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Silvia Rostianingsih
Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
Computer Science & IT

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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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Abstract

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 Pakar Diagnosa Penyakit pada Anjing Menggunakan Metode Forward Chaining dan Certainty Factor Kevin Shaquille Limanuel; Leo Willyanto Santoso; Silvia Rostianingsih
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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%.
Aplikasi Marketplace Vendor Lamaran dan Pernikahan berbasis Android Yansen Tri Utomo; Silvia Rostianingsih; Leo Willyanto Santoso
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

In the world of marriage or application, it is something that takes quite a long time, especially in choosing vendors, venues, and WO. With the Mywedding mobile application, it is made to assist in choosing any vendors that can be used for their wedding or application as well as provide the best recommendations according to the criteria of everyone who will prepare for a wedding. Content based filtering method used to collect data and assess suitable vendors to be recommended by the system to users. Based on the results of the tests carried out, the content-based filtering method succeeded in providing recommendations according to the wishes of the user so that they can find out which vendor can be used, although sometimes the user profile needed is more specific to be more accurate. which can be used for their wedding or proposal and provide the best recommendations that match the criteria of everyone who will prepare for a wedding. Content based filtering method used to collect data and assess suitable vendors to be recommended by the system to users.
Penerapan Metode KNN-Regresi dan Multiplicative Decomposition untuk Prediksi Data Penjualan pada Supermarket X Calvin Christopher Kurniawan; Silvia Rostianingsih; Leo Willyanto Santoso
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Supermarket X is one of the supermarkets in West Nusa Tenggara that needs a way to predict sales in the future. This prediction is needed by Supermarket X to estimate the purchase plan because so far there have been frequent stockouts or oversupply which have caused losses to the company. Based on the problems that occur, this study applies the KNN Regression and Multiplicative Decomposition methods in predicting Supermarket X sales so that supermarket managers can design a strategy to make sales in the future. The results show that predictions based on divisions, departments, categories, sub categories, and products have a smaller average error rate when using the Multiplicative Decomposition method with RMSE = 492.89 and MAPE = 0.29, while the KNN Regression method has RMSE= 757.77 and MAPE= 0.36
Pengaruh Feature Selection terhadap Kinerja C5.0, XGBoost, dan Random Forest dalam Mengklasifikasikan Website Phishing Michael Jonathan; Silvia Rostianingsih; Henry Novianus Palit
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

With the increase in internet users, especially websites, it provides an opportunity for phishing actors to obtain or steal personal information from users. On each website there will be a lot of information that will be used as a feature, this feature will be used to classify phishing websites. Features will be divided into 3, namely feature url, content feature, and external feature. In this study, three methods will be used, namely C5.0, XGBoost, and Random Forest. The three methods will be tested for their performance to find the best method for classifying phishing websites. In addition, this research will also utilize feature selection with the aim of removing features that have no effect so that training time can be shortened. Based on the test results obtained, it shows that C5.0 is able to provide accuracy, precision, recall, & f1-score values with an average of 93.5%, XGBoost with an average of 96.6%, and Random Forest with an average of 95.7 %. The use of feature selection in the three algorithms also shows that training time can be shortened by an average of about 3.53 times faster by using only 15 feature importance. However, with the use of feature selection, the performance on accuracy, precision, recall, & f1- score values decreased slightly even though the given decrease was not significant or had no major impact on the classification process.
Aplikasi Sistem Pendukung Keputusan Perekrutan Karywan berdasarkan Hasil Tes Rekrutmen dengan Metode Fuzzy AHP dan Profile Matching pada Konsultan Manajemen Sumberdaya Manusia CV.X Josia Christian; Silvia Rostianingsih; Yulia Yulia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

CV X is a human resource management consulting company serving personnel management services such as recruitment, assessment, making company policies, and making employment agreements. So far, all business processes are still done manually including the employee recruitment process. Based on the existing problems, this research will create a Decision Support System for Employee Recruitment based on Recruitment Test Results with Fuzzy AHP and Profile Matching Methods. The system is expected to optimize the efficiency of the recruitment process at CV X Human Resource Management Consultant. The results show that the system can help calculate candidate rankings with an accuracy of 83.975% when compared to manual ranking results. In addition, the system can also help reduce the influence of assessor subjectivity on ranking results.
Penerapan SVM untuk Klasifikasi Sentimen pada Review Comment Berbahasa Indonesia di Online Shop Yoshua Refo; Silvia Rostianingsih; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

With so many users accessing online shops, comments are an important aspect when shopping. Buyers can provide comments about the goods or thing that have been purchased, both negative comments and positive comments. By collecting various kinds of comments, the data can be used to classify comments. This research will use the Support Vector Machine (SVM) algorithm which is considered the right method for text classification. The method will be tested for its performance, seen from how good and accurate the method used in classifying comments is. In addition, this research also uses kernels, namely Linear kernels, Radial Basis Function (RBF) kernels, and Polynomial kernels as test scenarios. Based on the test results shown, SVM is a good method in classifying text. SVM classifies text that has gone through the preprocessing stage with an accuracy value of 88% on the RBF kernel, 87% on the linear kernel, and 87% on the polynomial kernel. The accuracy value in the aspect classification itself is 78% on the RBF kernel, 78% on the Linear kernel and 74% on the Polynomial kernel.
Form Evaluasi Online Mata Kuliah Pra Skripsi Dan Skripsi Berbasis Android Stephen Cornelius Hertanto; Silvia Rostianingsih; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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.
Penerapan Metode Multiplicative Decomposition dan Autoregressive Integrated Moving Average dalam Prediksi Penjualan Produk Manufaktur pada PT. XYZ Melvin Soeharto; Silvia Rostianingsih; Leo Willyanto Santoso
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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.
Co-Authors Alexander Setiawan Andre Cristo Singgih Andreas Handojo Calvin Christopher Kurniawan Christian Natanael Sugiharto Daniel Hartono Dion Alexander Louis Djoni Haryadi Setiabudi Feronica Natalia Rivaldi Henry Novianus Palit Indar Sugiarto Jason Jason Josia Christian Kevin Christian Kevin Pramana Pongmasak Kevin Shaquille Limanuel Leo Willyanto Santoso Liliana Liliana Lily Puspa Dewi Melvin Soeharto Michael Jonathan Resmana Lim Resmana Lim Stephen Cornelius Hertanto Willy Pratama Darmalim Yansen Tri Utomo Yoel Julianto Yosefani Kurniawan Yoshua Refo Yulia Yulia