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All Journal KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Jurnal Pseudocode Journal of ICT Research and Applications SINTECH (Science and Information Technology) Journal WIDYA LAKSANA Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Indonesian Journal of Electrical Engineering and Computer Science INSERT: Information System and Emerging Technology Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi
I Md. Dendi Maysanjaya
Universitas Pendidikan Ganesha
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Other

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Pengembangan Sistem Identifikasi Jenis Kelamin Janin Pada Citra Usg Maysanjaya, I Made Dendi; Kesiman, Made Windu Antara; Wahyuni, Dessy Seri
Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Vol 2, No 1 (2013)
Publisher : Jurusan Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1669.817 KB)

Abstract

Penelitian ini bertujuan untuk: (1) merancang sistem identifikasi jenis kelamin janin pada citra USG, (2) mengimplementasikan sistem identifikasi jenis kelamin janin pada citra USG. Dalam perancangan dan pengimplementasiannya, penelitian ini menggunakan 3 jenis metode atau proses yang terdapat di dalam pengolahan citra digital yaitu: segmentasi citra, ekstraksi fitur, dan pengelompokan data. Inputan serta keluaran dari aplikasi ini adalah citra inputan yang berekstensi bitmap (*.bmp) dan keluarannya berupa informasi mengenai jenis kelamin janin. Pengujian dilakukan pada seluruh sampel yang dijadikan basis pengetahuan. Pada proses pengujian ini diperlukan bantuan dokter terlebih dahulu untuk mengidentifikasi jenis kelamin janin. Dalam merancang dan mengimplementasikan rancangan aplikasi, digunakan metode waterfall atau yang sering disebut dengan classic life cycle model. Implementasi dan pengujian pada penelitian ini adalah suatu Sistem Identifikasi Jenis Kelamin Janin pada Citra USG yang menggunakan bahasa pemrograman Delphi. Dari data hasil uji performansi sistem didapat bahwa sistem mampu mengidentifikasi jenis kelamin janin hingga 66,67% dengan total sampel uji 54 citra USG. Berdasarkan  hasil tersebut, Sistem Identifikasi Jenis Kelamin Janin pada Citra USG cukup  membantu dokter kandungan dalam mengidentifikasi jenis kelamin janin.
PENGEMBANGAN SISTEM IDENTIFIKASI JENIS KELAMIN JANIN PADA CITRA USG Dendi Maysanjaya, I Made
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol 1, No 3 (2012)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v1i3.19524

Abstract

This study aimed at: (1) designing the identification system of fetus genders’ at USG image, and (2) implementing the identification system of fetus genders’ at USG image. In designing and implementing the system, it was used three main types of operation methods, namely segmentation, features extraction, and data clustering. Input of these applications were image with extent bitmap (*.bmp), and its output is an information about fetus genders’. The test has been done on the entire image sample which has become a knowledge based. In the process of testing, it was initially needed the helping of an obstetrician in identifying the fetus genders’. In designing and implementing the application design, it was used a waterfall method which is usually called as a classic life cycle model. This is a classic model which creates the software systematically and sequentially that includes some stages namely: (1) requirements definition, (2) system and software design, (3) implementation and unit testing, and (4) integration and testing system.  The implementation and testing in this study was an identification system of fetus genders’ at USG image that were using a Delphi program. Based on the data of the performance system test about the accuracy of the system when identified the fetus genders’, it was found that until 66.67% could be identified well from 54 USG image sample. In this case, the identification system of the fetus genders’ was very helpful for obstetricians when they would be identifying the fetus genders’.  
PELATIHAN PENGGUNAAN KAHOOT SEBAGAI MEDIA PEMBELAJARAN BERBASIS GAMIFIKASI BAGI GURU-GURU SMK SE-KECAMATAN GEROKGAK Listartha, I Made Edy; Darmawiguna, I Gede Mahendra; Pradnyana, I Made Ardwi; Pradnyana, Gede Aditra; Maysanjaya, I Made Dendi; Driya, Putu Dhanu; Dharma Putra, I Gede Wira; Putu Setiari, Gusti Ayu
JURNAL WIDYA LAKSANA Vol 9, No 1 (2020)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (309.92 KB) | DOI: 10.23887/jwl.v9i1.22369

Abstract

Gamifikasi merupakan sebuah teknik yang menjadi tren dewasa ini, namun masih sedikit para pengajar yang belum dapat menerapkan media pembelajaran berbasis gamifikasi ini. Dari hasil jajak pendapat yang dilakukan terhadap 33 pengajar SMK Se-Gerokgak, terlihat hanya 17 pengajar yang mengetahui media pembelajaran berbasis gamifikasi. Kemudian, terlihat 45.5% pengajar sudah mengetahui media pembelajaran berbasis gamifikasi Kahoot, namun hanya 27.3% pengajar dari total 33 responden pengajar yang menggunakan media pembelajaran Kahoot. Tim pelaksana berhasil melaksanakan kegiatan pengabdian yang ditujukan untuk semua tenaga pengajar SMK sekecamatan Gerokgak yang dilaksanakan pada 15 dan 16 November 2019 di SMK N 1 Gerokgak. Dari 32 guru yang ikut dalam proses pelatihan menggunakan Kahoot ini, didapatkan hasil dari jajak pendapat bahwa 100% guru sudah bisa menggunakan media pembelajaran Kahoot, sebanyak 96.9% yakin media pembelajaran berbasis gamifikasi dapat membantu kegiatan pengajaran mereka dan sebanyak 93.8% akan menggunakan media pembelajaran Kahoot sebagai penunjang kegiatan pembelajaran.
PELATIHAN PENGGUNAAN E-LEARNING SCHOOLOGY BAGI GURU SMK SE-KECAMATAN GEROKGAK Maysanjaya, I Made Dendi; Pradnyana, I Made Ardwi; Listartha, I Made Edy; Pratiwi, Putu Yudia; Kusumadewi, Ni Made Ayu Mita; Walhidayah, Irfan; Yasa, I Gede Agus Sukariana; Cahyadi, Kadek Wawan
JURNAL WIDYA LAKSANA Vol 10, No 2 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.13 KB) | DOI: 10.23887/jwl.v10i2.24977

Abstract

E-learning merupakan terobosan dalam meningkatkan kualitas pembelajaran. Beragam jenis learning management system (LMS) telah dikembangan dan digunakan, salah satunya adalah schoology. Meski demikian masih ada guru, khususnya guru SMK di Kecamatan Gerokgak yang sama sekali belum pernah menggunakan LMS. Sementara ada beberapa guru yang sudah pernah menggunakan LMS, menyatakan bahwa LMS yang digunakan masih memiliki beberapa kelemahan dan cenderung tidak stabil. Berdasarkan permasalahan tersebut dirancanglah sebuah kegiatan pelatihan untuk guru SMK sebanyak 46 orang, dan berasal dari beberapa SMK di Kecamatan Gerokgak. Metode pengabdian yang dilakukan terdiri atas lima tahap kegiatan, yang terdiri atas penentuan lokasi, persiapan, pelatihan, evaluasi, dan pelaporan kegiatan. Dari hasil pengabdian yang dilakukan, sebanyak 95,7% menyatakan sudah bisa menggunakan fitur schoology dan merasakan kebermanfataannya, serta 73,9% menyatakan akan menggunakannya sebagai media pendukung proses pembelajaran.
PENGEMBANGAN SISTEM IDENTIFIKASI JENIS KELAMIN JANIN PADA CITRA USG I Made Dendi Maysanjaya
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 1 No. 3 (2012)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v1i3.19524

Abstract

This study aimed at: (1) designing the identification system of fetus genders’ at USG image, and (2) implementing the identification system of fetus genders’ at USG image. In designing and implementing the system, it was used three main types of operation methods, namely segmentation, features extraction, and data clustering. Input of these applications were image with extent bitmap (*.bmp), and its output is an information about fetus genders’. The test has been done on the entire image sample which has become a knowledge based. In the process of testing, it was initially needed the helping of an obstetrician in identifying the fetus genders’. In designing and implementing the application design, it was used a waterfall method which is usually called as a classic life cycle model. This is a classic model which creates the software systematically and sequentially that includes some stages namely: (1) requirements definition, (2) system and software design, (3) implementation and unit testing, and (4) integration and testing system.  The implementation and testing in this study was an identification system of fetus genders’ at USG image that were using a Delphi program. Based on the data of the performance system test about the accuracy of the system when identified the fetus genders’, it was found that until 66.67% could be identified well from 54 USG image sample. In this case, the identification system of the fetus genders’ was very helpful for obstetricians when they would be identifying the fetus genders’.  
Revealing the Characteristics of Balinese Dance Maestros by Analyzing Silhouette Sequence Patterns Using Bag of Visual Movement with HoG and SIFT Features Made Windu Antara Kesiman; I Made Dendi Maysanjaya; I Made Ardwi Pradnyana; I Made Gede Sunarya; Putu Hendra Suputra
Journal of ICT Research and Applications Vol. 15 No. 1 (2021)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2021.15.1.6

Abstract

The aim of this research was to reveal and explore the characteristics of Balinese dance maestros by analyzing silhouette sequence patterns of Balinese dance movements. A method and complete scheme for the extraction and construction of silhouette features of Balinese dance movements are proposed to enable performing quantitative analysis of Balinese dance movement patterns. Two different feature extraction methods, namely the Histogram of Gradient (HoG) feature and the Scale Invariant Features Transform (SIFT) descriptor, were used to build the final feature, called the Bag of Visual Movement (BoVM) feature. This research also makes a technical contribution with the proposal of quantifying measures to analyze the movement patterns of Balinese dances and to create the profile and characteristics of dance maestros/creators. Eight Balinese dances from three different Balinese dance maestros were analyzed in this work. Based on the experimental results, the proposed method was able to visually detect and extract patterns from silhouette sequences of Balinese dance movements. Quantitatively, the pattern measures for profiling of Balinese dances and maestros revealed a number of significant characteristics of different dances and different maestros.
IDENTIFIKASI CITRA UKIRAN ORNAMEN TRADISIONAL BALI DENGAN METODE MULTILAYER PERCEPTRON I Gede Rusdy Mahayana Putra; Made Windu Antara Kesiman; Gede Aditra Pradnyana; I Made Dendi Maysanjaya
SINTECH (Science and Information Technology) Journal Vol. 4 No. 1 (2021): SINTECH Journal Edition April 2021
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v4i1.552

Abstract

Balinese ornament carving are a cultural heritage that is owned by especially the Balinese people. However, especially Balinese people only know the shape of the carving without knowing the name and characteristics of the Balinese traditional carving ornaments. Based on these problems, the researchers have a solution to research about Balinese Ornament Carving Identification by utilizing digital image processing technology. In this study uses Gabor Filter as a feature extraction from the carved image that used and Multilayer Perceptron as a classifier. There are 18 (eighteen) classes of Balinese carving ornaments use in this study with a total of dataset is 268 (two hundred and sixty eight). The purpose of this study was to determine the level of identification  accuracy  of Balinese ornament carving with Multilayer Perceptron method. In the implementation using digital image processing technic with Multilayer Perceptron method was based on backpropagation learning algorithm with 10560 neuron input layers, 50 neuron hidden layers, and 18 neuron output layers as classifier obtained the accuracy for testing is 43%. Classification testing based on k-fold cross validation with K=5 results in average accuracy of 41.14% with optimum accuracy of 56% and accuracy testing with Confusion Matrix obtained the accuracy 43.3%, sensitivity 42.68% and specificity 96.87%. 
Pengembangan Sistem Identifikasi Jenis Kelamin Janin Pada Citra Usg I Made Dendi Maysanjaya; Made Windu Antara Kesiman; Dessy Seri Wahyuni
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 2 No. 1 (2013)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v2i1.9754

Abstract

Penelitian ini bertujuan untuk: (1) merancang sistem identifikasi jenis kelamin janin pada citra USG, (2) mengimplementasikan sistem identifikasi jenis kelamin janin pada citra USG. Dalam perancangan dan pengimplementasiannya, penelitian ini menggunakan 3 jenis metode atau proses yang terdapat di dalam pengolahan citra digital yaitu: segmentasi citra, ekstraksi fitur, dan pengelompokan data. Inputan serta keluaran dari aplikasi ini adalah citra inputan yang berekstensi bitmap (*.bmp) dan keluarannya berupa informasi mengenai jenis kelamin janin. Pengujian dilakukan pada seluruh sampel yang dijadikan basis pengetahuan. Pada proses pengujian ini diperlukan bantuan dokter terlebih dahulu untuk mengidentifikasi jenis kelamin janin. Dalam merancang dan mengimplementasikan rancangan aplikasi, digunakan metode waterfall atau yang sering disebut dengan classic life cycle model. Implementasi dan pengujian pada penelitian ini adalah suatu Sistem Identifikasi Jenis Kelamin Janin pada Citra USG yang menggunakan bahasa pemrograman Delphi. Dari data hasil uji performansi sistem didapat bahwa sistem mampu mengidentifikasi jenis kelamin janin hingga 66,67% dengan total sampel uji 54 citra USG. Berdasarkan  hasil tersebut, Sistem Identifikasi Jenis Kelamin Janin pada Citra USG cukup  membantu dokter kandungan dalam mengidentifikasi jenis kelamin janin.
MULTI LAYER PERCEPTRON DAN PRINCIPAL COMPONENT ANALYSIS UNTUK DIAGNOSA KANKER PAYUDARA Made Satria Wibawa; I Made Dendi Maysanjaya
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 7 No. 1 (2018)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v7i1.12909

Abstract

CAD (Computer Aided Diagnosis) merupakan teknik diagnosa berbantuan komputer untuk meningkatkan akurasi hasil diagnosa dari suatu penyakit. CAD telah banyak digunakan untuk diagnosa dari berbagai penyakit, khususnya penyakit kanker payudara. Multi layer perceptron (MLP) sebagai salah metode dari jaringan saraf tiruan telah banyak digunakan untuk klasifikasi kanker payudara. Penelitian ini bertujuan untuk mencari kombinasi parameter paling optimal untuk mendiagnosa kanker payudara. Kombinasi parameter tersebut juga diujikan dengan metode reduksi fitur Principal Component Analysis (PCA). Hasil penelitian menunjukkan bahwa parameter paling optimal adalah fungsi optimisasi RELU serta TANH dengan fitur optimisasi adam dengan tingkat akurasi 0.973
Klasifikasi Pneumonia pada Citra X-rays Paru-paru dengan Convolutional Neural Network I Md. Dendi Maysanjaya
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 2: Mei 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1190.795 KB) | DOI: 10.22146/jnteti.v9i2.66

Abstract

Pneumonia is a lung disease that could be caused by bacteria, viruses, fungi, or parasites. The pulmonary cysts are filled with fluid, causing croup and mucus cough. Usually, observation of the patient's lung condition is performed through X-rays. However, the quality of X-ray images tends to be less than optimal. Therefore, a CAD-based automation system was developed. In this paper, a new chest X-rays dataset for pneumonia cases is classified by using Convolutional Neural Network (CNN). This study examines the CNN performance in handling the new dataset. The data were obtained from the Kaggle platform. In total, there were5,840 images occupied in this study, consisting of 1,575 normal lung images and 4,265 pneumonia lung images. The data were divided into training and testing data, with the amount of data 5,216 and 624 images on each, respectively. The CNN activation function applied the Rectifier Linear Unit (ReLU) function, Adam optimization function, and epoch as many as 200times. Based on the test results, the average accuracy and loss values are sequentially at 89.58% and 47.43%. The results of this test indicate that the CNN method is quite capable of classifying the pneumonia cases.
Co-Authors Ali Djamhuri Cahyadi, Kadek Wawan Dessy Seri Wahyuni Dharma Putra, I Gede Wira Driya, Putu Dhanu E. Elsa Herdiana Murhandarwati Gede Aditra Pradnyana Gede Saindra Santyadiputra, Gede Saindra Hanung Adi Nugroho I Gede Agus Krisna Perdana I Gede Mahendra Darmawiguna I Gede Riyan Ardi Darmawan I Gede Rusdy Mahayana Putra I Gusti Ayu Agung Diatri Indradewi I Made Angga Darma Putra I Made Ardwi Pradnyana I Made Edy Listartha I Made Gede Sunarya Irfanda, Achmad Kadek Suwis Satria Atmaja Komang Jepri Kusuma Jaya Komang Pramayasa Kusumadewi, Ni Made Ayu Mita Made Satria Wibawa Made Windu Antara Kesiman Muhammad Ridwan Noor Akhmad Setiawan Putu Hendra Suputra Putu Setiari, Gusti Ayu Putu Yudia Pratiwi Saraya, Fashan Walhidayah, Irfan Widhia K.Z Oktoeberza Yasa, I Gede Agus Sukariana