Recently Published
Change Detection in Multi\u002Dtemporal Images Using Multistage Clustering for Disaster Recovery Planning Image
Journal article

Change Detection in Multi-temporal Images Using Multistage Clustering for Disaster Recovery Planning

Face Recognition Using Complex Valued Backpropagation Image
Face Recognition Using Complex Valued Backpropagation Image

Face Recognition Using Complex Valued Backpropagation

Least Squares Support Vector Machines Parameter Optimization Based on Improved Ant Colony Algorithm for Hepatitis Diagnosis Image
Least Squares Support Vector Machines Parameter Optimization Based on Improved Ant Colony Algorithm for Hepatitis Diagnosis Image

Least Squares Support Vector Machines Parameter Optimization Based on Improved Ant Colony Algorithm for Hepatitis Diagnosis

Automatic Determination of Seeds for Random Walker by Seeded Watershed Transform for Tuna Image Segmentation Image
Automatic Determination of Seeds for Random Walker by Seeded Watershed Transform for Tuna Image Segmentation Image

Automatic Determination of Seeds for Random Walker by Seeded Watershed Transform for Tuna Image Segmentation

Eeg Classification For Epilepsy Based On Wavelet Packet Decomposition And Random Forest Image
Eeg Classification For Epilepsy Based On Wavelet Packet Decomposition And Random Forest Image

Eeg Classification For Epilepsy Based On Wavelet Packet Decomposition And Random Forest

A Flexible Sub\u002Dblock in Region Based Image Retrieval Based on Transition Region Image
Journal article

A Flexible Sub-block in Region Based Image Retrieval Based on Transition Region

Inter and Intra Cluster on Self\u002Dadaptive Differential Evolution for Multi\u002Ddocument Summarization Image
Journal article

Inter and Intra Cluster on Self-adaptive Differential Evolution for Multi-document Summarization

Bayesian Bernoulli Mixture Regression Model for Bidikmisi Scholarship Classification Image
Journal article

Bayesian Bernoulli Mixture Regression Model for Bidikmisi Scholarship Classification

Multispectral Dorsal Hand Vein Recognition Based On Local Line Binary Pattern Image
Journal article

Multispectral Dorsal Hand Vein Recognition Based On Local Line Binary Pattern

A Flexible Sub\u002Dblock in Region Based Image Retrieval Based on Transition Region Image
A Flexible Sub\u002Dblock in Region Based Image Retrieval Based on Transition Region Image
Journal article

A Flexible Sub-block in Region Based Image Retrieval Based on Transition Region

Inter and Intra Cluster on Self\u002Dadaptive Differential Evolution for Multi\u002Ddocument Summarization Image
Inter and Intra Cluster on Self\u002Dadaptive Differential Evolution for Multi\u002Ddocument Summarization Image
Journal article

Inter and Intra Cluster on Self-adaptive Differential Evolution for Multi-document Summarization

Bayesian Bernoulli Mixture Regression Model for Bidikmisi Scholarship Classification Image
Bayesian Bernoulli Mixture Regression Model for Bidikmisi Scholarship Classification Image
Journal article

Bayesian Bernoulli Mixture Regression Model for Bidikmisi Scholarship Classification

Multispectral Dorsal Hand Vein Recognition Based On Local Line Binary Pattern Image
Multispectral Dorsal Hand Vein Recognition Based On Local Line Binary Pattern Image
Journal article

Multispectral Dorsal Hand Vein Recognition Based On Local Line Binary Pattern

Most Viewed
A Goal Question Metric (Gqm) Approach for Evaluating Interaction Design Patterns in Drawing Games for Preschool Children Image
Journal article

A Goal Question Metric (Gqm) Approach for Evaluating Interaction Design Patterns in Drawing Games for Preschool Children

In recent years, there has been an increasing interest to use smart devices' drawing games for educational benefit. In Indonesia, our government classifies children age four to six years old as preschool children. Not all preschool children can use drawing games easily. Further, drawing games may not fulfill all Indonesia's preschool children's drawing competencies. This research proposes to use Goal-Question Metric (GQM) to investigate and evaluate interaction design patterns of preschool children in order to achieve the drawing competencies for preschool children in two drawing Android-based games: Belajar Menggambar (in English: Learn to Draw) and Coret: Belajar Menggambar (in English: Scratch: Learn to Draw). We collected data from nine students of a preschool children education in a user research. The results show that GQM can assist to evaluate interaction design patterns in achieving the drawing competencies. Our approach can also yield interaction design patterns by comparing interaction design patterns in two drawing games used.
Sistem Question Answering Bahasa Indonesia Untuk Pertanyaan Non\u002Dfactoid Image
Journal article

Sistem Question Answering Bahasa Indonesia Untuk Pertanyaan Non-factoid

Fokus dari penelitian ini adalah untuk mengembangkan data dan sistem Question Answering (QA) Bahasa Indonesia untuk pertanyaan non-factoid. Penelitian ini merupakan penelitian QA non-factoid pertama untuk Bahasa Indonesia. Adapun sistem QA terdiri atas 3 komponen yaitu penganalisis pertanyaan, pengambil paragraf, dan pencari jawaban. Dalam komponen penganalisis pertanyaan, dengan asumsi bahwa pertanyaan yang diajukan merupakan pertanyaan sederhana, digunakan sistem yang berbasis aturan sederhana dengan mengandalkan kata pertanyaan yang digunakan (“apa”, “mengapa”, dan “bagaimana”). Paragraf diperoleh dengan menggunakan pencarian kata kunci baik dengan menggunakan stemming ataupun tidak. Untuk pencari jawaban, jawaban diperoleh dengan menggunakan pola kata-kata khusus yang ditetapkan sebelumnya untuk setiap jenis pertanyaan. Dalam komponen pencari jawaban ini, diperoleh kesimpulan bahwa penggunaan kata kunci non-stemmed bersamaan dengan kata kunci hasil stemming memberikan nilai akurasi jawaban yang lebih baik, jika dibandingkan dengan penggunaan kata kunci non-stemmed saja atau kata kunci stem saja. Dengan menggunakan 90 pertanyaan yang dikumpulkan dari 10 orang Indonesia dan 61 dokumen sumber, diperoleh nilai MRR 0.7689, 0.5925, dan 0.5704 untuk tipe pertanyaan definisi, alasan, dan metode secara berurutan. Focus of this research is to develop QA data and system in Bahasa Indonesia for non-factoid questions. This research is the first non-factoid QA for Bahasa Indonesia. QA system consists of three components: question analyzer, paragraph taker, and answer seeker. In the component of question analyzer, by assuming that the question posed is a simple question, we used a simple rule-based system by relying on the question word used (“what”, “why”, and “how”). On the components of paragraph taker, the paragraph is obtained by using keyword, either by using stemming or not. For answer seeker, the answers obtained by using specific word patterns that previously defined for each type of question. In the component of answer seeker, the conclusion is the use of non-stemmed keywords in conjunction with the keyword stemming results give a better answer accuracy compared to non-use of the keyword or keywords are stemmed stem only. By using 90 questions, we collected from 10 people of Indonesia and the 61 source documents, obtained MRR values 0.7689, 0.5925, and 0.5704 for type definition question, reason, and methods respectively.
De\u002Didentification Technique for Iot Wireless Sensor Network Privacy Protection Image
Journal article

De-identification Technique for Iot Wireless Sensor Network Privacy Protection

Supervised Machine Learning Model for Microrna Expression Data in Cancer Image
Journal article

Supervised Machine Learning Model for Microrna Expression Data in Cancer

Random Adjustment \u002D Based Chaotic Metaheuristic Algorithms for Image Contrast Enhancement Image
Journal article

Random Adjustment - Based Chaotic Metaheuristic Algorithms for Image Contrast Enhancement

De\u002Didentification Technique for Iot Wireless Sensor Network Privacy Protection Image
De\u002Didentification Technique for Iot Wireless Sensor Network Privacy Protection Image
Journal article

De-identification Technique for Iot Wireless Sensor Network Privacy Protection

Supervised Machine Learning Model for Microrna Expression Data in Cancer Image
Supervised Machine Learning Model for Microrna Expression Data in Cancer Image
Journal article

Supervised Machine Learning Model for Microrna Expression Data in Cancer

Random Adjustment \u002D Based Chaotic Metaheuristic Algorithms for Image Contrast Enhancement Image
Random Adjustment \u002D Based Chaotic Metaheuristic Algorithms for Image Contrast Enhancement Image
Journal article

Random Adjustment - Based Chaotic Metaheuristic Algorithms for Image Contrast Enhancement

Suggested For You
Percepatan Motion Estimation Berbasis Phase Only Correlation Dengan Teknik Full Search Menggunakan Paralel Threading Pada Gpu Image
Journal article

Percepatan Motion Estimation Berbasis Phase Only Correlation Dengan Teknik Full Search Menggunakan Paralel Threading Pada Gpu

Penelitian ini menyajikan penggunaan metode Phase Only Correlation (POC) pada motion estimation dengan teknik full search menggunakan Graphical Processing Unit (GPU). Dengan fungsi POC, seseorang dapat melakukan estimasi translasi motion antara dua blok citra referensi dan citra yang diproses. Full Search berbasis POC adalah algoritma yang membutuhkan waktu proses lama. Hal ini menyebabkan sistem yang dicoba pada penelitian ini memproses fungsi POC pada Graphical Processing Unit (GPU) yang memiliki kelebihan dalam menyelesaikan perhitungan bilangan floating point dibandingkan CPU. Evaluasi dilakukan dengan menghitung kecepatan waktu proses menggunakan GPU pada video resolusi tinggi dengan resolusi hingga 1280x720 pixel. Hasil pengujian menunjukkan bahwa metode yang diselesaikan menggunakan GPU memiliki percepatan hingga hampir dua kali lipat pada ukuran blok POC 256 x 256 daripada menggunakan CPU. This research presents a method using Phase Only Correlation (POC) on the motion estimation with full search technique using the Graphical Processing Unit (GPU). With POC function, someone can estimate the translational motion between two blocks of the reference image and the processed image. POC based Full Search is an algorithm that takes long time process. This leads the system that is used in this research to process the POC function on Graphical Processing Unit (GPU) which has advantages in solving the floating point calculations than the CPU. Evaluation is conducted by calculating the speed of processing time using a GPU on a high-resolution video with resolutions up to 1280x720 pixels. The test results show that the method that is solved using GPU has an acceleration up to nearly twice the size of the POC block 256 x 256 instead of using the CPU.
Journal article

Electrocardiogram Arrhythmia Classification System Using Support Vector Machine Based Fuzzy Logic

Electrocardiogram Arrhythmia Classification System Using Support Vector Machine Based Fuzzy Logic Image
Journal article

Location Analysis on Smart House Using Projective Transformation

Location Analysis on Smart House Using Projective Transformation Image
Journal article

Analysis Resource Aware Framework by Combining Sunspot and Imote2 Platform Wireless Sensor Networks Using Distance Vector Algorithm

Analysis Resource Aware Framework by Combining Sunspot and Imote2 Platform Wireless Sensor Networks Using Distance Vector Algorithm Image
Read more articles