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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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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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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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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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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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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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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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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%.

Sales Management dalam Pengukuran Key Performance Indicator Dengan Menggunakan Metode C4.5 pada CV.X Feronica Natalia Rivaldi; Silvia Rostianingsih; Yulia Yulia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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CV.X is a wholesaler company that sells daily necessities. CV.X holds thousands of brands for the types of products sold. Currently, the company has a system that is still limited to desktop applications so that data is still processed manually before being entered into desktop applications. This can cause non-optimal performance in maximizing each salesperson as well as the human error factor that appears. In addition, the company also needs a system that can organize existing business processes, especially the sales side. The company also limited in terms of available reports and from the absence of an evaluation platform to analyze the performance of Key Performance Indicators from working salespersons. This causes the company to have no feedback to find out the measurements on the salesperson that affect its sales. The sales management system is made using a website base using the Codeigniter framework and a mobile application using the Flutter framework. This application can manage business processes related to sales more integrated. The C4.5 method is also used to overcome the grouping of available attributes. With this method, it helps to analyze the attributes with the greatest influence in influencing the achievement of performance in the salesperson. The end result of this program is the integration of business processes, especially sales, such as placing orders, shipping, submitting returns, sending and receiving returns and other processes. Users can also access existing reports in the form of table data and graphic data.

Sistem Informasi dan Rekomendasi Kegiatan Kemahasiswaan Universitas Menggunakan Content-Based Filtering pada Web App RE*ACH sebagai Pusat Informasi Kegiatan Kemahasiswaan Universitas untuk Mahasiswa Misael Rithe Setio; Henry Novianus Palit; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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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.

Penyuaraan Pesan Teks Media Sosial Pada Perangkat Mobile Menggunakan Text To Speech Michael Alexander Rustan; Anita Nathania Purbowo; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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The use of smartphones as a communication tool will increase along with the increase of smartphone users. Based on the data obtained, in early 2021 there are around 167 million smartphone users in Indonesia. The use of smartphone as a communication tool to send messages in its use can also start to annoy people when they are doing activities that require concentration, for example, such as driving. In 2017, there were about 15,341 cases of accidents in America caused by drivers using smartphone. To overcome this problem, the text to speech feature will be used to voicing the incoming messages so smartphone users do not need to open their smartphone to find out the sender and the contents of the message. The results of the tests that carried out on the usage on text to speech feature showed that the system can voiced the incoming messages well. For messages that have abbreviated words, the text to speech feature cannot voiced them properly. As for the tests carried out on the feature to detect the message, the system can detect some message data such as the package name of the application, the sender's name, and also the message content properly. For messages received through group chat, the detection results from the line application, and the whatsapp application have problems, so there are obstacles in the process of voicing group chat messages on the line application and whatsapp applications.

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Home Page

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Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota surabaya,

Jawa timur

INDONESIA