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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) JUITA : Jurnal Informatika JOIV : International Journal on Informatics Visualization Emerging Science Journal Syntax Literate: Jurnal Ilmiah Indonesia Gema Wiralodra Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies Engineering, Mathematics and Computer Science Journal (EMACS) Parameter: Journal of Statistics Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Indonesia Sosial Teknologi Jurnal Penelitian Pendidikan Indonesia Teknologi : Jurnal Ilmiah Sistem Informasi
Abba Suganda Girsang, Abba Suganda
Bina Nusantara University, Jakarta, Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : CommIT (Communication

 1 
Optimization of the Bugs Classification of the Ticketing System in Software Development: a Study Case Ardhito, Danar; Girsang, Abba Suganda
CommIT (Communication and Information Technology) Journal Vol 10, No 2 (2016): CommIT Vol. 10 No. 2 Tahun 2016
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v10i2.1670

Abstract

Computer bug elimination is an important phase in the software development process. A ticketing system is usually used to classify the identified bug type and to assign a suitable developer. This system is handled manually and error prone. This paper proposes a new bug classification method using the fast string search algorithm. The method searches the error string and compares it to the full text. The approach is deployed to the software development process at PT. Selaras Anugerah Lestari and it results in a significant reduction in the average value of the time required to handle the bugs.
Use of Data Mining for Prediction of Customer Loyalty Wijaya, Andri; Girsang, Abba Suganda
CommIT (Communication and Information Technology) Journal Vol 10, No 1 (2016): CommIT Vol. 10 No. 1 Tahun 2016
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v10i1.1660

Abstract

This  article  discusses  the  analysis  of  customer  loyalty  using  three  data  mining  methods:  C4.5,Naive Bayes, and Nearest Neighbor Algorithms and real-world  empirical  data.  The  data  contain  ten  attributes related to the customer loyalty and are obtained from a national  multimedia  company  in  Indonesia.  The  dataset contains 2269 records. The study also evaluates the effects of  the  size  of  the  training  data  to  the  accuracy  of  the classification.  The  results  suggest  that  C4.5  algorithm produces   highest classification   accuracy   at   the   order of  81%  followed  by  the  methods  of  Naive  Bayes  76% and  Nearest  Neighbor  55%.  In  addition,  the  numerical evaluation  also  suggests  that  the  proportion  of  80%  is optimal  for  the  training  set.
Use of Data Mining for Prediction of Customer Loyalty Andri Wijaya; Abba Suganda Girsang
CommIT (Communication and Information Technology) Journal Vol. 10 No. 1 (2016): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v10i1.1660

Abstract

This  article  discusses  the  analysis  of  customer  loyalty  using  three  data  mining  methods:  C4.5,Naive Bayes, and Nearest Neighbor Algorithms and real-world  empirical  data.  The  data  contain  ten  attributes related to the customer loyalty and are obtained from a national  multimedia  company  in  Indonesia.  The  dataset contains 2269 records. The study also evaluates the effects of  the  size  of  the  training  data  to  the  accuracy  of  the classification.  The  results  suggest  that  C4.5  algorithm produces   highest classification   accuracy   at   the   order of  81%  followed  by  the  methods  of  Naive  Bayes  76% and  Nearest  Neighbor  55%.  In  addition,  the  numerical evaluation  also  suggests  that  the  proportion  of  80%  is optimal  for  the  training  set.
Optimization of the Bugs Classification of the Ticketing System in Software Development: a Study Case Danar Ardhito; Abba Suganda Girsang
CommIT (Communication and Information Technology) Journal Vol. 10 No. 2 (2016): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v10i2.1670

Abstract

Computer bug elimination is an important phase in the software development process. A ticketing system is usually used to classify the identified bug type and to assign a suitable developer. This system is handled manually and error prone. This paper proposes a new bug classification method using the fast string search algorithm. The method searches the error string and compares it to the full text. The approach is deployed to the software development process at PT. Selaras Anugerah Lestari and it results in a significant reduction in the average value of the time required to handle the bugs.
Co-Authors Achmad Abimanyu Adi Setya Agung Nur Aprianto Agus Susanto Ali, Ichsan Andrew, Peter Andri Wijaya Anggara, Nelsen Anita Sindar Ros Maryana Sinaga Ardhito, Danar Aurelia, Miracle Budi Juarto Burhanudin Burhanudin Chu-Sing Yang Chun-Wei Tsai Danar Ardhito Dela Nurlaila Dewangga, Firdaus Angga Febryan Grady Gagas Pandusarani, Gagas I Dewa Bagus Gde Khrisna Jayanta Nugraha Imran, Bahtiar Indrabudhi Lokaadinugroho Jimmy Jimmy Joel Rizky Wahidiyat Ko-Wei Huang Lawijaya, Viriyaputra Lawysen, Lawysen Monica, Sheila Nasari, Maulin Naufal, Muhammad Alwan Novika, Andien Dwi Nursandi, Bambang Priccilia, Shania Prisscilya, Veren Putra, Anugrah Dwiatmaja Ricky Eka Putra Rifqi Ramadhani Almassar Stefani Agusta Suharjito Suharjito, Suharjito Syamsul Arifin Taufiq, Muhammad Imam Tedjasulaksana, Jeffrey Junior Tjeng Wawan Cenggoro Widjaya Kumala Putra Yefferson, Danny Yongky Yulianto Nugroho