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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Ilmu Komputer dan Agri-Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Pengabdian Informatika (JUPITA)
I Gede Arta Wibawa
Informatics Study Program, FMIPA, Universitas Udayana, Bali
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Education Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Sum of Squared Difference (SSD) Template Matching Testing on Writing Learning Application Sidi, Widya Dharma; Arta Wibawa, I Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 4 (2020): JELIKU Volume 8 No 4, Mei 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i04.p11

Abstract

Abstract This research was conducted to determine the accuracy of the Sum of Squared Difference (SSD) Template Matching method in the Application of Learning Numbers Writing Games. This game application is an application created to help early childhood in recognizing Arabic numbers, namely numbers from 0 to 9. In the SSD Template Matching method there are several processes including Preprocessing, thinning, feature extraction, and classification (SSD template matching). In testing the game application involves 10 respondents who were asked to write numbers correctly as requested by the application. For each number writing test, it is tested by 3 times. From the tests conducted, obtained an accuracy of 94.67%. Keyword: Template Matching, Sum of Squared Difference (SSD), Education Game, Optical Character Recognition, Mobile Learning
VOCAL TONE PRECISION DETECTION USING HARMONIC PRODUCT SPECTRUM (HPS) AND K-NEAREST NEIGHBOR (KNN) CLASSIFICATION Apsari, Made Sri Ayu; Widiartha, I Made; Agung Raharja, Made; Santi Astawa, I Gede; Arta Wibawa, Gede; Made Mahendra, Ida Bagus
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 2022
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2022.v10.i03.p01

Abstract

The progress of the digital era that is happening today, encourages rapid development in technology and science, one of which is in the field of art. Of all performing arts, the art of singing is the most complex, which requires a lot of preparation and practice. Everyone has a different type of voice. Males generally have three types of voice, namely bass, baritone, and tenor, while women generally have three types of voice, namely contralto (alto), mezzo-soprano, and soprano. However, not everyone knows what kind of voice they have. Therefore, this study will focus on classifying the human voice. In this study, the author uses the Harmonic Product Spectrum (HPS) and K-Nearest Neighbor (K-NN) algorithms. The data used is in the form of primary voice recording data obtained from 258 participants (male and female), where each person has 8 sound files, namely do, re, mi, fa, sol, la, si, and do'. saved in .wav format. From the research conducted, the test was carried out using the K-NN and K-NN methods with Hyperparameters. The results obtained in the form of accuracy of 74% and 81%, so that the Harmonic Product Spectrum (HPS) and K-Nearest Neighbor (K-NN) algorithms give good results for determining the type of human voice.
Comparison of SVM and LIWC for Sentiment Analysis of SARA AAIN Eka Karyawati; Prasetyo Adi Utomo; I Gede Arta Wibawa
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.69617

Abstract

SARA is a sensitive issue based on sentiments about self-identity regarding ancestry, religion, nationality or ethnicity. The impact of the issue of SARA is conflict between groups that leads to hatred and division. SARA issues are widely spread through social media, especially Twitter. To overcome the problem of SARA, it is necessary to develop an effective method to filter negative SARA. This study aims to analyze Indonesian-language tweets and determine whether the tweet contains positive or negative SARA or does not contain SARA (neutral). Machine learning (i.e., SVM) and lexicon-based method (i.e., LIWC) were compared based on 450 tweet data to determine the best approach for each sentiment (positive, negative, and neutral). The best evaluation results are shown in the negative SARA classification using SVM with λ = 3 and γ = 0.1, where Precision = 0.9, Recall = 0.6, and F1-Score = 0.72. The best results from the positive SARA classification were shown in the LIWC method, where Precision = 0.6, Recall = 0.8, and F1-Score = 0.69. The best evaluation results for neutral classification are shown in SVM with λ = 3 and γ = 0.1, with Precision = 0.52, Recall = 0.87, and F1-Score = 0.65.
APLIKASI PENGENALAN SELAPUT PELANGI (IRIS) MENGGUNAKAN TRANSFORMASI HAAR WAVELET I Gede Arta Wibawa
Jurnal Ilmu Komputer Vol. 4, No. 2 September 2011
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.771 KB)

Abstract

Sistem pengenalan biometrik merupakan sistem pengenalan pola yang menggunakan karakteristik fisiologis atau karakteristik perilaku untuk mengenali identitas seseorang. Berdasarkan sudut pandang aplikasi, sistem pengenalan biometrik dapat dibangun dalam modus verifikasi atau identifikasi. Selaput pelangi (iris) merupakan salah satu karakteristik fisiologis yang paling berpotensi digunakan dalam sistem pengenalan biometrik. Kerumitan, keunikan, dan kestabilan karakteristik tekstur acak yang dimiliki iris dapat digunakan sebagai salah satu paspor hidup untuk pengenalan individu yang disarankan oleh ophthalmologists.Pada penelitian ini dibangun sistem verifikasi citra iris yang digunakan untuk melakukan validasi identitas seseorang dengan membandingkan dua iris template. Keputusan verifikasi yang dihasilkan didasarkan pada match threshold yang digunakan. Untuk mengekstraksi pola iris yang akan dijadikan karakteristik dari suatu iris dapat dilakukan dengan berbagai metode yang sebagian besar didasarkan pada dekomposisi band pass citra iris. Salah satu metode yang dapat digunakan adalah transformasi Haar wavelet. Metode tersebut diaplikasikan pada citra iris yang telah dinormalisasi ke koordinat polar. Iris template yang dihasilkan dibentuk dari kombinasi koefisien detil HL5, LH5, dan HH5.Hasil penelitian yang diperoleh menunjukkan iris template yang dibentuk dari kombinasi HL5 – HH5 menghasilkan keputusan verifikasi yang lebih akurat dengan persentase FNMR dan FMR sebesar 6,67%.
Estimasi Spektrum Reflectance Citra Daun Jati Belanda Menggunakan Transformasi Wavelet I Gede Arta Wibawa; Yeni Herdiyeni; Bib Paruhum Silalahi
Jurnal Ilmu Komputer & Agri-Informatika Vol. 4 No. 1 (2015)
Publisher : Departemen Ilmu Komputer - IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (373.132 KB) | DOI: 10.29244/jika.4.1.22-28

Abstract

Jati belanda (Guazuma ulmifolia) adalah salah satu tanaman yang berkhasiat sebagai antioksidan karena pengaruh senyawa aktif yang terkandung di dalamnya. Cahaya pantulan (reflectance) dapat digunakan untuk mengetahui kualitas senyawa aktif pada daun jati belanda. Penelitian ini membahas tentang estimasi spektrum reflectance citra digital daun jati belanda menggunakan model reflectance daun tanaman obat dengan menerapkan transformasi wavelet. Bahan yang digunakan adalah daun tanaman obat dan daun jati belanda. Transformasi wavelet digunakan untuk merepresentasikan reflectance daun tanaman obat. Model polinomial diterapkan untuk mengekspansi ciri citra digital. Model reflectance terbaik dari penerapan transformasi wavelet dan model polinomial digunakan untuk mengestimasi reflectance dari daun jati belanda. Evaluasi spektrum reflectance asli dengan spektrum keluaran model estimasi reflectance menggunakan kriteria kesalahan terkecil dan kemiripan terbesar. Kata kunci: jati belanda, model polinomial, reflectance, wavelet
Forecasting Saham Perbankan Dengan Penerapan Multilayer Backpropagation Neural Network I Putu Ryan Paramaditya; Cokorda Rai Adi Pramartha; I Gede Arta Wibawa; I Gede Santi Astawa; Ida Bagus Gede Dwidasmara; I Dewa Made Bayu Atmaja Darmawan
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 4 (2024): JELIKU Volume 12 No 4, May 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2024.v12.i04.p02

Abstract

The use of the Neural Network algorithm with Backpropagation is used to predict stock price data based on the closing price of the following day, as a reference for buying shares in the future. The dataset used is of the time-series type, stock data for the state-owned banking category comes from Yahoo Finance such as Bank BNI (BBNI). Where from the results of the model training carried out, the lowest loss was 0.0011 at epoch 29, 33, 41, 43, 46, 47, and 49 and the highest was 0.0243 at epoch 0. The lowest Val Loss was 0.0011 at epoch 5, 10, and 46 and the highest was 9.555 at epoch 44. The model test score results showed a Median Absolute Error (MAE) of 85.57 and a Mean Absolute Error Percent (MAE%) of 1.97%. Root Mean Squared Error (RMSE) is 103.85 and Root Mean Squared Error Percent (RMSE%) is 2.39%. This score is considered good because it is below 50%. Prediction results reach an average of above 90%. To get the best prediction results, the percent change must be above -4.35% and the percentage above 95.65%.
Implementasi Algoritma Naïve Bayes Terhadap Klasifikasi Ulasan Aplikasi Tokopedia Yauw James Fang Dwiputra Harta; I Gede Arta Wibawa
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2023.v12.i03.p08

Abstract

Tokopedia has an average number of visitors per month which is 149.67 visitors. In addition, the Tokopedia application has been downloaded by more than 100 million users with 6.34 million reviews and received a rating of 4.7 out of 5. This study aims to classify the positive and negative reviews of the Tokopedia application on the Google Playstore. The results of the 2000 test data testing obtained 842 positive reviews and 1158 negative reviews. This means the percentage for positive reviews is only 42.1%, in contrast to negative reviews of 57.1%. The performance generated in this test against 2000 testing data is 96.19% accuracy value, with a precision value of 1. While in Class Recall the resulting value is 93.45% (positive class: negative). Then for the AUC value is 0.975.
Analisis Sentimen Berbasis Aspek Terhadap Ulasan Aplikasi Mobile Jkn Dengan Metode Random Forest Dan Information Gain Sebagai Seleksi Fitur Yauw James Fang Dwiputra Harta; I Gede Arta Wibawa; Anak Agung Istri Ngurah Eka Karyawati; Komang Ari Mogi
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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

Abstract

In the rapidly advancing digital age, applications have become integral to daily life. This study focuses on aspect-based sentiment analysis of reviews for the Mobile JKN application using the Random Forest and Information Gain methods. This technological approach is vital for understanding user opinions, guiding further improvements and developments. Google Play Store review data is employed, with rating scores serving as guides for sentiment classification. The study aims to provide in-depth insights into sentiments and aspects influencing Mobile JKN application reviews. Through this approach, the quality of healthcare services delivered via the application is anticipated to be continually enhanced.
Pembangunan Aplikasi Pengenalan Kualitas Rasa Buah Jeruk Siam Kintamani Menggunakan GLCM dan K-NN Berbasis User Centered Design (UCD) Putu Bagus Dio Pranata; I Gede Arta Wibawa; Made Agung Raharja; I Gusti Ngurah Anom Cahyadi Putra
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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

Abstract

Buah Jeruk Siam Kintamani merupakan salah satu komoditas unggulan yang memiliki variasi kualitas rasa yang signifikan. Oleh karena itu, diperlukan suatu alat yang dapat membantu pengguna dan calon konsumen, dalam mengenali kualitas rasa buah dengan cepat dan akurat. Metode GLCM digunakan untuk mengekstraksi fitur tekstur dari citra buah Jeruk Siam Kintamani, sementara algoritma K-NN akan memproses fitur-fitur tersebut untuk mengklasifikasikan kualitas rasa buah. Pendekatan UCD diterapkan dalam pengembangan aplikasi untuk memastikan bahwa antarmuka pengguna dirancang dengan mempertimbangkan kebutuhan dan preferensi pengguna akhir. Pengujian usability testing dan uji akurasi algoritma Gray Level Co – Occurrence Matrix (GLCM) dan K – Nearest Neighborts (KNN) dilakukan, dengan memanfaatkan hasil pengujian usability, serta akurasi algoritma pengenalan kualitas rasa. Hasil dari penelitian ini memiliki hasil tingkat usability sangat baik, dalam masing – masing aspek yang di uji, yaitu aspek learnability sebesar 80%, efficiency 83%, hasil nilai skor system usability scale (SUS) sebesar 86,3%, dan error defective rate sebesar 14% kemudian dikatakan valid serta reliabel, serta sudah baik dan dapat diterima oleh pengguna aplikasi ini.
Analisis Sentimen Ulasan Aplikasi Solusi Kota Cerdas Menggunakan Algoritma Naïve Bayes dan Support Vector Machine (SVM) dengan Seleksi Fitur Chi-Square Ni Luh Komang Indira Pramesti; Made Agung Raharja; Ngurah Agus Sanjaya ER; I Gede Arta Wibawa
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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

Abstract

Masyarakat yang semakin bergantung dengan teknologi dalam kegiatan sehari-hari menyebabkan banyaknya aplikasi yang hadir dalam membantu kegiatan ini. Salah satunya adalah aplikasi SpeedID yang berfungsi sebagai solusi kota cerdas. Fitur yang dimiliki beragam, mulai dari verifikasi identitas online, antrean online, manajemen usaha kuliner, manajemen usaha UKM, dan masih banyak lagi. Popularitas aplikasi ini berujung pada banyaknya ulasan yang diberikan oleh pengguna, baik itu positif, negatif, maupun netral. Oleh karena itu, perlu dilakukan suatu analisis sentimen ulasan guna mengetahui pandangan pengguna terhadap aplikasi. Metode analisis sentimen yang digunakan adalah Naïve Bayes (NB) dan Support Vector Machine (SVM) dengan seleksi fitur chi-square. Hasil evaluasi model menunjukkan bahwa seleksi fitur chi-square memiliki pengaruh positif terhadap performa model NB yang ditandai dengan meningkatnya nilai akurasi hingga sebesar 3,12%. Namun, seleksi fitur chi-square ini tidak memiliki pengaruh terhadap performa model SVM yang tidak mengalami peningkatan atau penurunan nilai akurasi saat ditambahkan chi-square.
Co-Authors Adiartika, Made Harry Dananjaya Adiriyanto, Shiennyta Florensia Anak Agung Gede Agung Angga Aditya Anak Agung Istri Ngurah Eka Karyawati Anak Agung Istri Ngurah Eka Karyawati Anak Agung Putra Adnyana Apriana, I Komang Gede Apsari, Made Sri Ayu Bib Paruhum Silalahi Cokorda Rai Adi Pramartha Danandjaya, Gede Bagus Diyarini, Ni Wayan Dwijayana, I Gede Diva Gede Astuti, Luh Giri, Gst. Ayu Vida Mastrika Gst. Ayu Vida Mastrika Giri I Dewa Made Bayu Atmaja Darmawan I Dewa Ngurah Tri Hendrawan I Gede Santi Astawa I Gede Tendi Ariyanto I Gusti Agung Gede Arya Kadyanan I Gusti Ngurah Anom Cahyadi Putra I Ketut Gede Suhartana I Komang Gede Apriana, I Komang Gede Apriana I Made Ryan Prana Dhita I Made Widiartha I Made Widiartha I Putu Ryan Paramaditya I WAYAN SANTIYASA I Wayan Widya Premananda Ida Bagus Gede Dwidasmara Ida Bagus Made Mahendra Ida Bagus Made Mahendra Jaya, Cokorda Gde Teresna Kadek Diah Pramesti Kartika Noviyanti, Komang Komang Ari Mogi Komang Arsa Wiguna Kurnia Amerta, I Made Pegi Luh Arida Ayu Rahning Putri Luh Gede Astuti Michael Tanaya Ngurah Agus Sanjaya ER Ni Luh Komang Indira Pramesti Ni Putu Suci Paramita Ni Wayan Yulia Damayanti Paramita, Ni Putu Suci Pradnyawati, Putu Indah Pradyto, Kadek Dwitya Adhi Prasetyo Adi Utomo Prathama, Wayan Adhitya Premananda, I Wayan Widya Putra, Angga Pramana Putra, I Putu Andi Wiratama Putra, Ida Bhujangga Bagus Dili Putu Bagus Dio Pranata Qaris Ardian Pratama Raharja, Made Agung Setiawati, Ni Ketut Intan Siaka, Made Bayu Maha Krisna Sidi, Widya Dharma Tamba, Andreas Panangian Vyasa, I Made Satya Wiguna, Komang Arsa Wijaya, Arvanchrist Charlie Wiratama Putra, I Putu Andi Wisnawa, Agus Yauw James Fang Dwiputra Harta Yauw, Yauw James Fang Dwiputra Harta