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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Maksum Ro’is Adin Saf
Politeknik Caltex Riau
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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PENGEMBANGAN ALGORITMA PENGENALAN JENIS KALIMAT PADA BAHASA ARAB DENGAN METODE AFFIX MAPPING Maksum Ro’is Adin Saf; Dini Hidayatul Qudsi; Istianah Muslim
Jurnal Teknologi Informasi dan Terapan Vol 4 No 2 (2017)
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v4i2.66

Abstract

Arabic is one of the most popular languages in Indonesia which is Muslim population being majority. Ability to recognize the types of sentence in Arabic Language is one of basic topic in Arabic language studying. The type of sentence in Arabic is known from the first word in the sentence, but often the first word of a sentence is not the original words, so it can not be found directly in the dictionary. In this reseach, the Arabic Stemming algorithm was modified to find the type of the word using affixes include to the word, this method refers to the rules in Sharf science, therefore this method is named as Affix Mapping Algorithm. The algorithm that has been prepared is tested using Cyclomatic Complexity method and the result shows that the independent path obtained is 5, from the result it can be concluded that the algorithm is structured well, very easy to test, and last long.
Aplikasi Pengenalan Nama Surah pada Juz ke 30 Kitab Suci Al-Qur’an Menggunakan Speech Recognition Dhimas Sena Rahmantara; Kartina Diah Kesuma Wardhani; Maksum Ro’is Adin Saf
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 2 No 1 (2018): April 2018
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (764.425 KB) | DOI: 10.29207/resti.v2i1.285

Abstract

Al-Qur’an is a scripture which contains the saying of Allah Subhanahu Wa Ta’aala and was revealed to Prophet Muhammad. The 30th juz is the juz that exists in the Al-Qur’an. When studying how to read Al-Qur’an well, the first thing that is learned is reading and memorizing surahs in the 30th juz. Nevertheless, there is a problem in remembering or knowing the surah name and the verse which are in the 30th juz. An android application was developed in order to recognize the surah names in the 30th juz by utilizing speech recognition technology to overcome that problem. Markov Model (Markov Chain) algorithm was implemented in this application. This algorithm will process user’s speech and compute probability of the surah name that was spoken. Speech detection testing gave result that the highest accuracy of application in recognizing the speeches was in the environment without noise with the accuracy of 100% in the most ideal distance is 50 cm for male and for female user. Based on the blackbox testing result, all functionalities of the application have functionated well. Control flow testing gave result that the value is 7 which indicates that the code is simple and well written. 87,74% respondents answered, by filling up the questionnaires, that the application is useful in order to make user knows better about the surah names in the 30th juz.
Pengenalan Kepribadian Seseorang Berdasarkan Pola Tulisan Tangan Menggunakan Jaringan Saraf Tiruan Mutia Fadhilla; Maksum Ro’is Adin Saf; Dadang Syarif Sihabudin Sahid
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 3: Agustus 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1332.807 KB)

Abstract

Graphology is a study of representing personality based on handwriting. Individual’s handwriting is unique and has own feature that it can be analyzed to understand personality. Graphology is used in some fields such as staffing, determining interest and talent. Some researches in graphology using artificial intelligence have been studied before. However, most of the researches still used one handwriting feature and did not classify into personality type. In this study, using some features of handwriting, i.e. left margin, right margin, size, and slant to classify personality type. Personality is classified based on Myers-Briggs Type Indicator (MBTI) using Back Propagation and Learning Vector Quantization method. The result shows that Learning Vector Quantization has better performance, with 90% accuracy, than Back Propagation, which has 82% accuracy.
Co-Authors Dhimas Sena Rahmantara Dini Hidayatul Qudsi Istianah Muslim Kartina Diah K. W. Mutia Fadhilla Sahid, Dadang Syarif Shihabudin