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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJISTECH
Roro Inda Melani
Department Of Informatics, Faculty Of Science And Technology, Universitas Islam Negeri (UIN) Maulana Malik Ibrahim, Malang, Indonesia
Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences

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Hand Gesture Recognition Using Hidden Markov Model Algorithm Melani, Roro Inda
MATICS Vol 9, No 1 (2017): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (760.208 KB) | DOI: 10.18860/mat.v9i1.4126

Abstract

Abstract— Recognizing human hand gesture through the use of INS (Inertial navigation System) sensor, Hidden Markov Model (HMM) was used as a tool to recognize pattern statistically. Employing INS sensor to admit data input , it is assumed that hand gesture could be detected by analizing the acceleration and fluctuation from data sensor and the difference of hand-position in 3-axis. The INS sensor that was being used was came with 6 channels to generate signals of a 3-axis gyroscope and a 3-axis accelerometer. The acceleration fluctuated in three perpendicular directions due to different hand gestures was detected by the accelerometer, while the change of hand-position in 3-axis was detected by gyroscope. Data from sensor was exported to computer via USB (Universal Serial Bus) port.During the stage of data collection, a cut algorithm was developed to pick the most significant part of the sensor data. After finishing data comparison stage, DCT (Discrete Cosine Transform) was selected to transform the signal from time domain to frequency domain. Sequences of calculation were performed to analyze the best sampling frequency to select dominant frequency of every gesture to be picked as parameter value. The parameter value used in HMM as the approach to recognize and differs gestures. Index Terms—3-axis gyroscope, accelerometer, gesture, gesture recognition, hand gesture, human gesture.
QUERY ANSWERING SYSTEM OF SHAHIH HADITH MUTTAFAQUN ‘ALAIH USING INDONESIAN THESAURUS BASED ON QUERY EXPANSION AND NAÏVE BAYES CLASSIFIER Rounaqi, Muhammad Fairuz Zumar; Crysdian, Cahyo; Melani, Roro Inda
MATICS Vol 12, No 1 (2020): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (585.358 KB) | DOI: 10.18860/mat.v12i1.8320

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Abstract— Hadith are all the words, deeds and provisions of the Prophet Muhammad SAW that are used as the second of Islamic law after Al-Quran. The purpose of this study is to make an Information Retrieval system called the Query Answering System is expected to facilitate users in searching and finding the hadith documents as the user's needs. This study implements the Naïve Bayes Classifier method combined with Indonesian thesaurus as a query expansion to find the hadith documents that relevant to the input query. Based on the testing of 50 query data, the test results show that the use of query expansion gives better results than without using query expansion. Where based on testing of the top 1 data without using query expansion obtained an average recall value of 62%, an average precision value of 62%, an average accuracy value of 92.4% and an average value of the f-measure of 62%, while testing using query expansion obtained an average recall value of 66%, an average precision value of 66%, an average accuracy value of 93.2% and an average f -measure value of 66%. Based on the test results, the use of query expansion shows an improvement in the average recall value of 4%, an improvement in the average precision value of 4%, and an improvement in the average accuracy value of 0.8% and an improvement in the average f-measure value of 4% compared on without using query expansion. Index Terms—hadith, information retrieval, query expansion, naïve bayes. 
Co-Authors Agung Teguh Wibowo Almais Cahyo Crysdian Dian Maharani, Dian Fresy Nugroho Hammad, Jehad AH Lestari, Tri Mukti Mochammad Wahyu Firmansyah Muhammad Ridho Nurrahma ‘N, Alfina Pebrianti, Dwi Rounaqi, Muhammad Fairuz Zumar Safitri, Annisa Heparyanti Supriyono Syauqi, A'la Yunifa Miftachul Arif