation stage of the course, it involves many parties, so to digitize all documents and facilitate coordination, an application is needed to assist the entry process and produce the required reports. So far, the evaluation process that has occurred is quite long and takes a lot of time, namely when evaluating the Pre-Thesis to Thesis. As well as seeing the increasing number of Petra students every year, the coordinating lecturers and supervisors on Pre Thesis and Thesis will be more and more difficult in handling the evaluation. Therefore, this thesis creates an "Online Evaluation Form for Pre-thesis and Thesis courses based on Android" which is an application on an Android-based smartphone that aims to facilitate the coordination of lecturers and supervisors in evaluating these courses. By making this application, it will be easier for the lecturers to fill in the scores and evaluation of the Pre-thesis and Thesis reports without taking much time, and the data created can be more accurate and faster. So that the delivery of grades to students becomes shorter.
Sistem Otomasi Rute Order Picking Pada Gudang dengan Metode Simulated Annealing
Order Picking is a process to make a selection from products and picking them up from the place that products are stored and then sort the products out to fulfill the customer orders. Order picking process is the most expensive activity in the warehouse. The reason is order picking needs a lot of workforce and if order picking done manually it will cost as much as 55 % of the total cost of the warehouse. That’s why order picking is the correct part to be optimize to make warehouse become more effective and efficient. In this thesis, a web based application designed to solve all the problems above, which includes showing the shortest route to be pick for orders picking with simulated annealing method. Other than that, the application will be included with a hardware named RFID reader which can detect product placement and pickup from the shelf. The result of this thesis showed that simulated annealing algorithm able to reduce the range that are needed to order picking as much as 51.57058354 % for 100 data, 35.56569879 % for 500 data and 28.18222784% for 1000 data with fixed parameters. For the RFID reader it have the accuracy of 40% for reading products on the shelf. This is because the signals from tags clashing with each other which make the reader unable to read all of them.
Implementasi Text Summarization pada Review Aplikasi Super di Google Play Store Menggunakan Metode Maximum Marginal Relevance
Super App is an app for reseller agents who sell and distribute basic necessities in tier 2, 3 cities and rural Indonesia. The Super app has been downloaded by around 50,000 users on the Play Store. Various reviews or reviews have also been given by users who have downloaded the Super application. Whether we realize it or not, customer opinions / reviews given on Google play, a little or a lot, will have an influence on potential customers. Based on the problems that occur, this research will implement a text summarization program on Super App reviews with the implementation of the MMR and TF-IDF methods, so that from the large number of existing reviews, only a few important sentences can be extracted, so that the conclusion making process will become easier. The results of the research using the MMR method produced an average precision value of 40.4% in 3 trials, and with the highest precision value of 60.4% in the experiment using the parameter value = 0.7
Rancang Bangun Aplikasi Panggil Tukang Berbasis Android di Daerah Surabaya
Nowadays, many people are using android applications in their daily lives. Many kind of applications have been made to make everyday jobs and daily routines become simpler and easier. Looking for AC Service and home repairman is one of them. In Surabaya, looking for service providers is stil use with manual search which is asking to their neighboor. But the problem is, when the people just move in the new neighborhood, and just barely know anyone around, or urgently need to repair your air conditioner problem, and they just don't know whom to ask for help. Because of the problem, Writer make an application Panggil Tukang for helping people find good technicians especially people who lives in Surabaya. The features available on this application will be help the user to find the right technician. The user can get the interesting experience to find a good technicians in this application. Features such as price negotiation, payment methods, and chat will help the user to communicate with the service provider to find the best solution for them. This application simply make life much easier for people who are looking for the right technician's help. On the other hand, this application also provide help for all the technicians' service provider who are looking for people who needs their service. The application and website were built base on PHP language code and Kotlin. While the database we are using to make this application is Firebase.
Aplikasi Sistem Pengontrolan Turtle Tub Untuk Pemeliharaan Kura-Kura Red Belly Nelsoni Dengan Arduino
Having turtles, especially Red Belly Nelsoni turtle is very common, but usually the owner don’t really know how to properly taking care of their turtles, according to the parameters needed in turtle maintenance. The problem that the author wants to solve is by utilizing Blynk application and Internet of Things tools that has a function to control, monitor and maintain all parameters that needed in turtle maintenance, so that the owner of the turtle can more easily taking care of the turtle in the turtle tub. The test was carried out by giving 2 turtle tubs containing Red Belly Nelsoni turtles to 2 volunteers who carried out the turtle care and maintenance in different ways. From the result of the test carried out, the application has been able to help the volunteers in taking care of the turtles according to the parameter aspects that needed in turtle maintenance.
Penerapan Artificial Neural Network dan Rule Based Classifier untuk Mengklasifikasikan Pendonor Darah Potensial pada Sistem Broadcast Pendonor
One of UTD PMI Surabaya’s task is to provide safe and quality blood when blood is needed in an emergency. The availability of blood at UTD PMI Surabaya can be erratic, because it depends on the number of donors that fluctuates and the storage time of blood is not long. Therefore, UTD PMI Surabaya needs a system to invite potential donors to meet blood needs when needed in an emergency, by minimizing blood wasted. The classification model and the creation of a recommendation system will produce a list containing donors who have been sorted by priority. Testing was carried out by dividing the data according to the conditions of the data collection environment (before the pandemic, during the pandemic and a combination of before and during the COVID-19 pandemic). The highest MRR value was obtained from the ANN model made from a combined data of 90% classification results using RBC and fake data. The accuracy value obtained from the model is 91.13% for training and 91.83% for testing. The resulting MRR value is 8.07 x 10-4 .
Pewarnaan Otomatis Sketsa Gambar Menggunakan Metode Conditional GAN Untuk Mempercepat Proses Pewarnaan
Anime is a Japanese animation that consists of many frames of images. Images that used to make an anime can be made using hand-drawn or using digital-drawn. It takes a lot of time to make an anime. In making anime for 1 second, it needs a total of 24 frames, this is why it takes a lot of time to make anime and also takes a lot of money. Each image also needs to be colored, this is also why making anime takes so much time. The method used in this research is GAN (Generative Adversarial Network) or should we call C-GAN (Conditional Generative Adversarial Network) to make coloring anime sketches easier. Dataset that is used in this research is a pair of sketch images and sketch images that have already been colored.
Aplikasi Penerjemah Kegiatan Seminar Menjadi Video Bahasa Isyarat BISINDO Dengan Speech To Text
Information at this time is very much needed to increase our knowledge. However, this delivery can be hindered by several conditions such as the inability to hear the deaf community. Based on data from the Data and Information Center of the Ministry of Health of the Republic of Indonesia in 2019, 7.09% of the Indonesian population is deaf. In addition, the delivery of information at the seminar can be hindered by noise and participants sitting far from the speaker will have difficulty hearing the speaker's voice. In this study, we will use Speech-To-Text on the Android application which aims to help translate information in the form of voice delivered as at a seminar into text and will be converted into BISINDO sign language video. The results of testing the use of the Speech-To-Text feature in the application that has been made show that it is able to accommodate approximately 100 words in 1 minute at a time when the speaker speaks without any pause. The Speech-To-Text feature used takes approximately 2 seconds to translate the received voice and the time lag required by the speaker device to the participant's device takes approximately 3-5 seconds after using 5 different internet speeds. For the accuracy of the Speech-To-Text feature that was tested using 3 narrations read by 4 different people, the accuracy of the Speech-To-Text feature has an accuracy of above 80% in general, although there is an accuracy that is below 80% due to the ambiguity of the pronunciation.
Penerapan Metode Multiplicative Decomposition dan Autoregressive Integrated Moving Average dalam Prediksi Penjualan Produk Manufaktur pada PT. XYZ
PT. XYZ is a company engaged in the manufacture of drinking water (AMDK). PT. XYZ conducts product sales transactions in large quantities every day, so the large number of existing sales transactions will certainly affect the daily necessities inventory in the company. The problem that occurs in the company is regarding overstock and understock. Based on the problems that occur, the researchers will apply the Multiplicative Decomposition and Autoregressive Integrated Moving Average (ARIMA) methods to process a large number of sales-data which is used as information. So, the purpose of this study is to implement the Multiplicative Decomposition and Autoregressive Integrated Moving Average (ARIMA) methods to predict sales of mineral water goods at PT. XYZ. The test system will use the Mean Absolute Percentage Error (MAPE) method.
Prototype Website Monitoring Parameter Energi Listrik pada Gedung A, B, C, D, & I di UK PETRA
In this modern era, technology is developing very quickly which can facilitate human needs. The fast developed technology need more energy resources such as electricity. This thesis is intended to display electrical energy parameter in the Petra Christian Building via website to show the energy consumption patterns. The data processing method is carried out using PHP on the website. Predictive data analysis using data from Petra Christian University Building which is sent via Gateway to WiFi/LAN. The result of the thesis shows that, the result of the data pattern can help provide an understanding of the pattern of electricity consumption in each building. The regression prediction result has a slope of about -0.75% from the original data. The survey result has an overall rating of 4,375 out of 5 which indicates that users are satisfied with this website.
Sistem Informasi dan Rekomendasi Kegiatan Kemahasiswaan Universitas Menggunakan Content-Based Filtering pada Web App RE*ACH sebagai Pusat Informasi Kegiatan Kemahasiswaan Universitas untuk Mahasiswa
In living the college life in Petra Christian University, each college students have his own problems. One of them is the problem of meeting the requirement for Student Activity Credit Unit (SKKK). There are also various reasons for each student to have this kind of problem. However, getting the opportunity to pass the selection as a committee member or participate in some student activities is one of the reason that the students complain most. Therefore, an information system and recommendation system for student activities must be created in a centralized platform that can be accessed by all Petra Christian University students. In helping the information system to be more precise in providing information, recommended system is added to the system so that the information related to the users can be addressed correctly to the users who really need it. In making the recommendation system, the ContentBased method with cosine similarity is used because the method tends to recommend products based to each user’s individual preferences. Users of RE*ACH application are all Petra Christian University students, so the dataset will consists of personal data from all Petra Christian University registered in the application.