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Studi Pembanding Edge Detection Metode Sobel dan Prewitt pada Citra Rontgen Menggunakan Software Matlab Seneng, I Kadek; Adnyana, I Made Budi; Putra, I Made Agus Wirahadi; Suwirmayanti, Ni Luh Gede Pivin
Jurnal Eksplora Informatika Vol 13 No 2 (2024): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v13i2.1033

Edge detection merupakan sebuah proses mendeteksi garis tepi yang membatasi dua wilayah, deteksi tepi banyak diterapkan pada bidang medis yang bertujuan untuk memudahkan analisis. Menentukan metode deteksi tepi citra tidak bisa hanya dilihat secara langsung, maka perlu adanya analisis penentuan metode. Pada penelitian ini menggunakan citra rontgen tulang rusuk, dan citra rontgen jari-jari tangan, pada penelitian ini dilakukan tahap perbaikan citra noise reduction, kemudian konversi citra menjadi grayscale, kemudian deteksi tepi metode Sobel dan Prewitt, kemudian proses binerisasi dan perbandingan menggunakan tiga parameter perbandingan MSE, PSNR dan nnz. Semakin besar nilai MSE menunjukkan perbedaan besar antara citra awal dengan citra hasil, semakin besar nilai PSNR menunjukkan semakin besar kualitas dari gambar yang dihasilkan. Fungsi nnz (number of nonzero entries) semakin banyak piksel warna putih maka semakin banyak juga tepi yang diperoleh. Berdasarkan hasil penelitian yang telah dilakukan, maka diperoleh kesimpulan, pada citra rontgen tulang rusuk metode sobel menghasil nilai lebih baik berdasarkan hasil yang diperoleh pada masing-masing parameter penguji MSE= 4.610,7, PSNR= 11.493,2 dB, nnz= 10.752. Pada citra rontgen jari-jari tangan metode prewitt menghasilkan nilai lebih baik berdasarkan hasil yang diproleh MSE= 1.188,8, PSNR= 17.379,9 dB, nnz= 6.948.

Comparison of LSTM and GRU Models Performance in Forecasting Gold Prices: A Case Study Using Historical Data from Yahoo Finance Sudiatmika, I Putu Gede Abdi; Putra, I Made Agus Wirahadi
ARRUS Journal of Engineering and Technology Vol. 4 No. 1 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech2760

This research aims to compare the performance of two types of recurrent neural network models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in forecasting gold prices based on historical closing price data. Historical gold price data from December 14, 2017, to March 14, 2024, was downloaded using the yfinance library. The data was normalized using MinMaxScaler and split into training and testing sets with an 80:20 ratio. LSTM and GRU models were constructed with two recurrent layers followed by a Dense layer for output. Both models were trained using the training data and evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R²) metrics. The experimental results indicate that the GRU model outperformed the LSTM model in predicting gold prices. GRU achieved an MSE of 337.70, MAE of 14.05, and R² of 0.933, whereas LSTM achieved an MSE of 808.98, MAE of 22.71, and R² of 0.839. Based on the model performance evaluation, it can be concluded that GRU consistently produced more accurate predictions closer to the actual values of gold prices compared to LSTM. This finding suggests that GRU may be a preferable choice in applications for forecasting gold prices using historical data.

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping Dharmendra, I Komang; Januhari, Ni Nym Utami; Ramayasa, I Putu; Putra, I Made Agus Wirahadi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v7i1.1748

Opinion is an important part of decision making, so it takes the ability to get information from opinions. Sentiment Analysis is a branch of science from Text mining that can be used for opinion analysis in the form of text to classify opinions into 3 types of opinions, namely positive opinions, neutral opinions and negative opinions. Support Vector Machine (SVM) is one method that is widely applied for text mining because it is able to show good performance (Styawati and Mustofa, 2019). SVM works with a learning system that uses a hypothetical space in the form of linear functions in a high-dimensional feature space. Maximum Entropy is a probabilistic classification algorithm that belongs to the class of exponential models, which is based on the principle of Maximum Entropy. Maximum Entropy can be used to solve text classification problems such as Language detection, topic classification, and sentiment analysis. Sentiment analysis was tested using the Support Vector Machine (SVM) and Maximum Entropy methods to test the accuracy of each method in analyzing the sentiments of college alumni opinions. from the test results show Maximum Entropy has a better level of accuracy with the results of 95.45%

Visualisasi Data Opini Publik pada Media Sosial Twitter (Studi Kasus : Nusantara Sebagai IKN Indonesia) Dharmendra, Komang; Januhari, Ni Nym Utami; Diaz, Ricky Aurelius Nurtanto; Ramayasa, I Putu; Putra, I Made Agus Wirahadi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 2 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

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

The capital city has an important role for various aspects of government, the capital city has a function as the center of political power and the economy of a country. In the process, sometimes the head of government of a country moves the capital of the country, either moving it to an existing city or building a new city that was built specifically to become the capital of the country. Like what Indonesia did, which planned to move the country's capital, which was previously in Jakarta, moved to East Kalimantan and built a new city to become the nation's capital with the name Nusantara. The relocation of the capital city was carried out to divide the economic center and the government center which were previously centered in Jakarta into an economic center in Jakarta and a government center in the archipelago. The announcement of the name of Indonesia's new capital city received reactions from the public, with various written opinions being shared through social media. One of the social media channels that is widely used is Twitter. With so many public responses through social media, a process is needed to find out how to respond and form of expression for the announcement of the name of the capital city of the archipelago. One of the processes that can be done is to visualize tweets containing the word "Nusantara" which collected 83604 tweets using data on the number of tweets, posting hours, hashtags that can find out how the public responds to the announcement of the state capital "Nusantara"..

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping Dharmendra, I Komang; Januhari, Ni Nym Utami; Ramayasa, I Putu; Putra, I Made Agus Wirahadi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v7i1.1748

Opinion is an important part of decision making, so it takes the ability to get information from opinions. Sentiment Analysis is a branch of science from Text mining that can be used for opinion analysis in the form of text to classify opinions into 3 types of opinions, namely positive opinions, neutral opinions and negative opinions. Support Vector Machine (SVM) is one method that is widely applied for text mining because it is able to show good performance (Styawati and Mustofa, 2019). SVM works with a learning system that uses a hypothetical space in the form of linear functions in a high-dimensional feature space. Maximum Entropy is a probabilistic classification algorithm that belongs to the class of exponential models, which is based on the principle of Maximum Entropy. Maximum Entropy can be used to solve text classification problems such as Language detection, topic classification, and sentiment analysis. Sentiment analysis was tested using the Support Vector Machine (SVM) and Maximum Entropy methods to test the accuracy of each method in analyzing the sentiments of college alumni opinions. from the test results show Maximum Entropy has a better level of accuracy with the results of 95.45%

Visualisasi Data Opini Publik pada Media Sosial Twitter (Studi Kasus : Nusantara Sebagai IKN Indonesia) Dharmendra, Komang; Januhari, Ni Nym Utami; Diaz, Ricky Aurelius Nurtanto; Ramayasa, I Putu; Putra, I Made Agus Wirahadi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 2 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

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

The capital city has an important role for various aspects of government, the capital city has a function as the center of political power and the economy of a country. In the process, sometimes the head of government of a country moves the capital of the country, either moving it to an existing city or building a new city that was built specifically to become the capital of the country. Like what Indonesia did, which planned to move the country's capital, which was previously in Jakarta, moved to East Kalimantan and built a new city to become the nation's capital with the name Nusantara. The relocation of the capital city was carried out to divide the economic center and the government center which were previously centered in Jakarta into an economic center in Jakarta and a government center in the archipelago. The announcement of the name of Indonesia's new capital city received reactions from the public, with various written opinions being shared through social media. One of the social media channels that is widely used is Twitter. With so many public responses through social media, a process is needed to find out how to respond and form of expression for the announcement of the name of the capital city of the archipelago. One of the processes that can be done is to visualize tweets containing the word "Nusantara" which collected 83604 tweets using data on the number of tweets, posting hours, hashtags that can find out how the public responds to the announcement of the state capital "Nusantara"..

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