Penyakit yang sering dianggap sepele namun sangat mengganggu adalah penyakit gigi. Umumnya gigi rentan terhadap makanan dan cuaca bila gigi mengalami permasalahan. Dari survey diperoleh sangat minim keinginan penderita sakit gigi berobat ke rumah sakit atau dokter spesialis. Sebuah sistem pakar memperkenalkan implementasi diagnosa penyakit gigi. Sipenderita dapat mengobati sakit gigi dengan arahan dari kommputer (pakar). Pakar sebagai sumber data basis pengetahuan diwakilkan komputer mendiagnosa penyakit. Menurut pakar gigi ada 7 jenis penyakit: Erosi Gigi, Ginggi-vitis, Pulpi-tis, Abses Gigi, Periodo-ntitis, Karies Gigi, Hali-tosis, dan Sindrom Gigi Retak. dengan 37 gejala (dikodekan sesuai kriteria). Dalam Naïve Bayes, pengklasifikasian menggunakan metode probabilitas dan statistik. Perhitungan Naïve Bayes berdasarkan data penyakit dan data gejala dengan variable Data, Hipotesa dan Probabilitas. Hasil dari penelitian ini adalah sebuah diagnosa terhadap penyakit gigi dengan hasil nilai probabilitas tertinggi. Nilai probabilitas dari gejala penyakit gigi diperoleh berdasarkan pengalaman seorang pakar atau dokter gigi. Dari data yang diuji sesuai kasus diketahui probabilitas Penyakit Halitosis adalah yang tertinggi dari penyakit lain yaitu 0.29646 atau 29.64%.
Malnutrition is a disease with a growing number of sufferers every year in Indonesia. The percentage of malnutrition in Indonesia is around 3.4%. The characteristics of malnutrition indicate that growth is not optimal, intellectual development is not optimal, the appearance of visual impairment, fatigue, lack of appetite, abnormal bone shape, easy pain. The limited number of medical personnel can be assisted by the application of an expert system without intending to replace the Expert. Expert system is a system (knowledge machine) that is able to replace the function of expertise. This study aims to detect malnutrition at the age of 1-3 years (toddlers). using the Naïve Bayes Clasifier algorithm. In this study known 3 types of diseases based on symptoms, namely Kwarshiorkor (P1), Marasmik-Kwarshiorkor (P2), Marasmus (P3) with 24 symptoms of malnutrition. The results showed the highest multiplication results from the naive bayes classification were a type of malnutrition suffered by patients. Detection results can be used as initial information on the detection of malnutrition.
Overtime is a part of a project plan that is intended to complete a production process that is not possible to be completed in a normal working day. Overtime work must be balanced with the readiness of supporting factors including labor (employees), work materials and tools that are suitable for the needs of the job. To overcome these supporting factors, it is necessary to finance the payment of labor (wages). The problem that arises when determining employee overtime is the influence of overtime work on work productivity and the condition of employees in carrying out overtime tasks. How to determine overtime for employees will use the Analytical Hierarchy Process (AHP) method. Indicators used in determining employee overtime are the criteria for weighting. The indicator for determining overtime employees consists of three criteria, namely attitude, ability and contribution. The main output of the system, contains an alternative that has the highest weight so that the name of the employee who has to work overtime to meet the needs of the company is obtained. The advantage of the AHP method is that it makes it easy to calculate performance criteria based on priority considerations that can facilitate the determination of overtime employees.
Message encoding is an art and science to maintain news or data, learn mathematical techniques related to aspects of information security such as data confidentiality, data validity, data integrity, and data authentication. The process of encoding and inserting messages with the Vigenere Cipher and LSB methods is the first step in inputting text and keyword files, then text files and keywords are converted into decimal numbers, then processed according to the Vigenere Cipher formula, the ciphertext is then transformed into binary form it is inserted into the image by means of each bit of the ciphertext in the last bit of the image, so it is expected that the data sent is not easy to read by third parties. The vigenere cipher algorithm and the LSB (Last Significant Bit) technique can be used as a solution for the security of secret messages that are inserted into the image, can be re-revealed exactly the same as the original form and do not experience the slightest damage.
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