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Silvia Rostianingsih
Program Studi Informatika
Computer Science & IT

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Implementasi Sistem Informasi Administrasi Pembelian, Penjualan, Retur dan Inventaris Produk Kosmetik Toko Beauty Dengan Platform Android Tommy Sugiarto; Silvia Rostianingsih; Rolly Intan
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Integrated information system is needed on running a business process. The problem nowadays is there is no information system yet capable of support faster business processes. By using the development of technology, information system can process data which can easily manage business process at company. Nowadays, there are companies that are not using the technology optimally.To solve the problems, Beauty Store needs implementation of integrated information system by mobile is needed. By using the technology, can help in increasing of speed and accuracy when make a transaction. Information system of website and point of sales application can record any transaction of purchasing, selling, return and inventory by detail, so it can be practical and easy to use for transaction. From the analysis of questionnaire and system test, 76% of the respondent stated that the website and point of sales application can easily help to manage data of sales, purchasing, return and inventory, and the rest stated not that easy to help manage transaction data.
Pencatatan dan Penghitungan Skor Pada Olahraga AAIPSC dengan NFC Berbasis Android Satria Antoni Gunawan; Silvia Rostianingsih; Alexander Setiawan
Jurnal Infra Vol 7, No 2 (2019)
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Abstract

Recording and Calculation of Scores in AAIPSC sports requires speed and accuracy both in terms of accessing and inputting data. At this time, recording is done through paper, so the time taken to enter the calculation software takes a relatively long time. The author hopes that the application created can speed up the calculation and data can be stored to SQL server. With NFC as a validation system, it is hoped that data validation can be maintained at the time of inputting.
Perancangan dan Pembuatan Sistem Infromasi Akuntansi di Perusahaan XYZ Prayudi Suseno; Silvia Rostianingsih; Lily Puspa Dewi
Jurnal Infra Vol 2, No 1 (2014)
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XYZ company is a company engaged in manufacturing car boxes. Box for sale is the result of the manufacture from raw materials purchased from suppliers and then processed by the production. The company want to replace manual systems to computerized systems, because by using the old system of recording transactions are less secure and not convincing in data storage. Thus, they need a system that can help improve company performance. Therefore, in this thesis designed an accounting system that can perform all accounting processes and transactions more quickly and with securely stored data.The process of making this software is started from the system design, analyzes the Problems Company have, and analysis of the needs that exist in the company. The modules are made using of Microsoft Visio for DFD, ERD using Smart Draw and also design tables and design a menu . This software is created using VB programming language .NET and Microsoft SQL Server also uses as data storage.Based on the results of testing, the program is considered to be in accordance with existing accounting system in general. This can be evidenced by the percentage of the number of respondents who answered the questionnaire.
Perbandingan Analisis Faktor Penentu Penjualan PT. X Menggunakan LASSO Regression dan Gradient Boosted Regression Tree Jessica Athalia; Henry Novianus Palit; Silvia Rostianingsih
Jurnal Infra Vol 9, No 1 (2021)
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Information becomes a crucial asset for an organization. However, employees of PT. X are facing difficulty in analyzing data because it has to be processed one by one. Moreover, analyzing data in an operational database is not recommended as it can interfere with the performance of the operational database. Then, when the Board of Directors want to know the reason behind its sales’ performance, they conclude it based on their mere assumption. This research implemented a data warehouse with the help of ETL tools. Then, sales transactions of PT. X were analyzed to get information about factors that affect company’s revenue. Factor models were formed for brands which sales were not good enough these past few years. Factors which are examined are sales price, stock availability, on time delivery of goods, quantity of returns, month of transaction, and cost price. The analysis was carried with two methods, LASSO regression and Gradient Boosted Regression Tree. These models were measured by Root Mean Squared Error, R-squared, and Variance Inflation Factor to know which model performs better. Result of the research shows LASSO regression and Gradient Boosted Regression Tree succeed in performing feature selection for sales transactions of PT. X. Yet, the factor model from Gradient Boosted Regression Tree gives a better result than LASSO regression. Last, a program was made for the company in the need of future analysis using Gradient Boosted Regression Tree.
Analisa Forecasting Pada Penjualan Pakaian Di PT X Andreas William; Silvia Rostianingsih; Yulia Yulia
Jurnal Infra Vol 9, No 2 (2021)
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PT X is garment company based in Surabaya that distributing clothing goods to Department Stores throughout Indonesia. PT X have an accumulation of goods in every Department Stores that are related as their business partners. This has an impact on the company's losses because high production costs do not match the remaining stock of goods in each store. Therefore, PT X needs an application that can forecast the number of categories of goods that will be sold in the future. Analysis of sales forecasting methods at PT X uses four different forecasting approaches, consists of Single Moving Average (SMA), Weighted Moving Average (WMA), Brown's Double Exponential Smoothing, and Holt’s Double Exponential Smoothing. The results of sales forecasting analysis on 4 categories of goods in the form of long blouses, short blouses, dresses, and robes from one of the stores, namely MDS Delta Plaza, show that the most appropriate method for PT X is Holt’s Double Exponential Smoothing (HES). The Mean Absolute Deviation (MAD) error value and the Mean Squared Error (MSE) of each category have the least value of the other methods.
Analisa Audio Features dengan Membandingkan Metode Multiple Regression dan Polynomial Regression untuk Memprediksi Popularitas Lagu Billy Faith Susanto; Silvia Rostianingsih; Leo Willyanto Santoso
Jurnal Infra Vol 9, No 2 (2021)
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Songs are artistic works that expresses ideas and emotion in the forms of rhythms, melodies, and harmonies. Songs are the source of huge profit for musicians or artists from commercial view-point. Based on the data from IFPI, the earnings from the music industry in 2019 reached US$20.2 billion, in which 56.1% of them came from streaming revenue. Spotify is one of the largest and most well-known streaming services in the world today. This research aims to make predictions of popularity from each song according to the audio feature data taken from Spotify's API. The process of prediction will use 2 regression methods, which are Linear Regression and Polynomial Regression. The model will be made using those 2 methods and will be tested with the R2, Adjusted R2, MAE, and MSE metric systems. From the analysis of the implementation to the program, the Linear Regression method had garnered the average results as follows: 0.23614 for R2, 0.23536 for Adjusted R2, and had average errors 17.38129 for MAE method, 442.31700 for MSE method. Using the Polynomial Regression method, the average results were: 0.31496 for R2, 0.25880 for Adjusted R2, and had average errors 16.47367 for MAE method, 409.76242 for MSE method.
Aplikasi Scoring System Untuk Penentuan Keputusan Kredit Pada BPR DRJ Berbasis Web David Alfredo Wiejoyo; Silvia Rostianingsih; Lily Puspa Dewi
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

In the banking world, specifically rural bank, lending a credit facility is a crucial business step. To be given a credit facility, the customer first have to pass through several assessment to determine the eligibility wether the customer met to be given a credit facility. Sales or the customer themselves can collect the requirement and sent them to the rural bank to complete the requirement of a credit facility. The assessment will be held by human and tend to have error-prone. Another obstacle is the distance, the customer have to come to the rural bank themselves or even send the requirement which takes time to send the requirement. These obstacles given the writer an idea to create the application. This application created based on web with HTML and PHP language alongside with Javascript features with MySQL database. This application can run the process needed from the beginning of collecting requirement until the score of the assessment is out. The application can aslo store the uploaded documents to the application database.The result of this thesis is the application can run the process of credit scoring until the score is out. The application can also print the required legal documents created by the application. The application can run responsively at different platform. The thesis also meet the problem statement.
Penerapan Segmentasi Pelanggan dengan Menggunakan Metode K-Means Clustering Pada Sistem Customer Relationship Management di PT. Titess Michael Boentarman; Silvia Rostianingsih; Alexander Setiawan
Jurnal Infra Vol 9, No 2 (2021)
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PT. Titess is a consumer good company with a variety of products such as consumption salt, packaged cooking oil, soap, sugar and so on. Currently PT. Titess has distributors whose role is to market products directly to consumers. With the aim of increasing sales at each distributor, PT. Titess provides special treatment. Special treatment is given manually for certain distributors. This is felt to be less than optimal, because the special treatment given is not right on target for each distributor who has the most sold superior product types. Therefore, we need a distributor segmentation system using the K-means method referring to sales history data. The proposed system also has features that can help distributors to place orders independently, confirm payments, submit returns, submit complaints and exchange reward points for prizes that can be arranged by the company. The results of the system have been tested for system acceptance using a questionnaire that was distributed to 5 users. The results of the system acceptance test show the distributor's satisfaction level with the system. Distributors feel the convenience and benefits of the system.
Aplikasi Transaksi Bisnis Usaha Mikro Kecil dan Menengah dengan Fitur Penyimpanan Data Online dan Offline Michelle Florensia; Silvia Rostianingsih; Andreas Handojo
Jurnal Infra Vol 9, No 2 (2021)
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Micro Small and Medium Enterprises (MSMEs) today are still many who do manual recording using paper so that often causes miscalculation. In addition, MSMEs are also unable to provide information quickly because information is not distributed. MSME actors also need time in analyzing sales. Therefore, a system is needed that can help MSMEs to record and calculate stocks and profit/loss statementsSeeing the problem, then this thesis will be created a website with the feature of recording goods, buying and selling transactions, and the calculation of profit/loss. In addition, the website is equipped with online and offline data storage features so that users do not have to be connected to the internet. The system is made based on a website so that MSMEs can access the website through a smartphone or laptop. The system will be created using the PHP 7 programming language, download the cache using the Service Worker as well as use the CouchDB online database and the PouchDB offline database.Based on the results of this thesis research can be concluded that the use of the website can help MSMEs in recording the business process. Websites can also run without an internet connection, but pages must be loaded one by one. Memory usage is also small enough that it does not interfere with the performance of the device. This website can be developed further by adding features and easier to do cache downloads
Implementasi Algoritma YOLO pada Aplikasi Pendeteksi Senjata Tajam di Android. Christopher Nathanael Liunanda; Silvia Rostianingsih; Anita Nathania Purbowo
Jurnal Infra Vol 8, No 2 (2020)
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Advances in computing power have exceeded traditional smartphone needs. Object detection requires high computational power. Tensorflow Lite can be used to run models quickly and easily to mobile devices. The YOLO network was used because of faster and more accurate performance than other similiar networks. The object to be identified are bladed weapons that are knifes and machetes. Bladed weapons are selected because of potential applications in the real world.The trained models are YOLOv2-tiny, YOLOv3-tiny and YOLOv3. Transfer Learning is done to these models with Darknet so that YOLO can detect the desired weapon. Darknet model will be converted to Tensorflow Lite. Model testing is done by looking at some standard accuracy metrics such as precision, recall, mAP, and the average IoU. The model with the best performance will be installed in the Android application to detect bladed weapon objects knifes and machetes.The test results show that the performance of the model is very dependent on the type of network, the number of datasets, and the shape of the dataset. YOLOv2-tiny produces the worst result with mAP of 55% and average IoU of 35%. The final accuracy for Tensorflow Lite Android model are 72.7% for YOLOv3 and 63.6% for YOLOv3-tiny. The YOLOv3-tiny network is suitable for real-time detection because of fast inference time (0.9 seconds).
Co-Authors Alexander Setiawan Alvin Nathaniel Tjondrowiguno Andre Gunawan Andreas Handojo Andreas William Anita Nathania Purbowo Ardian Teja Billy Faith Susanto Christian Purnama Christopher Nathanael Liunanda David Alfredo Wiejoyo Febry Suryanto Fendy Haryanto Hansen Ginno Samuel Tangkas Soetedjo Giovanni Gabriela Gunadi Hendyk Cendana Santoso Henry Novianus Palit Hilarius Andriano Sengyang Indra Setiawan Indro Setiawan Jessica Athalia Juan Felix Nyoto Santoso Justinus Andjarwirawan Kartika Gunadi Kevin Yosi Putra Utama Leo Willyanto Santoso Lily Puspa Dewi Michael Boentarman Michael Levi Michelle Florensia Prayudi Suseno Regina Valentina Resmana Lim Rolly Intan Satria Antoni Gunawan Stefanus Benhard Stefen Ongko Saputro Stephen Lukas Wijaya Susangto Andi Putera S. Tommy Sugiarto Yohanes Setiawan Yulia Yulia