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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JUTI: Jurnal Ilmiah Teknologi Informasi Transformasi: Jurnal Pengabdian Masyarakat Seminar Nasional Informatika (SEMNASIF) Register: Jurnal Ilmiah Teknologi Sistem Informasi Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) SISFOTENIKA Paradigma JURNAL MEDIA INFORMATIKA BUDIDARMA Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi Jurnal Sisfokom (Sistem Informasi dan Komputer) INTEK: Jurnal Penelitian Jurnal Linguistik Komputasional EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Terapan (J-TIT) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Charity : Jurnal Pengabdian Masyarakat KLIK: Kajian Ilmiah Informatika dan Komputer eProceedings of Engineering Jurnal INFOTEL
Moch Arif Bijaksana
Universitas Telkom, Bandung, Indonesia
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Social Sciences

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Pencarian Kesamaan Redaksional pada Terjemahan Al-Quran Bahasa Indonesia Menggunakan Metode Rule-based Chunking Alfredo Primadita; Moch Arif Bijaksana; Eko Darwiyanto
Jurnal Linguistik Komputasional Vol 3 No 1 (2020): Vol. 3, No. 1
Publisher : Indonesia Association of Computational Linguistics (INACL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1344.604 KB) | DOI: 10.26418/jlk.v3i1.32

Abstract

Al-Quran merupakan kitab suci yang menjadi panutan dan rujukan seluruh umat Muslim di dunia. AlQuran terdiri dari 114 surat, 6236 ayat, dan 77845 kata. Dikarenakan Al-Quran memiliki banyak informasi di dalamnya, salah satu upaya untuk mempermudah pembaca dalam mempelajari dan menyaring informasi dari Al-Quran adalah dengan membuat parafrasa yang singkat dengan mempergunakan sistem Rule-based Chunking. Rule-based Chunking dapat mempersingkat suatu kalimat dengan mengelompokan kata-kata yang dianggap penting berdasarkan aturan tata bahasa. Sistem memiliki input berupa ayat-ayat Al-Quran terjemahan bahasa Indonesia yang sudah dicari Longest Common Substring dan Longest Common Subsequence dengan output berupa himpunan parafrasa. Dari 2341 teks berulang yang didapatkan pada penelitian sebelumnya, telah diperoleh 1261 chunk. Setelah melakukan evaluasi pada sistem, akurasi yang didapatkan adalah 91%, dengan precision 63,5% dan recall 74,4%.
Sistem Pencarian Ayat Al-Quran Berdasarkan Kemiripan Ucapan Menggunakan Algoritma Soundex dan Damerau-Levenshtein Distance Puruhita Ananda Arsaningtyas; Moch. Arif Bijaksana; Said Al Faraby
Jurnal Linguistik Komputasional Vol 1 No 2 (2018): Vol. 1, No. 2
Publisher : Indonesia Association of Computational Linguistics (INACL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (583.631 KB) | DOI: 10.26418/jlk.v1i2.10

Abstract

Developing Set of Word Senses of Vocabulary in Al-Qur’an Neca Aqila; Mochammad Arif Bijaksana
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 1 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i1.2119

Abstract

Al-Qur’an has become the guideline for all Muslims in the world, which makes many Muslims are eager to understand its contents. Nevertheless, Al-Qur’an consist of many words that have more than one meaning, which represent certain difficulties while understanding the meaning itself. As example, the word أَزْوَاجًا has two equivalents as it might be translated either "jodoh" (“mate”) in Surah An-Nahl (16: 72: 6) and "golongan-golongan" (“groups”) in Surah Al-Hijr (15: 88: 8). This case is known as a word sense, a word that has more than one meaning. This research aims to construct the word sense as a set of vocabulary, in order to simplify the vocabulary meaning in Al-Qur’an itself. The data set used in this research is nouns from Al-Qur’an which have been translated into Bahasa. In order to construct the set of word sense, this research grouped the words using Hierarchical Clustering method. The total set of the word senses found is 34 nouns, which contains diverse translation. The F measure from evaluation of this research resulted in an accuracy of 65.85%. The result was obtained based on the conformity between the results of the word senses set by the system and by the linguists. The outcome of this research is, accuracy is low, due to the type and the number data used is limited.
Dependency Parsing for Arabic Quran using Easy-First Parsing Algorithm Alfiya El Hafsa; Mochammad Arif Bijaksana; Arief Fatchul Huda
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 2 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i2.2453

Abstract

Arabic is the main language of Al-Quran. Nowadays, many people are studying the Language of Al-Quran, called Quran Arabic. For the beginners, it is important for them to understand the syntactic relationship in a sentence found in the Qur'an. If they do not understand enough, the interpretation will be different and wrong. It will turn into dangerous because Al-Quran is a source of guidance for Muslims’ life. Dependency parsing is very important for linguistic research, especially for rich languages such as the Arabic Language. This study aims to build dependency parsing, in order to make it easier to get to understand syntactic relationship information in sentences. This study uses a parsing method called deterministic parsing, which the method used is shift-reduce parsing with the Easy-First parsing algorithm. The evaluation used labeled attachment score calculation. The score generated from the evaluation was 69.7, beforehand, the comparison both the system results and the gold standard have been done. 62 sentences found the correct head and relation in each word. The number of words found to be wrong is not more than 3 words in one sentence. Evaluation scores produced are not exorbitant due to the complicated tagset used and lacking test sentences.
Name Disambiguation Analysis Using the Word Sense Disambiguation Method in Hadith Ageng Prasetio; Mochammad Arif Bijaksana; Arie Ardiyanti Suryani
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 2 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i2.2551

Abstract

Name disambiguation is the problem solving process to find similar names in sentences. The ambiguity of names can be found in hadith of Sahih Bukhari, names "Abdullah bin Amru" in hadiths no 27 and “Abdullah bin Amru” in hadith no 58, These names are the same, but there is no proof they are the same person. This problem is the early indication of ambiguity of name in the hadith. Based in this problem, this research aims to find name disambiguation of hadith narrators with classification by considering the perawi chain. To solved this problem the authors used Word Sense Disambiguation (WSD), WSD is a process to assign the same meaning from the sentences, based on the context in which the word appears. To classify several names in the hadith, the authors used KNN algorithm, by combining the WSD and KNN method can reduce the ambiguity of names in hadith. The data used in this study came from the hadith of Sahih Bukhori through the pre-processing stage. After conducting the research showed a collection of hadith numbers with the same name prediction with an accuracy of 99% at k = 1. Thus, this method can be used for name disambiguation.
Building Synonym Sets for English WordNet with Robust Clustering using Links Method Sarah Suryaningsih; Moch Arif Bijaksana; Widi Astuti
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 1 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i1.2063

Abstract

English WordNet is an important synonym set to present the similarity of meanings between words. Synonym Set is built using Oxford Thesaurus which is accessed through lexico.com, which is a part of the lexical database that will be used. After using the extraction process through Oxford Thesaurus it will produce a synonym set with the same meaning between words. The difference between WordNet and ordinary dictionaries is that the word is interconnected with other words. One method employed for this approach is Robust Clustering Using Links method, which is similarity values and synonym sets that have been created to be used to build a lexical database. Therefore the main purpose of the development of the English WordNet is to produce an accurate synonym set using clustering techniques. The evaluation calculation will use the F-measure method and will use the gold standard for the calculation method. With the ROCK method, there is an increase in accuracy output from dataset input. Building the English wordnet is to improve words that can be used to help research and development of other language wordnets with role models using more accurate English wordnets. And the use of ROCK method there is an increase in the accuracy upon results of the development of English wordnet compared to the previous method, which is using hierarchical clustering. The outcome of this study resulted in improved accuracy so that the ROCK method is one of the good methods used in the development of the English wordnet.
Analysis of Name Entities in Text Using Robust Disambiguation Method Muthia Virliani; Moch. Arif Bijaksana; Arie Ardiyanti Suryani
SISFOTENIKA Vol 10, No 2 (2020): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.011 KB) | DOI: 10.30700/jst.v10i2.963

Abstract

Named entities are proper nouns or objects contained in a text, such as a person's name, country name, and others. Names of persons in some text are often ambiguous, which makes it difficult for ordinary people to find out these same names are the same person or not.  An ambiguity of names also found in hadith, like the name Abdullah in hadith number 86 and 2411, that might be the same person or might be different. Based on this problem, then this study focuses on named entity disambiguation, which considered further semantic and lexical relation between a named entity. Expected in the future, it would help people to understand the ambiguity of the name or distinguish ambiguous names. The method used in this research was Robust Disambiguation because, in this method, the context of the named entity considered. The resulted output obtained was in the form of named entity that grouped based on the same person or different person processed with Density-based Spatial Clustering of Applications with Noise.  This research resulted in an accuracy value of 90%, a precision value of 97%, and a recall value of 89% obtained from actual value and predicted value
Analysis Name Entity Disambiguation Using Mining Evidence Method Adelya Astari; Moch. Arif Bijaksana; Arie Ardiyanti Suryani
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (814.724 KB) | DOI: 10.31294/p.v22i2.8196

Abstract

Hadith is the second guideline and source of Islamic teachings after the Qur'an. One of the most Saheeh hadith is the book of Saheeh al-Bukhaari. Hadith Sahih Bukhari has a chain of narrators, hadith numbers, and contents of different contents. This tradition also has science that discusses the history of the narrators of the hadith called the Science of Rijalul Hadith. In the Sahih Bukhari hadith there are the names of the narrators of the hadith who have the same name, causing obligation between names. That makes it difficult for many ordinary people to understand these ambiguous names because it is not yet known whether the two names are the same person or not. So, it raises the problem of a name ambiguation for ordinary people who cannot distinguish whether the name of the narrator is the same person or not. To solve these problems, a solution is built, namely the disambiguation of names to eliminate the ambiguity of the name by checking the name, hadith number, narrators chain, content topics, circles, countries, and companions of the Prophet that are seen from the 3 last names before the Prophet based on the chain of narrators. Also, the solution is assisted by using a method Mining Evidence with several other approaches, i.e. Association label documents, word association labels, context similarity, cosine similarity, and word2vec to obtain all similarity values between name entities. After the similarity values are obtained, the data are grouped using the Clustering algorithm. This system is expected to be able to produce a good system performance with a confusion matrix based on value precision, recall, and accuracy.
Penggunaan Metode Bagging dengan Menerapkan Data Balancing pada Churn Prediction Untuk Perusahaan Telekomunikasi ZK. Abdurahman Baizal; Moch. Arif Bijaksana; Ina Rofi’atun Nasihati
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2009
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Churn Prediction merupakan salah satu aplikasi data mining yang bertujuan untuk memprediksi parapelanggan yang berpotensial untuk churn. Churn Prediction merupakan salah satu kasus kelas imbalance danchurn merupakan kelas minor. Terdapat beberapa cara untuk mengatasi permasalahan imbalance class yangmelekat pada kasus churn ini. Salah satu contohnya dengan cara melakukan balancing terhadap data trainingatau dengan cara menggunakan metode yang khusus dapat menyelesaikan permasalahan imbalance class ini.Analisis yang dilakukan pada penelitian ini adalah mengetahui apakah metode Bagging dan Lazy Baggingdapat dijadikan solusi dalam mengklasifikasikan data churn. Dalam mendukung penelitian ini, dibuatperangkat lunak yang mengimplementasikan metode Bagging, dan Lazy Bagging. Pengujian dilakukan denganmenggunakan data salah satu perusahaan telekomunikasidi Indonesia. Sebagai metode pembanding adalahBoosting Clementine 10.1 dan C5.0 Clementine 10.1. Analisis dilakukan dengan melakukan penghitunganakurasi model churn prediction yang dinyatakan dalam bentuk lift curve, top decile dan gini coefficient serta fmeasureuntuk penghitungan akurasi data yang imbalance. Dari analisa yang dilakukan, metode Bagging dapatmemprediksikan data churn jika dilakukan balancing terlebih dahulu terhadap data training yang digunakan.Tetapi dari parameter lift curve, gini coefficient, ternyata Lazy Bagging menghasilkan nilai yang lebih baikuntuk data yang sangat imbalance (tanpa balancing)Kata kunci : bagging, lazy bagging, boosting , data imbalance, churn prediction, akurasi.
Analisis Pengaruh Metode Over Sampling dalam Churn Prediction untuk Perusahaan Telekomunikasi ZK. Abdurahman Baizal; Moch. Arif Bijaksana; Angelina Sagita Sastrawan
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2009
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Churn prediction adalah suatu cara untuk memprediksi pelanggan yang berpotensial untuk churn. Datamining, khususnya klasifikasi tampaknya dapat menjadi salah satu alternatif solusi dalam membuat modelchurn prediction yang akurat. Namun hasil klasifikasi menjadi tidak akurat disebabkan karena data churnbersifat imbalance. Kelas data menjadi tidak stabil karena data akan lebih condong ke bagian data yangmemiliki komposisi data yang lebih besar. Salah satu cara untuk menangani permasalahan ini adalah denganmemodifikasi dataset yang digunakan atau yang lebih dikenal dengan metode oversampling. Analisis yangdilakukan pada penelitian ini adalah mengetahui bagaimana pengaruh metode oversampling yang digunakanterhadap akurasi prediksi data churn dengan melakukan penghitungan akurasi model churn prediction yangdinyatakan dalam bentuk lift curve, top decile dan gini coefficient serta f-measure untuk penghitungan akurasiprediksi data sebagai data yang imbalance. Hasil yang didapat dari penelitian menunjukkan bahwa metodeoversampling yang menghasilkan data synthetic belum sesuai diterapkan pada data churn, karena cenderungmasih menghasilkan nilai top decile yang kecil. Tetapi secara umum metode oversampling ini mampumeningkatkan akurasi untuk memprediksi data minor. Dengan penerapan metode oversampling, data churnyang memiliki tingkat imbalance yang besar dapat diklasifikasi tanpa mengorbankan data minor yang menjadifokus penelitian. Metode oversampling yang digunakan juga memiliki hasil evaluasi yang berbeda terhadapdataset sebagai data churn dan sebagai data imbalance.Kata kunci: churn prediction, imbalance, sampling, akurasi, evaluasi.
Co-Authors Abdul Raffi Malikul Mulki Abdurrahman, Azzam Ade Romadhony Adelya Astari Aditya Hanif Utama Ageng Prasetio Agni Octavia Agung Wardhana Z. Nasution Akip Maulana Al Faraby, Said Alfiya El Hafsa Alfredo Primadita Ali Ridho Fauzi Rahman Angelina Sagita Sastrawan Annisa Dian Muktiari annisa Imadi Puti Anugerah, Sri Mulyani Aqila, Neca Ardhi Akmaludin Jadhira Arie Ardiayanti Suryani Arie Ardiyanti Arie Ardiyanti Suryani Arief Fatchul Huda Arief Fatchul Huda Arief Fatchul Huda Arini Rohmawati Arlinda Dwi Ardiyani aulia khemas Heikhmakhtiar Bagus Ardisaputra Bambang Ari Wahyudi Bening Suryani Pratiwi Bhudi Jati Prio Utomo Darwiyanto , Eko Dea Delvia Arifin Dhafin Putra Aldi dina juni restina Djusnimar Zultilisna Donni Richasdy Dwi Marlina Sari Dzaky Ikram Dzidny, Dimitri Irfan Eki Rifaldi Eko Darwiyanto Fairuz Ahmad Hirzani Fakhruddin, Muhammad Rafi Falia Amalia Fauzan Ramadhan Fauziah, Salma Fernandy Marbun Floribertus Yericho Pramudya Galih Rizky Prabowo Gde Surya Pramartha Grace Duma Tambunan Hafsa, Alfiya El Huda, Arief Fatchul Huda, Arief Fatchul I Gusti Ayu Chandra Devi I Komang Resnawan Tri Putra I Made Darma Yoga I Nyoman Cahyadi Wiratama I Putu Prima Ananda Ibnu Asror Idzhari Syaeful Ma'mun - Ina Rofi’atun Nasihati Indra Lukmana Sardi Intan Khairunnisa Fitriani IZZAH, NURUL Jihan Ratnasari1 KD Krisna Dwipayana Kemas M Lhaksmana Kemas Muslim Lhaksmana Khalid kurnia sari lingga Kurniawan Adina Kusuma Luh Putri Ayu Ningsih Lukman Abdurrahman Meiditia Mustika Rani Miftahul Adnan Rasyid Mochamad Agung Permana Mohamad Syahrul Mubarok Mubaroq Iqbal Muhamad Jibril Muhammad Adib Imtiyazi Muhammad Althoof Nabalah Muhammad Aris Maulana Muhammad Budi Hartanto Muhammad Fakhri Ar-Razi Muhammad Faris Abdussalam Muhammad Haerunnur Syahnur Muhammad Rizki Chairulloh Muhammad Zidny Naf'an Munirsyah Munirsyah Muthia Virliani Mutia, Aufa Naufal Rasyad Neca Aqila Nisaa' 'Ainulfithri Nur Indrawati, Nur Nurul Izzah Patra , Gifaro Andyano Pramudita Oktaviani Prasetio, Ageng Puruhita Ananda Arsaningtyas Purwita, Naila Iffah Putri Cendikia Rahmad Geri Kurniawan Ramadhyni Rifani Ramanti Dwi Indrapurasih Rendy Andrian Saputra Retno Diah Ayu Ningtias Rifki Wijaya Riska Junia Wulandari Rizky Caesar Irjayana Ryan Fahreza Maliki Said Al Farab Sakinah Rahmi Sang Made Naufal Caesarya Mahardhika Saputro3,, Widyanto Adi Sarah Suryaningsih Sarja Asra Winata Sendika Panji Anom Shaufiah . Shervano Naodias Siagian Siti Sa'adah Siti Sa’adah Suryaningsih, Sarah Tegar Graha Adiwiguna Teuku Muhammad Ikhsan Totok Suhardijanto Triawati, Candra Valentino Rossi Fierdaus Wahyu Kurniawan Wahyu Purbaningrum Warih Maharani Widi Astuti Winda Eka Samodra Wiwin Aminah Yusuf Anugrah Putra Aditama ZK Abdurahman Baizal