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INDONESIA
Indonesian Journal on Computing (Indo-JC)
Published by Universitas Telkom
ISSN : 24609056     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University (Indonesia).
Arjuna Subject : -
Articles 5 Documents
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Search results for , issue "Vol. 7 No. 1 (2022): April, 2022" : 5 Documents clear
Non-Negative Matrix Factorization Based Recommender System using Female Daily Implicit Feedback Hani Nurrahmi; Agung Toto Wibowo; Selly Meliana
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.599

Abstract

Recommender Systems is widely used by e-commerce to provide recommendations of products that are probably to be the interest to users. One of the recommender system algorithms that can be implemented is Non-negative Matrix Factorization (NMF) which receives explicit feedback in the form of user ratings. Although this method is effective, there are problems faced by explicit feedback as input, e.g. there are users who act as grey-sheep or black-sheep by providing dishonest ratings as explicit feedback. On the opposite, dishonest feedback least frequently occurs in implicit feedback. Therefore, in this study, we used implicit feedback to recommend products by taking the implicit feedback obtained from Female Daily’s mobile application as a case study. There are three types of implicit feedback: View Product Detail, View Review Detail, and Add to Wishlist. We experimented with the NMF algorithm provided by Surprise library using two implicit ratings weighting scenarios: accumulative weighting and maximum weighting. We combined several NMF parameters and run our experiment in 5-fold cross-validation. The best performance result in accumulative weighting is MSE = 1,2969, RMSE = 1,1388, MAE = 0,7909. Meanwhile, the best performance result in maximum weighting is MSE = 0,6742, RMSE = 0,8211, MAE = 0,5924.
Column-Level Database Encryption Using Rijndael Algorithm and Dynamic Key on Learning Management System Ariva Syam Mursalat; Ari Moesriami Barmawi; Prasti Eko Yunanto
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.609

Abstract

The course management system’s goal is to help learning activities. The system helps tomanage tasks, the grading process, and user communications. To avoid unauthorized dataaccess, the course management system needs a mechanism to protect the password that isused in the system’s login process. Database encryption using Rijndael algorithm is proposedby Francis Onodueze et al. to protect the data. A key is needed for the encryption process,and the key has to be kept secret. Thus, when the key is static, it is vulnerable against keyguessing attacks. To overcome the static key’s drawback, a dynamic key generation usingHash Messages Authentication Code - Deterministic Random Bit Generator (HMAC-DRBG)is proposed because it can generate keys periodically. Based on the evaluation, the probabilityof success key guessing attack using the proposed method is less than using the previousmethod, while the time complexity of those methods is similar.
Study of Denoising Method to Detect Valvular Heart Disease Using Phonocardiogram (PCG) Muhammad Yaumil Ihza Ihza; Satria Mandala; Miftah Pramudyo
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.610

Abstract

Heart sound is a very weak acoustic signal, very susceptible to external acoustic signals and electrical disturbances, especially friction caused by the subject's breathing or body movements. The heart sound signal will be recorded in a phonocardiogram (PCG) and produce heart sounds, noise, and extra sounds. The purpose of this work is to denoise the signal from the heart sounds recorded on the PCG and determine valvular heart disease (VHD). Several methods have been proposed for denoising heart sound signals, both in the time domain and in the frequency domain. Most of these methods still have problems for denoising results. In this paper, the techniques used to denoise the heart sound signal are Discrete Wavelet Transform (DWT), Short Term Fourier Transform (STFT), and Low-Pass filter.
Job Vacancy Information System Based on SMS Gateway as Part of Tracer Study Alumni of UPI Cibiru Campus Fahmi Candra Permana; Sisilia Sylviani; Feri Hidayatullah Firmansyah; Intan Permata Sari
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.611

Abstract

The waiting period for graduates of an educational institution to get a job can be a benchmark for the quality of the institution in carrying out the educational process for its graduates. One thing that indicates the success of the educational process in an institution is the absorption of graduates from that institution in the world of work. To achieve this, an educational institution requires a system that can provide services and specific attention to its graduates in obtaining information related to work by their scientific fields quickly and sustainably. In this paper, an information system based on SMS Gateway technology is designed as a medium that can provide information directly to graduates rapidly and sustainably according to the needs of graduates. The method that we used in this research is the Rapid Application Development method as an information system design method, and Black Box Testing as a test of information system applications that have been developed. This system was built as part of the Tracer Study for alumni of the UPI Cibiru Campus, to provide information on job vacancies by the scientific fields of its graduates.
Stock Market Price Forecasting Using Recurrent Neural Network Pragya Bhardwaj; Jayant Kwatra
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.612

Abstract

A stock refers to the ownership of the organisation and its investors. A market where these stocks are sold or purchased is known as stock market. The prices of the stock is listed over National Stock Exchange or Bombay Stock Exchange for all Indian Companies. In this work, a machine learning approach is used to predict and forecast the prices of a company listed in NSE and BSE for 30 days using recurrent neural network known as stacked long-short term memory model. The results show that the model worked highly effective in performing the task. The model in the evaluation phase gave a root mean square error of 3.00 on the training data, 0.03 on testing data. R2 score for training data was 0.99 and 0.97 for the testing data. The prices when compared by the client organisation showed that they matched the predicted values to upto 90%. Thus, stacked LSTM models are one of the best models to make predictions of stock related data.

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