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All Journal Jurnal Manajemen Informatika JESICA
Mohammad Edi
Universitas Amikom Yogyakarta
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering

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Implementasi Bidirectional LSTM untuk Analisis Sentimen Terhadap Layanan Grab Indonesia Dloifur Rohman Alghifari; Mohammad Edi; Lutfi Firmansyah
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.7764

Abstract

Grab Indonesia is one of the leading online motorcycle taxi companies in Indonesia and has a large number of customers in Indonesia. The level of customer satisfaction varies with the services provided, so there must be suggestions and complaints from customers. Sentiment analysis can be used as a solution to determine the level of service satisfaction in order to improve the system and service. This study aims to determine the level of satisfaction of Grab Indonesia users through the Grab application in the Playstore. One of the approaches that can be used is LSTM. LSTM is an RNN algorithm development to solve the vanishing gradient problem. LSTM has the disadvantage of only running can only capture information from one direction. Bidirectional LSTM (BiLSTM) is an LSTM method that has been developed, where BiLSTM can capture information from two directions. In this BiLSTM method, the more data, the better the algorithm's performance. The test results show that BiLSTM is more reliable than LSTM in the case of sentiment analysis on the Indonesian Grab service. BiLSTM produces the best accuracy of 91% and training loss of 28%. Suggestions for future research can produce more and varied word representations by considering the word embedding combinations.
Prediksi Harga pada Trading Forex Pair USDCHF Menggunakan Regresi Linear Mohammad Edi; Ema Utami; Ainul Yaqin
Jurnal Manajemen Informatika JAMIKA Vol 13 No 2 (2023): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v13i2.9826

Abstract

In the era of globalization, free trade grows rapidly and technology develops, affecting economic competition. Forex, foreign exchange trading, is one of the investments used to face this challenge. Technical and fundamental analysis is used to predict price movements in forex trading. Previous studies have used linear regression algorithms and other techniques for price prediction in forex. In this study, the linear regression algorithm is used to predict closing prices in forex trading because the linear regression algorithm is an algorithm that has been widely used in predictions, its strengths are in estimating simple model parameters and data based on time series. In addition, the linear regression algorithm can perform analysis using several independent variables so that the prediction results can be more accurate. The purpose of this study is to create a forex price prediction model, to make it easier for traders to make price predictions. A dataset of 2066 data was obtained through the metatrader software and processed through the preprocessing stage. The linear regression model was created using 5 scenarios, and the evaluation was carried out using the Mean Squared Error (MSE) and Root Mean Square Error (RMSE) values to select the best model. The results show that linear regression is able to predict the closing price of the USDCHF pair. The best linear regression model is obtained using the independent variable in scenario 1, namely the Open variable, with a linear regression equation of y=0.0145+0.9849x, the best MSE is 0.0000328509 and the best RMSE is 0.0057315705.
Prediksi Harga pada Pasar Forex Menggunakan Regresi Linier Berganda Mohammad Edi; Ema Utami; Ainul Yaqin
JESICA (Jurnal Teknologi Informasi , Sistem Informasi, dan Data Science) Vol 1 No 2 (2024): MARET 2024
Publisher : LPPM AMIK Taruna Probolinggo

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pasar Forex, atau pasar valuta asing, adalah pasar global yang melibatkan pertukaran mata uang dari berbagai negara di seluruh dunia. Harga mata uang dalam pasar Forex berfluktuasi secara terus-menerus, dipengaruhi oleh berbagai faktor ekonomi, politik, dan sosial. Oleh karena itu, memiliki kemampuan untuk memprediksi pergerakan harga mata uang secara akurat menjadi kunci dalam mengambil keputusan perdagangan yang sukses. Permasalahan di Indonesia adalah seringkali masyarakat Indonesia tidak memandang investasi sebagai sesuatu yang penting. Berinvestasi sangat penting, tetapi banyak yang kehilangan uang atau menderita kerugian besar saat berinvestasi, terutama di pasar forex. Berinvestasi di pasar forex memang memiliki potensi keuntungan yang tinggi, namun risikonya juga tinggi. Tujuan dari penelitian ini adalah untuk memprediksi harga close yang dapat digunakan trader dalam pengambilan keputusan pada pasar forex. Algoritma yang digunakan adalah regresi linier berganda, dengan hasil akurasi sebesar 0.9996763769734622 atau 99.96763769734622%. Nilai MSE yang dihasilkan sebesar 7.326609474636409e-08 atau 0.00000007326609474636409, sedangkan nilai RMSE sebesar 0.0002706771042152699. Nilai MSE dan RMSE mendekati nol, metode yang dibentuk dalam penelitian ini sangat baik.
Co-Authors Ainul Yaqin Dloifur Rohman Alghifari Ema Utami Ida Ayu Putu Sri Widnyani Lutfi Firmansyah