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All Journal TEKNIK INFORMATIKA Query : Jurnal Sistem Informasi
Anif Hanifa Setianingrum
UIN Syarif Hidayatullah Jakarta
Computer Science & IT Control & Systems Engineering

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IMPLEMENTASI ALGORITMA MULTINOMIAL NAIVE BAYES CLASSIFIER Anif Hanifa Setianingrum; Dea Herwinda Kalokasari; Imam Marzuki Shofi
JURNAL TEKNIK INFORMATIKA Vol 10, No 2 (2017): Jurnal Teknik Informatika
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (855.54 KB) | DOI: 10.15408/jti.v10i2.6822

Abstract

ABSTRAK Informasi diperkirakan lebih dari 80% tersimpan dalam bentuk teks tidak terstruktur. Oleh karena itu, dibutuhkan sistem pengelolaan teks yaitu dengan metode text mining yang diyakini memiliki potensial nilai komersial tinggi. Salah satu implementasi dari text mining yaitu klasifikasi teks. Tidak hanya dokumen, pemanfaatan klasifikasi juga digunakan pada surat. Peneliti mengkaji Multinomial Naive Bayes Classifier untuk mengklasifikasi surat keluar sehingga dapat menentukan nomor surat secara otomatis. Sistem klasifikasi didukung dengan confix-stripping stemmer untuk menemukan kata dasar dan TF-IDF untuk pembobotan kata. Pengujian diukur dengan menggunakan confusion matrix. Dari hasil pengujian menunjukkan bahwa implementasi Multinomial Naive Bayes Classifier pada sistem klasifikasi surat memiliki tingkat accuracy, precision, recall, dan F-measure berturut-turut sebesar 89,58%, 79,17%, 78,72%, dan 77,05%.  ABSTRACT The information estimated that more than 80% is stored in the form of unstructured text. Therefore, it takes a text management system, namely text mining method is believed to have high potential commercial. One of text mining implementation is text classification. Not only documents, the use of classification is also used in official letter. Researcher examined Multinomial Naive Bayes Classifier to classify the letter so it can determine the letters classification code automatically. The classification system is supported by confix-stripping stemmer to find root and TF-IDF for term weighting. The test used by confusion matrix of a classified as a measure of its quality. The test results showed that the implementation of Multinomial Naive Bayes Classifier on letter classification system has a level of accuracy, precision, recall, and F-measure respectively for 89.58%, 79.17%, 78.72% and 77.05%.How to Cite : Setianingrum, A. H. Kalokasari, D.H . Shofi. I. M. (2017). IMPLEMENTASI ALGORITMA MULTINOMIAL NAIVE BAYES CLASSIFIER. Jurnal Teknik Informatika, 10(2), 109-118. doi: 10.15408/jti.v10i2.6822Permalink/DOI: http://dx.doi.org/10.15408/jti.v10i2.6822
Implementasi Algoritma Boyer Moore Pada Aplikasi Kamus Istilah Kebidanan Berbasis Web Rizky Ivan Darmawan; Anif Hanifa Setianingrum; Arini Arini
Query: Journal of Information Systems VOLUME: 02, NUMBER: 01, APRIL 2018
Publisher : Program Studi Sistem Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1022.74 KB)

Abstract

The lack of understanding in obstetrics and limit of instructional media has become one of the factors in the making of dictionary application of midwifery. The current dictionary is still a thick book with many terms in it and difficult to use. dictionary midwifery terms have a weakness in the search process, because users should search for words and terms manually by opening pages per page on the dictionary and existing data could not be changed.Keywords: Algorithm, Boyer Moore, Midwifery Dictionary.
Hand-Gesture Detection Using Principal Component Analysis (PCA) and Adaptive Neuro-Fuzzy Inference System (ANFIS) Anif Hanifa Setianingrum; Arifa Fauzia; Dzul Fadli Rahman
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v15i1.24869

Abstract

Sign language is a non-verbal language that Deaf persons exclusively count on to connect with their social environment.The problem that occurs in two-way communication using sign language is a misunderstanding when learning new terms that need to be taught to deaf and mute people. To minimize these misunderstandings, a system is needed that can assist in correcting hand gestures so that there is no misinterpretation in teaching new terms. Several optimality properties of PCA have been identified namely: variance of extracted features is maximized; the extracted features are uncorrelated; finds best linear approximation in the mean-square sense and maximizes information contained in the extracted feature. The classification uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. From the results of experiments with different image size variables, the largest accuracy was obtained with an image size of 449x449 of 76.20%. While the lowest accuracy of 52.38% is obtained through scenarios with image sizes of 57x57 and 45x45. Therefore, differences in the use of image sizes have an influence on the accuracy of hand signal prediction. The smaller the size given, the smaller the accuracy obtained. This is indicated by the decreasing accuracy value when given a smaller size in the four scenarios that have been studied.
Co-Authors Arifa Fauzia Arini Arini Dea Herwinda Kalokasari Dzul Fadli Rahman Rizky Ivan Darmawan Shofi, Imam Marzuki