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Jurnal Infra
Published by Universitas Kristen Petra Surabaya
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Core Subject : Science,
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Articles 79 Documents
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Search results for , issue "Vol 10, No 2 (2022)" : 79 Documents clear
Pengamatan IP Cycling Pada VPN Menggunakan GRC Fingerprints dan DNSLeakTest R. Agastya Ardhitaputera Ramadhan; Justinus Andjarwirawan; Agustinus Noertjahyana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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.
Website Human Resource Information System Dengan Fitur Pengukuran Efektivitas Kinerja Karyawan Pada PT. Deus Digital Transformasi Universal Alvin Putra Wong; Alexander Setiawan; Lily Puspa Dewi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

PT. Deus Digital Transformasi Universal is a service company that focuses on website creation, social media management, and client product marketing. So far, the management of human resources is still mostly done manually, so it is very possible for recording errors or other errors that make the data inaccurate. PT. Deus Digital Transformasi Universal also plans to open several branches outside the Surabaya area which causes the company's need for a Human Resources Information System to be very strong and cannot be avoided anymore. HRIS is equipped with a decision support feature using the Analytical Hierarchy Process method that can display suggestions and actions for evaluating employee performance results. In this study, an HRIS was designed which has several modules, namely the Master module, recruitment module, project module, violation module, daily work module, performance module, and payroll module. To support decisions the system uses the Analytical Hierarchy Process used in the calculation process, and ranking of employee performance. The system is made based on a website using the laravel PHP framework, javascript, HTML, and MySQL database. The result of this research is a system that can help HRD in all matters of human resource management, and help company directors to be able to unify the work of employees, and their performance in real-time, and objectively.
Adaptive Sparse Transformer untuk Meningkatkan ROUGE-1 Score pada Text Summarization Scientific Paper Andrew Firman Saputra; Liliana Liliana; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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 Deteksi Reputasi Akun Seller Pada Steam Community Menggunakan Metode Klasifikasi Support Vector Machine Nalom Aholiab Sinaga; Alexander Setiawan; Agustinus Noertjahyana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Playing games is an activity that is often done by many people from various ages, some just fill their free time, some make the game a job or a place to make money. The online gaming industry is currently an industry with a large value, which is $21.1 million in 2021. The Steam Community is an online game platform that provides nearly 30000 games. In this platform, you can not only play games but can make transactions with fellow Steam Community users. The transactions made include selling games, ingame accessories, steam wallets and artwork. The problem faced is, payment transactions are carried out outside the Steam platform itself, on the other hand Steam users do not know each other yet, so the seller's account reputation needs to be checked. The checks carried out are through analyzing the sentiment on the comments of the account in question. Analyzing these comments is done by using the Support Vector Machine method to classify the purpose and sentiment of the comments. The results of this research will be presented in the form of a website where users of this website-based application will enter SteamID into the system, and the system will perform sentiment analysis on comments, then the system displays the results of the analysis in the form of data presentations, in the form of the number of comments based on existing sentiments. And the system will also display all comments on the profile along with the predictions for their comments. Based on research that has been carried out using the Support Vector Machine method, the model with the best accuracy is 91% for classification of comments purposes, and 86% for sentiment classification. Based on a survey of this application, 76% of respondents claimed to be helped by this application, and 66% of respondents were willing to recommend this application to their friends.
Sistem Optimalisasi Rute Model Capacitated Vehicle Routing Problem With Time Windows Menggunakan Algoritma Metaheuristic Particle Swarm Optimization pada Perusahaan Kantong Plastik HDPE PT XYZ Jason Jason; Silvia Rostianingsih; Andreas Handojo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Technology has been one of the key factors behind industrial revolution. Companies are now required to use technological assistance and data processing to produce faster and more efficient business processes. This is also the case with Company XYZ. Company XYZ is an HDPE plastic manufacturer domiciled in Surabaya. Currently, the company is trying to handle the increasing frequency of shipments that exist in the company. Due to the increasing frequency of shipments, the company is often overwhelmed in handling its shipments because there is no system that can quickly determine the shipping route for the company. Moreover, there are other route determining factors such as shipment weight, truck capacity, and special delivery hour requests that add to the complexity of the route to be calculated manually. So a system is needed that is able to provide route recommendations quickly. This route optimization system is designed using the PHP programming language and the Bootstrap frontend framework to support the system UI Design. The database used is mySQL database. The system will be created in 2 modules, namely a module for the admin and a module for the driver. For this system to work, firstly the system will run the KMeans Cluster function from the database to cluster all customers in the company. This cluster is one of the factors determining the fitness value in the Particle Swarm Optimization algorithm. After the order data is obtained, the system will use the PSO algorithm to determine the delivery agenda for each truck. The determining factors of PSO include customer location, priority hours of customer requests, order weight, and loading capacity of different types trucks. After obtaining the delivery table of each truck, the system will use the help of Google Waypoints API to determine the routing order from each truck. The final result of this system is a delivery route optimization system that is able to provide route selection recommendations for each truck in the company. The system is also able to sort shipments with various shipping priority restrictions. From the test results, the PSO algorithm in the system is able to produce routes with less total distance traveled and less travel duration than the routes generated manually by the employees in the company.
Pengurangan Sampah Makanan dalam Bisnis Kuliner Menggunakan Konsep E-Marketplace pada Aplikasi Mobile Jessica Clarensia Suko; Djoni Haryadi Setiabudi; Justinus Andjarwirawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Food waste has a lot of negative impact on various aspects. The two biggest contributor of food waste are domestic food waste and food service food waste that come from foods that are unsold. There are a few mobile applications that help reducing food waste on a domestic level using food sharing between individuals, but it didn’t work effectively due to lack of trust. To resolve that, a mobile application with an e-marketplace concept will be created to reduce food waste that focuses on culinary businesses (food services) level. With e-marketplace concept, the individual who has the role to give the food to the consumers will be culinary businesses that used to make foods on day to day basis and have their own business reputation, so that hopefully it will increase the trust of the consumers on receiving leftover foods (unsold foods). The application was tested on two culinary businesses in Surabaya with the first culinary business being a small culinary business and not very well known by the public, while the second culinary business is a large and very well-known culinary business among the public. The result shows that the application can reduce food waste as much as 5% on the first culinary business, but the application has failed to reduce the food waste of the second culinary business. On the other hand, the application managed to increase the trust of the consumers on buying and accepting the leftover foods although there is culinary business that the consumers didn’t know before.
Penerapan Linguistic Inquiry and Word Count dan Random Forest Dalam Klasifikasi Personality Berdasarkan Data Posting Twitter Sehingga Dapat Ditentukan Gaya Belajar yang Sesuai Cristine Ferlly Wiyanto; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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
Aplikasi Omni-channel untuk Pengaturan Multi-channel Order Management di Toko Kyuuden Katherine Putri Sutjiadi; Yulia Yulia; Krisna Wahyudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Kyuuden store is an online store that provides variety of electronics products especially games related. Kyuuden store sold in marketplace platform such as Shopee, Tokopedia, Bukalapak, OLX, and Blibli. The store currently storage or collecting data manually with Ms. Excel while there are a lot of data to manage which made the data management much more difficult. Not just managing data, Kyuuden store make sales in more than one marketplace platform which makes it also difficult and wasting more time to managing it. Based on those problems, it needed an omni-channel application that integrates data from multiple channels and can manage computerized all the business activity data. The integrated channels are offline channel, Shopee, and Tokopedia. This application programmed with PHP framework Codeigniter 3 and database phpmyadmin MySQL. This application has two access group such as owner and administrator. Final result of this research and application is that this application can integrating data, managing data, dan synchronizing data within all channels either online or offline. From the questionnaire result with the respondent, 75% user response that overall application could help the business process of Kyuuden store.
Sistem Pendukung Keputusan Pemberian Kredit berdasarkan Klasifikasi Kelancaran Pembayaran Kredit Menggunakan Metode VIKOR pada Bank XYZ Daniel Hartono; Leo Willyanto Santoso; Silvia Rostianingsih
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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.
Sistem Pakar Diagnosa Penyakit Ikan Arwana dengan Menentukan Tingkat Kualitas Air Menggunakan Forward Chaining dan Simple Additive Weighting Kevin Christian; Djoni Haryadi Setiabudi; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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%.

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