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Leo Willyanto Santoso
Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
Computer Science & IT

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Sales Management Support and Analytics untuk Meningkatkan Koordinasi Pekerja dan Pelayanan Pembeli UD. XYZ Melissa Marvella; Leo Willyanto Santoso; Yulia Yulia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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.
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.
Sistem Rekomendasi Pembelian Laptop dengan K-Nearest Neighbor (KNN) Sheeren Hendrik Anggela; Leo Willyanto Santoso; Justinus Andjarwirawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

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.
Co-Authors Agustinus Noertjahyana Calvin Christopher Kurniawan Daniel Hartono Dion Alexander Louis Felix Felix Henry Novianus Palit Ivan Hartono Jennifer Soeryawinata Justinus Andjarwirawan Kevin Shaquille Limanuel Melissa Marvella Melvin Soeharto Rescky Marthen Mailoa Sheeren Hendrik Anggela Silvia Rostianingsih William Jordy Yansen Tri Utomo Yulia Yulia