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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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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.
Mobile Decision Support System to Determine Toddler's Nutrition Using Fuzzy Sugeno Suharjito Suharjito; Jimmy Jimmy; Abba Suganda Girsang
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.601 KB) | DOI: 10.11591/ijece.v7i6.pp3683-3691

Abstract

Determination of nutritional status is closely related to the determination of dietary patterns should be given to infants. Nutrition is very important role in mental, physical development, and human productivity. In this study, the system based on android is developed to determine the nutritional status of infants by using Fuzzy Sugeno. Indicator variables are age, height, circle head, and body weight according to the male or female. In this study, the results of measurements of nutritional status of children with Fuzzy Sugenoare tested by comparing the nutritional quality of the data Posyandu toddler by using anthropometric tables. The results of the evaluation measurement accuracy in this application are compared with the results of manual calculation based infant growth charts according to WHO standards. Therefore, these applications can be used to help the community in monitoring the nutritional status of children so that the growth of children is more appropriate in line with expectations.
Family Relationship Identification by Using Extract Feature of Gray Level Co-occurrence Matrix (GLCM) Based on Parents and Children Fingerprint Suharjito Suharjito; Bahtiar Imran; Abba Suganda Girsang
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (12.646 KB) | DOI: 10.11591/ijece.v7i5.pp2738-2745

Abstract

This study aims to find out the relations correspondence by using Gray Level Co-occurrence Matrix (GLCM) feature on parents and children finger print. The analysis is conducted by using the finger print of parents and family in one family There are 30 families used as sample with 3 finger print consists of mothers, fathers, and children finger print. Fingerprints data were taken by fingerprint digital persona u are u 4500 SDK. Data analysis is conducted by finding the correlation value between parents and children fingerprint by using correlation coefficient that gained from extract feature GLCM, both for similar family and different family. The study shows that the use of GLCM Extract Feature, normality data, and Correlation Coefficient could identify the correspondence relations between parents and children fingerprint on similar and different family. GLCM with four features (correlation, homogeneity, energy and contrast) are used to give good result. The four sides (0o, 45o, 90o and 135o) are used. It shows that side 0o gives the higher accurate identification compared to other sides.
Neural Collaborative with Sentence BERT for News Recommender System Budi Juarto; Abba Suganda Girsang
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.678

Abstract

The number of news produced every day is as much as 3 million per day, making readers have many choices in choosing news according to each reader's topic and category preferences. The recommendation system can make it easier for users to choose the news to read. The method that can be used in providing recommendations from the same user is collaborative filtering. Neural collaborative filtering is usually being used for recommendation systems by combining collaborative filtering with neural networks. However, this method has the disadvantage of recommending the similarity of news content such as news titles and content to users. This research wants to develop neural collaborative filtering using sentences BERT. Sentence BERT is applied to news titles and news contents that are converted into sentence embedding. The results of this sentence embedding are used in neural collaboration with item id, user id, and news category. We use a Microsoft news dataset of 50,000 users and 51,282 news, with 5,475,542 interactions between users and news. The evaluation carried out in this study uses precision, recall, and ROC curves to predict news clicks by the user. Another evaluation uses a hit ratio with the leave one out method. The evaluation results obtained a precision value of 99.14%, recall of 92.48%, f1-score of 95.69%, and ROC score of 98%. Evaluation measurement using the hit ratio@10 produces a hit ratio of 74% at fiftieth epochs for neural collaborative with sentence BERT which is better than neural collaborative filtering (NCF) and NCF with news category.
Effort Estimation Development Model for Web-Based Mobile Application Using Fuzzy Logic Stefani Agusta; Suharjito Suharjito; Abba Suganda Girsang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.6561

Abstract

Effort estimation becomes a crucial part in software development process because false effort estimation result can lead to delayed project and affect the successful of a project. This research proposes a model of effort estimation for web-based mobile application developed using object oriented approach. In the proposed model, functional size measurement of object oriented based web application named OOmFPWeb, web metric and mobile characteristic for web-based mobile application size measurement are combnined. The estimation process is done by using mamdani fuzzy logic method. To evaluate the proposed model, the comparison between OOmFPWeb as the variable that affect effort estimation for web-based mobile application and the proposed model are performed. The evaluation result shows that effort estimation for web-based mobile application with the proposed model is better than just using OOmFPWeb.
HABCO: A Robust Agent on Hybrid Ant-Bee Colony Optimization Abba Suganda Girsang; Chun-Wei Tsai; Chu-Sing Yang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 3: September 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i3.3656

Abstract

The purpose of this research is to generate a robust agent by combining bee colony optimization (BCO) and ELU-Ants for solving traveling salesman problem (TSP), called HABCO. The robust agents, called ant-bees, firstly are grouped into three types scout, follower, recruiter at each stages. Then, the bad agents are high probably discarded, while the good agents are high probably duplicated in earlier steps. This first two steps mimic BCO algorithm. However, constructing tours such as choosing nodes, and updating pheromone are built by ELU-Ants method.To evaluate the performance of the proposed algorithm, HABCO is performed on several benchmark datasets and compared to ACS and BCO. The experimental results show that HABCO achieves the better solution, either with or without 2opt.
Development of an Enterprise Architecture for Healthcare using TOGAF ADM Abba Suganda Girsang; Achmad Abimanyu
Emerging Science Journal Vol 5, No 3 (2021): June
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01278

Abstract

Hospital is one of the most complex organization with highly intensive interaction between stakeholders (patients, nurses, doctors, staff, etc.). In the operation of a hospital, the use of Information technology has been proven to improve effectiveness and efficiency. However, in the majority of cases, the processes to achieve the Strategic Objectives through implementation of Information Technology are full of challenges. Based on the case study in Dharmais Cancer Hospital, there are many symptoms that are identified by this study and lead to 4 issues, namely: lack of ownership from Business users, lack of alignment between business strategy and IT strategy, lack of awareness to use IT as a tool for competitive advantage, and low quality of IT operation performances. In order to solve the issues and support the achievement of Strategic Business Objective through IT, an Enterprise Architecture approach can be used to develop baseline architecture, identify the target architecture, finding the gap, and use the gap as recommendation to solve those issues. The methodology chosen is TOGAF ADM, based on its focus on processes and its flexibility to combine artifacts and approaches that are most suitable for the case. This study develops 7 recommendations to Strengthen Business area of organization, 5 recommendations to Align IT plan with Business Strategy, 16 recommendations to Implement several IT solutions as Competitive Advantage for organization, and 8 recommendations to provide higher performances by enabling Service Management approach for IT Operation. This study also shows how TOGAF ADM can improve the awareness of the business users to the business itself. Doi: 10.28991/esj-2021-01278 Full Text: PDF
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