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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) snimed Jurnal Teknoin Media Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Gaung Informatika Jurnal Informatika CommIT (Communication & Information Technology) Jurnal Teknologi Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Telematika JUITA : Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi Journal of Information Systems Engineering and Business Intelligence AJIE (Asian Journal of Innovation and Entrepreneurship) INFORMAL: Informatics Journal Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Informatika Upgris Journal of Advanced Civil and Environmental Engineering Sinkron : Jurnal dan Penelitian Teknik Informatika IT JOURNAL RESEARCH AND DEVELOPMENT INOVTEK Polbeng - Seri Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI KACANEGARA Jurnal Pengabdian pada Masyarakat Jiko (Jurnal Informatika dan komputer) ComTech: Computer, Mathematics and Engineering Applications JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik Journal of Appropriate Technology for Community Services Refleksi Pembelajaran Inovatif Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal Indonesian Journal of Electrical Engineering and Computer Science G-Tech : Jurnal Teknologi Terapan Computer Science and Information Technologies JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Ekonomi dan Teknik Informatika Applied Research in Science and Technology Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi
Sri Kusumadewi
Jurusan Teknik Informatika Universitas Islam Indonesia Jl. Kaliurang Km 14,5 Yogyakarta
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Journal : commit communication

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KLASIFIKASI STATUS GIZI MENGGUNAKAN NAIVE BAYESIAN CLASSIFICATION Kusumadewi, Sri
CommIT (Communication and Information Technology) Journal Vol 3, No 1 (2009): CommIT Vol. 3 No. 1 Tahun 2009
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v3i1.506

Abstract

Until recently, Body Mass Index (BMI) has been used as a method for measuring the nutrient state of an individual. Two people having the same weight and height may have different nutrient states. Whenever this occurs, the use of BMI for measuring the nutrient state shall be deemed irrelevant. The anthropometry will be vital in measuring the nutrient state. On the contrary, as the development of IT progresses, so does the improvement of numerical computation. One of the computational algorithms that have been improving is probabilistic reasoning with Naive Bayesian Classification (NBC) as its method. This algorithm is intended to data classification. In this research, the NBC algorithm will be applied for measuring the human nutrient status by using anthropometry data as input system. The result of this research shows that NBC can solve this problem adequately. Research results shows total performance of this system as 93.2%.Keywords: classification, Naive Bayesian Classification (NBC), nutrition
Segmentation of Tuberculosis Bacilli Using Watershed Transformation and Fuzzy C-Means Kurniawan, Rahadian; Muhimmah, Izzati; Kurniawardhani, Arrie; Kusumadewi, Sri
CommIT (Communication and Information Technology) Journal Vol 13, No 1 (2019): CommIT Vol. 13 No. 1 Tahun 2019
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v13i1.5119

Abstract

The easily transmitted Tuberculosis (TB) disease is attributed to the fact that Mycobacterium Tuberculosis (MTB) bacteria/viruses can be transmitted through the air. One of the methods to screen the TB disease is by reading sputum slides. Sputum slides are colored sputum samples of TB patients placed on microscopic slides. However, TB disease microscopic analysis has some limitations since it requires high accuracy reading and well-trained health personnel to avoid errors in the process of interpretation. Furthermore, the number of TB patients in the Primary Health Care (PHC) and the process of manual calculation of bacteria in a field of view often complicate the decision-making in the screening process conducted by the medical staffs. In this paper, the researchers propose the use of Watershed Transformation and Fuzzy C-Means combination to help solve the problem. The researchers collect the photo shooting of three PHC in Indonesia with 55 images of sputum from different TB patients. The assessed results of the proposed method are compared with the opinions of three Microbiology doctors. The comparison shows Cohen’s Kappa Coefficient value of 0.838. It suggests that the proposed method can detect Acid Resistant Bacteria (ARB) although it needs some improvement to achieve higher accuracy.
KLASIFIKASI STATUS GIZI MENGGUNAKAN NAIVE BAYESIAN CLASSIFICATION Sri Kusumadewi
CommIT (Communication and Information Technology) Journal Vol. 3 No. 1 (2009): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v3i1.506

Abstract

Until recently, Body Mass Index (BMI) has been used as a method for measuring the nutrient state of an individual. Two people having the same weight and height may have different nutrient states. Whenever this occurs, the use of BMI for measuring the nutrient state shall be deemed irrelevant. The anthropometry will be vital in measuring the nutrient state. On the contrary, as the development of IT progresses, so does the improvement of numerical computation. One of the computational algorithms that have been improving is probabilistic reasoning with Naive Bayesian Classification (NBC) as its method. This algorithm is intended to data classification. In this research, the NBC algorithm will be applied for measuring the human nutrient status by using anthropometry data as input system. The result of this research shows that NBC can solve this problem adequately. Research results shows total performance of this system as 93.2%.Keywords: classification, Naive Bayesian Classification (NBC), nutrition
Segmentation of Tuberculosis Bacilli Using Watershed Transformation and Fuzzy C-Means Rahadian Kurniawan; Izzati Muhimmah; Arrie Kurniawardhani; Sri Kusumadewi
CommIT (Communication and Information Technology) Journal Vol. 13 No. 1 (2019): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v13i1.5119

Abstract

The easily transmitted Tuberculosis (TB) disease is attributed to the fact that Mycobacterium Tuberculosis (MTB) bacteria/viruses can be transmitted through the air. One of the methods to screen the TB disease is by reading sputum slides. Sputum slides are colored sputum samples of TB patients placed on microscopic slides. However, TB disease microscopic analysis has some limitations since it requires high accuracy reading and well-trained health personnel to avoid errors in the process of interpretation. Furthermore, the number of TB patients in the Primary Health Care (PHC) and the process of manual calculation of bacteria in a field of view often complicate the decision-making in the screening process conducted by the medical staffs. In this paper, the researchers propose the use of Watershed Transformation and Fuzzy C-Means combination to help solve the problem. The researchers collect the photo shooting of three PHC in Indonesia with 55 images of sputum from different TB patients. The assessed results of the proposed method are compared with the opinions of three Microbiology doctors. The comparison shows Cohen’s Kappa Coefficient value of 0.838. It suggests that the proposed method can detect Acid Resistant Bacteria (ARB) although it needs some improvement to achieve higher accuracy.
Co-Authors Abd. Halim Achmad Khodzim Agus Harjoko AGUS RIYANTO Al Amin, Muhammad Zainudin Alatas, Alwi Achmad Alfian Nurlifa Alysia Nurkhalisha Andika, Zikri Dwi Andri Panca Purnama Ardhitya Wiedha Irawan Aridhanyati Arifin Arifianto, July Arkham Zahri Rakhman Arrie Kurniawardhani Bayu Hartono Bediatra, Muhamad Riko Bhaskara, Adwitya Chaela Rosi Budiarti Chandra Putra Pradana Chanifah I. Ratnasari Chanifah Indah Ratnasari Dhina Puspasari Wijaya, Dhina Puspasari Dzikra Rafik Putra Edi Fitriyanto Edi Fitriyanto Elyza Gustri Wahyuni Erlina Marfianti, Erlina FAJAR SETIAWAN Fitri Nugraheni Fitriyanto, Raden Edi Frestiany Regina Putri Geralvin Maheswara Gita Putry Nabilah Gita Putry Nabilah, Gita Putry Hardiyanti, Cicin Hari Purnomo Heksaputra, Dadang Helmanatun Nisa Wulandari Heni Pujiastuti Hepi Wahyuningsih Herman Yuliansyah Idham Guswaludin Intan Ruspita Ipin Prasojo, Ipin Isnatin Miladiyah Izzati Muhimmah Jannah, Helmi Roichatul Kariyam - khanan khanan KHARISMA ERIZON Kholisoh Nur Sinta Kiki Kiki Kukuh Eka Nugraha Kusumaningrum, Trias Pungkur Lia Rosmalia Lia Rosmalia Linda Rosita Lizda Iswari Lusiana Indriasari Sagita Lusiana Indriasari Sagita Magus Sediono Mahesti Rancaksari Mufidah, Nadia Citra Muhamad Arifin, Muhamad Nabila Sholihah, Nabila Nadya Satya Handayani Neny Sulistianingsih Ninki Hermaduanti Numan Numan Nur W. Rahayu Nur Wachid Adi Prasetya Nurhayati Nurhayati Nurlaili Muzayyanah Nurul Bahiyah Nurul Mega Saraswati Pahri, Andi Nur Ilma PandiAstuti, Dien NoorFawziah Parjono, Parjono Prasetyo, Dono Catur Rahadian Kurniawan Rakhmat Wahyu Widiantoro Rani Putriana Rani Putriana, Rani Retantyo Wardoyo Rian Anggraeni Ridho Muktiadi Rika Ismayanti Roma Firmansyah Ruhil Iswara Ruslam, Andri Wahyu Ahmad Sabella, Billy Sagala, Muhammad Zikri Khatami Sagita, Lusiana Indriasari Setya Winarno Shofwan Hanif Sri Hartati sri mulyati Sri Mulyati Sri Winiarti Subayu, Abdi Sujarwo, Ari Sukma Puspitorini Supardianto Supadianto Syafiul Muzid Syaiful Hendra Tedy Rismawan WAHYU PRABOWO Wawan Indarto Wijaya, Guruh Yuantari, Rahma Yuliansyah, Herman Yunita Wisda Tumarta Arif