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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Implementation of persuasive design principles in mobile application development: a qualitative study Nor Afifah Shafin; RD Rohmat Saedudin; Nor Hazana Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1464-1473

Abstract

Persuasive design principles (PDP) of persuasive system features framework have shown impressive results from the context of user engagement and acceptance as well as continuous usage towards the persuasive systems involved. Yet, available literatures do not thoroughly address the implementation of these design principles specifically in mobile applications and there is insufficient discussion on the impact of the principles in relation to the overall achievement of mobile applications. Hence, this research was conducted with the aim to qualitatively explore the way PDP were implemented across three different levels of mobile applications’ attainment. For this study, seven semi-structured interviews were conducted with the involvement of fifteen (15) Android mobile applications in the area of utilities category. These mobile applications were then categorized into three categories which is successful, partially successful and less successful based on their numbers of mobile applications downloaded for three consecutive years. The results from the content analysis revealed that each of the PDP were implemented in many ways yet the most common applied principles are reduction, tailoring and personalization. However, the analysis also shows low numbers of implementation from the system credibility and social support category. In addition, most of the mobile applications of the successful category have implemented a lot more PDP as compared to the other two mobile application categories. The results from this study has provide significance towards developers, practitioners as well as the scholars from the contextual perspective of persuasive system framework also the practical values of the principles specifically the implementation in mobile application development.
An Effective Pre-Processing Phase for Gene Expression Classification Choon Sen Seah; Shahreen Kasim; Mohd Farhan Md Fudzee; Mohd Saberi Mohamad; Rd Rohmat Saedudin; Rohayanti Hassan; Mohd Arfian Ismail; Rodziah Atan
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1223-1227

Abstract

A raw dataset prepared by researchers comes with a lot of information. Whether the information is usefull or not, completely depends on the requirement and purposes. In machine learning, data pre-processing is the very initial stage. It is a must to make sure the dataset is totally suitable for the requirement. In significant directed random walk (sDRW), there are three steps in data pre-processing stage. First, we remove unwanted attributes, missing value and proper arrangement, followed by normalization of the expression value and lastly, filtering method is applied. The first two steps are completed by Bioconductor package while the last step is works in sDRW.
Imbalance class problems in data mining: a review Haseeb Ali; Mohd Najib Mohd Salleh; Rohmat Saedudin; Kashif Hussain; Muhammad Faheem Mushtaq
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i3.pp1552-1563

Abstract

The imbalanced data problems in data mining are common nowadays, which occur due to skewed nature of data. These problems impact the classification process negatively in machine learning process. In such problems, classes have different ratios of specimens in which a large number of specimens belong to one class and the other class has fewer specimens that is usually an essential class, but unfortunately misclassified by many classifiers. So far, significant research is performed to address the imbalanced data problems by implementing different techniques and approaches. In this research, a comprehensive survey is performed to identify the challenges of handling imbalanced class problems during classification process using machine learning algorithms. We discuss the issues of classifiers which endorse bias for majority class and ignore the minority class. Furthermore, the viable solutions and potential future directions are provided to handle the problems.
Comparison of feature selection techniques in classifying stroke documents Nur Syaza Izzati Mohd Rafei; Rohayanti Hassan; RD Rohmat Saedudin; Anis Farihan Mat Raffei; Zalmiyah Zakaria; Shahreen Kasim
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i3.pp1244-1250

Abstract

The amount of digital biomedical literature grows that make most of the researchers facing the difficulties to manage and retrieve the required information from the Internet because this task is very challenging. The application of text classification on biomedical literature is one of the solutions in order to solve problem that have been faced by researchers but managing the high dimensionality of data being a common issue on text classification. Therefore, the aim of this research is to compare the techniques that could be used to select the relevant features for classifying biomedical text abstracts. This research focus on Pearson’s Correlation and Information Gain as feature selection techniques for reducing the high dimensionality of data. Towards this effort, we conduct and evaluate several experiments using 100 abstract of stroke documents that retrieved from PubMed database as datasets. This dataset underwent the text pre-processing that is crucial before proceed to feature selection phase. Features selection phase is involving Information Gain and Pearson Correlation technique. Support Vector Machine classifier is used in order to evaluate and compare the effectiveness of two feature selection techniques. For this dataset, Information Gain has outperformed Pearson’s Correlation by 3.3%. This research tends to extract the meaningful features from a subset of stroke documents that can be used for various application especially in diagnose the stroke disease.
Co-Authors Abel Nathalia Widyastoro Adityas Adityas Adityas Widjadjarto Afif, Zehan Afizah Ahmad Fakhri Rizaldi Ahmad Munansyah Aida Mustapha Aida Mustapha, Aida Alfinansyah, Muhammad Dzaki Alfrianiko Anggriawan Alfrianiko Anggriawan Alfrianiko Anggriawan, Alfrianiko Amelia Kurniawati Ananda Anggie Nur Aini Ananda Fiqri Firdaus Ananda Risya Triani Angelia Lionardi Angelia Lionardi Anis Farihan Mat Raffei Anwar Sadat Anwar x Anwar Sadat Aria Fajar Ramdhany Ariq Yumna Mubarok Arvel Kennard Yeremia Avon Budiono Avon Budiono Avon Budiyono Azie, Febryan Elfanuary Bambang Tejo Kusumo BASUKI RAHMAD Basuki Rahmat Berka Irfansyah Berlian Maulidya Izzati Birahmatika, Raafi Asta Budi Praptono Budiono, Avon Caudinata, Owen Choon Sen Seah Daffa, Raihan Deya Ika Wardani Dicky Dwi Kurniawan Putra Dicky Hidayat Dida Diah Damayanti Fadhila, Muhammad Hilman Fajrin, Salsa Fauziyyah Faqih Hamami Faris Aufar Putra Farras Naim Fatin, Kanza Jilan Fatur Rachman Rasyid Fauzi, Rokhman Febryan Elfanuary Azie Fiega Dwi Novwari Fikri, Daffa Ilham Firdayakusmawarni Firdayakusmawarni Fitri Febriana Purba Fitri Febriana Purba, Fitri Febriana Fransiskus Tatas Dwi Atmaji Hamim Maafifa Nugraha Harizillah, M Ahyar Haryasena Panduwiyasa Haseeb Ali Himatul Zulfa Hind Raad Ebraheem Ibnu Caesar Ibnu Caesar, Ibnu Ibnu Yazid Ikhwana Ibrahim Hanif Alkhalil Ihfan Aditya Ghafur Intan Dwi Ariesta Putri Irfan Dwi Rahadianto Ismayana, I Nyoman Gede Iwan Tri Riyadi Yanto Iwan Tri Riyadi Yanto Judi Alhilman K. S. H., Umar Yunan Kashif Hussain Krisna Aji Wicaksono Kurniawan , MT. Kurniawan Kurniawan Kurniawan Kurniawan, M. Teguh Kurniawan, MT Kurniawan, MT. Lau Tian Rui Ling, Teng Mee Lingga Priyadi M Teguh Kurniawan M. Rafi Mario Mario Mochamad Hafiz Kurniawan Mochamad Teguh Kurniawan Mohamad Rizky Utomo Mohamad Tohir Mohammad Aljanabi Mohd Arfian Ismail Mohd Arfian Ismail Mohd Farhan Md Fudzee Mohd Najib Mohd Salleh Mohd Saberi Mohamad Muhammad Amanulloh Mz Muhammad Fadhil Muhammad Faheem Mushtaq Muhammad Fathinuddin Muhammad Fauzan Nasrullah Muhammad Hasbi Abid Ersalan Muhammad Ilham Zakky Mubarrak Muhammad Iqbal Muhammad Reyza Yana Putra Mustafa Mat Deris Nasrullah, Muhammad Fauzan Naufan, Zidni Ilman Nazim Razali Nenden Eva Nenden Eva Meilani Herlina Ni Kadek Dewi Pradnyawati Nicolaus Advendea Prakoso Indaryono Nina Nursetia Ningrum Noor Azah Samsudin Nor Afifah Shafin Nor Hazana Abdullah Norhalina Senan Novi Andriani, Novi Nur Ismianah Nur Syaza Izzati Mohd Rafei Oskar Halomoan Manalu Panji Permana Syahid Perkasa, Bimasetya Putri , Nabillah Verizky R. Wahjoe Witjaksono R. Yunendah Nur Fu’adah Rachmadita Andeswari Raharjo Putra Kurniadi Rahayu, Fresa Febrianti Rahma Karina Rahman, Ilham Auliya Rahmat Mulyana Rahmiati Aulia Rajif Rizal Fahlevi Ramadhan , Farhan Razali, Nazim Rd. Panji Erdinanda Pandu Jiwatama Regi Alvino Revi Fahreza Al Hazmi Reza Satya Rahmawan Rian Bimo Ankhal Ridha Hanafi Riksa Belasunda Rizki Yantami Arumsari Rodziah Atan Rohayanti Hassan Ronal Hadi Rui, Lau Tian Safitra, Muhammad Fakhrul Sahrial Hasan Wicaksana Samuel Putra Hari Satryo Dwi Sutrisno Sayyid Taufiq Abdulhafizh Selvi Marcellia Sely Novita Sari Seno Adi Putra Septian Sony Hermawan Septian Sony Hermawan Septiya Mutiara Septo, Umar Yunan Kurnia Shahreen Kasim Shahreen Kasim, Shahreen Shams N. Abd-Alwahab Shinta Meiliana Herdiani Singgih Krismarwantoni Sadino Siti Hajar Komariah Subhan Ari Raka Pradana Sulistijono Sulistijono Sutoyo, Edi Sutrisno Sutrisno Sutrisno Sutrisno Syarah Tazkiatun Nupus Syifa Sofiaturrohmah Syihan Qaes Yamani Syinta Kesuma Aisyah Tarjono, Muhamad Felix Nugraha Tesi Irwani Tesi Irwani, Tesi Triastuty Pardede Triastuty Pardede Triastuty Pardede, Triastuty Tutut Herawan Ugi Chandra Wiguna Umar Y.K.S. Hediyanto Umar Y.K.S. Hediyanto, Umar Y.K.S. Umar Yunan Umar Yunan K. S. H. Umar Yunan K.s. Hediyanto Umar Yunan KSP Yunan KSP Umar Yunan Kurnia Septo Hediyanto Vandha Pradwiyasma Widartha Vegi Fransiska Veronika Sari Asih Warih Puspitasari Wawan Tripiawan Yasser Sutojoyo Kusumo Yoga Yuniadi Yossy Meidy Wijaya Yossy Meidy Wijaya Yuanika Indanea Zainuri Saringat Zalino, Rama Rafitra Zalmiyah Zakaria Zehan Afizah Afif