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Contact Name
Mesran
Contact Email
mesran.skom.mkom@gmail.com
Phone
+6282161108110
Journal Mail Official
mib.stmikbd@gmail.com
Editorial Address
Jalan sisingamangaraja No 338 Medan, Indonesia
Location
Kota medan,
Sumatera utara
INDONESIA
JURNAL MEDIA INFORMATIKA BUDIDARMA
ISSN : 26145278     EISSN : 25488368     DOI : http://dx.doi.org/10.30865/mib.v3i1.1060
Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer science)
Articles 3 Documents
Search results for , issue "Vol 1, No 3 (2017): September 2017" : 3 Documents clear
PENERAPAN TEOREMA BAYES DALAM MEMPREDIKSI BAYI TERLAHIR CACAT Ratnasari, Desi; Hasibuan, Nelly Astuti
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 1, No 3 (2017): September 2017
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v1i3.523

Abstract

The development of computer-based medical systems has increased considerably today. One of the health problems that often interfere with pregnant women is that the risk of a baby born with a disability is often overlooked because most people do not understand that a baby can be born with a disability and assume that all babies have a disability after being born not before birth, but actually born babies are quite dangerous and can result in death. This study aims to build an expert-based application that can be used to make early predictions of birth defects. This expert-based application, which mimics the workings of an expert or physician in analyzing the symptoms. Type Inference engine (machine reasoning) used in the research Bayes Theorem is a theory to generate parameter estimation by combining information from samples and other information that has been available previously.
SISTEM PAKAR DIAGNOSA PENYAKIT TANAMAN KARET MENGGUNAKAN METODE CERTAINTY FACTOR Zainab, Zainab
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 1, No 3 (2017): September 2017
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v1i3.527

Abstract

Diseases in rubber plants often cause economic losses in rubber plantations. The resulting losses are not only the loss of yield due to crop damage but also the costs incurred in the control effort. The expert system is a software package or computer programming package intended to provide health and aids in solving problems in certain areas of specialization such as science, engineering, mathematics, agriculture, medicine, and so on. In accordance with the development of information technology, the expertise of rubber plant diseases needs to be implemented into a computer application using expert system method, namely: Certainty Factor (CF). The Certainty Factor method will display a selection of symptoms that can be selected by the user, where each choice of symptoms will take the user to the next symptom option until the final result. At the end result, the system will display the user's symptom choices, and the illness suffered. 
IMPLEMENTASI MEAN FILTERING UNTUK MENGURANGI NOISE PADA CITRA DIGITAL Manalu, Juliadi; Sinurat, Sinar
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 1, No 3 (2017): September 2017
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v1i3.545

Abstract

Improved image quality (image enhancement) is one of the early processes in image processing (image preprocessing). Improved quality is required because often the image used as the subject of discussion has poor quality, for example, the image is noise at the time of transmission through the transmission line, the image is too bright/dark, the image is less sharp, blurred, and so on. The mean filtering method is a filtering technique that works by replacing the intensity of a pixel with the average pixel value of pixels from neighboring pixels. If an image f (x, y) of size M x N is filtered by filter h (x, y) it will produce the image g (x, y), where filter h (x, y) is a matrix containing 1 / filter size. Mean filter the mean value of the data set. The mean filtering used for this smoothing effect is a type of spatial filtering, which in the process involves surrounding pixels.

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