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Intelmatics
Published by Universitas Trisakti
ISSN : -     EISSN : 27758850     DOI : https://doi.org/10.25105/itm
Core Subject : Science,
Computer Science & IT
The IntelMatics Journal is a scientific journal published by the department of informatics engineering at Trisakti University. The purpose and objective of the publication of the IntelMatics journal are as a means of dissemination of international standard science in the field of software engineering, information security, and business analysis in the scope of data intelligence and visualization. Journal will be published every sixth month
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol. 3 No. 2 (2023): Juli-Desember" : 8 Documents clear
Development of a Personnel and Payroll Information System at Madrasah Ibtidaiyah Misbahun Nasyiin School putra purnama; Dian Pratiwi; Agus Salim
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17145

Abstract

MI. Misbahunnasyiin is an Islamic educational institution located on Jl Raden Saleh, Tangerang. MI Misbahunnasyiin has administrative and financial data that is still recorded manually, which is very dangerous and vulnerable or at risk of data loss and damage. so that this research aims to find a solution to solve this problem by making applications related to digitalized payroll and staffing so that it can facilitate user performance and solve problems that existed before. Then writing study This is expected to simplify and increase efficiency in data processing and help develop information systems at the MI Misbahunnasyiin school using the language of them program PHP and MySql as server database.
The Implementation of Data Mining for Predicting XAU/USD Price Trends in the Forex Market on MetaTrader 5 using Naïve Bayes Method Sendi Novianto; Habib Akbar Wibowo
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17199

Abstract

The one of the trading instruments is forex or foreign exchange. The forex market provides various commodities, one of which is XAU/USD. XAU/USD dataset with daily, h4, h1 time frames obtained from the MetaTrader 5 application via the FBS broker. Predicting forex prices is difficult because there are various factors that influence it, so data mining methods are needed to predict increases or decreases. Naïve Bayes is a method and logic that can be applied in making predictions. So the research objective of this final project is to apply naïve Bayes methods and logic in predicting the price of XAU/USD on the daily, h4, h1 time frames. The application of the Naïve Bayes method uses several libraries to support research, namely pandas, jcopml, and sklearn. In naïve Bayesian logic research, this is called from the sklearn library using gaussianNB. In this study, the performance reference uses an f1 score matrix because the number of false positives and false negatives is not tight (symmetrical). This study produces values for each time frame obtained from the confusion matrix formula with f-scores of 49.99% (daily), 53.52% (h4), 55.44% (h1).
Forecasting Bulk Cooking Oil Prices for 20 District/Cities in North Sumatra Using Autoregressive Integrated Moving Average (ARIMA) Method: English Helmonica Simanjuntak; Is Mardianto; Syandra Sari
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17233

Abstract

Abstract— Frying is a popular method of food preparation in Indonesian society, whether it's for home-cooked meals or snacks bought outside. In Indonesia, there is bulk cooking oil available without a brand, which is cheaper. As a result, the usage of bulk cooking oil is higher compared to branded cooking oil. According to data published by BPS (Central Statistics Agency) in 2021, the per capita consumption of cooking oil in Indonesia reached 0.393L/Capita/week. The consumption of cooking oil in North Sumatra is also relatively high, but the poverty rate in North Sumatra is still high, with a figure of 1,268.19 thousand people. ARIMA method has advantages where the forecasting follows the data pattern and is flexible with relatively high accuracy. It is a quick and simple process (Hutasuhut, 2014). In ARIMA, there are two ways to determine the model, which are using the Auto Arima function and analyzing the ACF & PACF plots. The data used is the bulk cooking oil price data from January 2021 to January 2023 in Excel format, obtained from the Main Commodity Price System of North Sumatra. Based on the conducted research, the accuracy of the models generated by the Auto Arima function and the ACF & PACF plots are relatively similar. However, in some cases, the models generated by the Auto Arima function are not significant, although they have higher accuracy than the models generated from the ACF & PACF plots. The highest accuracy level is in Nias Utara district with an accuracy of 99.67% using the ARIMA(3,1,5) model, while the lowest accuracy level is in Nias Barat district with an accuracy of 75.26% using the ARIMA(2,0,0) model. Index Terms— ARIMA, Bulk Cooking Oil, Auto Arima, ACF&PACF Plot.
The Comparison of Gold Price Prediction Techniques Using Long Short Term Memory (LSTM) And Fuzzy Time Series (FTS) Method Putry Shan Alodia Surya Pangestu; Abdul Rochman; Ahmad Zuhdi
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17325

Abstract

Gold is a precious metal that has economic value and is often used as an investment tool. The demand for gold from day to day is increasing, because many know and think that gold can be used as ownership in the form of investment assets that have low risk. Therefore, it is necessary to predict the gold price to avoid losses. This study aims to predict the gold price using a machine learning architecture including deep learning, namely Long Short Term Memory (LSTM) and Fuzzy Time Series (FTS). Several trial processes were carried out in the training process and predict the LSTM and FTS models to get the best results. The data used in this experiment is real data from the period 15 September 2016 – 15 September 2021. The final results obtained from the LSTM method have an RMSE value of training data of 391.95 RMSE, and a value of test data 412.36 RMSE, and the FTS method has an RMSE value of 10449.115791541652
Web Based Banker Algorithm Simulation Bintang Rakha Daniswara; Rodrick Kiedies; Joshua Warman Sigalingging; gatot santoso
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17385

Abstract

This study aims to analyze and evaluate the Banker algorithm, which is used in operating systems to manage resources in a multiprogramming computing environment. This study uses an analytical and experimental approach to study the performance of the Banker algorithm in managing resource allocation and preventing deadlock conditions. The data was obtained through computer simulations and statistical analysis was used to compare results with other resource allocation algorithms. This research is expected to provide useful insights for operating system designers in selecting and implementing efficient algorithms to manage resources in complex computing environments.
Classification of Hijaiyah Letters Using Hybrid CNN-CatBoost Dimmas Mulya
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17521

Abstract

In this digital era, character recognition technology and letter classification are topics that are increasingly attracting attention, especially in the context of developing applications for learning Arabic, text processing, and artificial intelligence systems. There have been many previous studies examining this topic. However, there are still many opportunities to develop models for classifying hijaiyah letters to help many people learn to write hijaiyah letters. In this study, building a hijaiyah letter classification model using Hybrid-CNN and CatBoost, where CNN is used as a feature extractor and CatBoost as a classifier. CNN will be trained first to become a feature extractor and the results of the CNN model will be used as a feature extractor to create feature representation for training and testing CatBoost model. The AHDC dataset was used in this study and succeeded in achieving an accuracy value of 96.07%. Although it has not been able to compete with previous research, the Hybrid-CNN model with CatBoost has good potential in the future.
Implementation of Odoo-Based ERP in The Case Study of Micro, Small, and Medium Enterprises(MSME) "Woody Moody Jakarta" Syafitri Lutfia Zahra Zahra; Teddy Siswanto; Syaifudin
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17590

Abstract

Woody Moody is a Micro, Small, and Medium Enterprises (MSME) engaged in custom furniture services and is currently growing in West Jakarta. The operational business processes are still manually managed, starting from orders to transactions, resulting in manual handling of data related to sales results and transaction reports using spreadsheets. By implementing the Odoo methodology, an integrated Enterprise Resource Planning (ERP) system can help the MSME address existing issues in their business processes.The implementation of the integrated Enterprise Resource Planning (ERP) system aims to accommodate specific information system needs and assist in streamlining the business processes, starting from order processing to sales, thereby ensuring effective and efficient transactions. The results of the implementation demonstrate that the open-source Odoo-based Enterprise Resource Planning (ERP) can resolve these issues through the integration of digital business processes, providing convenience for business owners. Index Terms— ERP, Odoo, UMKM, Integration
Designing a Mobile-Based USAKTI on APP using The User Centered Design (UCD) Method Ratna Shofiati; Muhammad Rafiansyah Pramono; Agung Sediono
Intelmatics Vol. 3 No. 2 (2023): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i2.17639

Abstract

Usakti On APP merupakan aplikasi sistem informasi akademik yang dimiliki Universitas Trisakti. Aplikasi tersebut ada di platform mobile android dan juga website. Aplikasi yang berjalan di website melibatkan pengguna semua sivitas akademika. Aplikasi mobil awalnya bertujuan untuk mempermudah mahasiswa untuk melakukan pengecekan nilai dan krs. Kondisi tampilan user (user interface) dari Usakti On App masih kurang informatif dan terlihat kurang menarik, warna pada aplikasi kurang kontras dan kurang nyaman untuk mata, sehingga informasi yan disajikan menjadi tidak jelas. Oleh karena itu perlu adanya perbaikan alur sebuah system dengan menerapkan metode User Centered Design (UCD) pada perancangan system Usakti On App. Prototipe dibuat dengan Figma untuk menghasilkan rancangan yang high fidelity yaitu rancangan yang sangat mirip dengan hasil akhirnya. Hasil evaluasi dengan SUS didapatkan bahwa system yang baru mendapatkan skor rata-data 80,86 yaitu setingkat baik atau “good”

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