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All Journal Scientific Journal of Informatics Wikrama Parahita : Jurnal Pengabdian Masyarakat International Journal of Applied Sciences and Smart Technologies
C. Kuntoro Adi
Universitas Sanata Darma
Computer Science & IT Economics, Econometrics & Finance Energy Engineering Industrial & Manufacturing Engineering Social Sciences

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An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method Trihartati S., Agustin; Adi, C. Kuntoro
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7918

Abstract

Tuberculosis (TB) is a disease that can cause a death if not recognized or not treated properly. To reduce the death rate of tuberculosis patients, the health experts need to diagnose that disease as early as possible. Based on the main indication data, laboratory test results and the  rontgen photo, Naïve Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Naïve Bayes classifiers predict class membership probabilities with a class that has the highest probability value. The output of the system is an identification Tuberculosis type of the patients. Testing of the system using 237 data sample with variation of cross-validation in 3, 5, 7 and 9-fold cross validation gives an average accuracy 85,95%.
An Identification of Tuberculosis (Tb) Disease in Humans using Nave Bayesian Method Trihartati S., Agustin; Adi, C. Kuntoro
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7918

Abstract

Tuberculosis (TB) is a disease that can cause a death if not recognized or not treated properly. To reduce the death rate of tuberculosis patients, the health experts need to diagnose that disease as early as possible. Based on the main indication data, laboratory test results and the rontgen photo, Nave Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Nave Bayes classifiers predict class membership probabilities with a class that has the highest probability value. The output of the system is an identification Tuberculosis type of the patients. Testing of the system using 237 data sample with variation of cross-validation in 3, 5, 7 and 9-fold cross validation gives an average accuracy 85,95%.
An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method Trihartati S., Agustin; Adi, C. Kuntoro
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7918

Abstract

Tuberculosis (TB) is a disease that can cause a death if not recognized or not treated properly. To reduce the death rate of tuberculosis patients, the health experts need to diagnose that disease as early as possible. Based on the main indication data, laboratory test results and the  rontgen photo, Naïve Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Naïve Bayes classifiers predict class membership probabilities with a class that has the highest probability value. The output of the system is an identification Tuberculosis type of the patients. Testing of the system using 237 data sample with variation of cross-validation in 3, 5, 7 and 9-fold cross validation gives an average accuracy 85,95%.
Backpropagation Neural Network for Book Classification Using the Image Cover I Putu Budhi Darma Purwanta; Cyprianus Kuntoro Adi; Ni Putu Novita Puspa Dewi
International Journal of Applied Sciences and Smart Technologies Volume 02, Issue 02, December 2020
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v2i2.2653

Abstract

Artificial Neural Networks are known to provide a good model forclassification. The goal of this research is to classify books in Bahasa (Bahasa Indonesia) using its cover. The data is in the form of scanned images, each with the size of 300 cm height, 130 cm width, and 96 dpi image resolution the research conducted features extraction using image processing method, MSER (Maximally Stable Externally Regions) to identify the area of book title, and Tesseract Optical Character Recognition (OCR) to detect the title. Next, features extracted from MSER and OCR are converted into a numerical matrix as the input to the Backpropagation Artificial Neural Network. The accuracy obtained using one hidden layer and 15 neurons is 63.31%. Meanwhile, the evaluation using 2 hidden layers with a combination of 15 and 35 neurons resulted in accuracy of 79.89%. The ability of the model to classify the book was affected by the image quality, variation, and number of training data.
Pemanfaatan Teknologi Informasi untuk Pembuatan Materi, Pendistribusian Materi dan Evaluasi Pembelajaran bagi Guru Sekolah Dasar Kanisius Kalasan Eko Hari Parmadi; C. Kuntoro Adi; S. Widanarto Prijowuntato
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2022): November 2022
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v6i2.4039

Abstract

Pandemi Covid-19 mempengaruhi berbagai bidang seperti ekonomi, kesehatan, pariwisata, industri, termasuk pendidikan. Di bidang pendidikan, banyak guru maupun siswa yang tergagap karena tidak terbiasa menggunakan teknologi informasi untuk kegiatan pembelajaran. Permasalahan yang dihadapi oleh guru-guru SD Kanisius Kalasan adalah rendahnya pemanfaatan teknologi informasi bagi pembuatan materi ajar, belum optimalnya distribusi materi ajar ke siswa, belum digunakannya teknologi informasi untuk evaluasi pembelajaran. Berdasarkan situasi yang ada, maka disusun program pengabdian masyarakat yang bertujuan untuk memanfaatkan teknologi dalam pembuatan materi, pendistribusian materi, dan Evaluasi Pembelajaran. Tahapan kegiatan PKM ini terdiri dari pelatihan dan praktik langsung secara terbimbing serta tugas secara mandiri. Keberhasilan program ini dilihat dari kenaikan kemampuan peserta didik yang diukur dengan menggunakan pretest dan posttest. Hasil pengabdian ini menunjukkan bahwa ada peningkatan rata-rata skor kemampuan guru dalam menggunakan teknologi informasi dari 207,86 menjadi 214,29 atau kenaikan rata-rata sebesar 6,43. Kebanyakan guru di SD Kanisius tergolong muda. Mereka memiliki kemampuan beradaptasi dengan perkembangan teknologi informasi.
Co-Authors Agustin Trihartati S., Agustin Eko Hari Parmadi I Putu Budhi Darma Purwanta Ni Putu Novita Puspa Dewi S. Widanarto Prijowuntato