Paradigma - Jurnal Komputer dan Informatika

Mobile-based Application Development on Admission of New Students with Design Science Research Methodology

Yuris Alkhalifi, Rino Ramadan, Rahdian Kusuma Atmaja, Ispandi — Thu, 03 Oct 2024 00:00:00 +0700

Increased use of mobile devices in recent years has led to a change in human behavior as users. Mobile devices today are being used for a wide range of sectors ranging from entertainment, and business to education. In the field of education, it can be used to interact between teachers and students, and lecturers with students, and can also be done for registration of New Student Admission. The presence of PMB registration through mobile devices can help prospective students apply wherever they are without having to come directly to the campus. It's not implemented by the Indonesian Siber University. (Cyber University). The Cyber University campus is currently implementing New Student Admission registration directly through the campus, so this process is still likely to take a long time. To solve the problem, this study will solve the problem of new student enrolment that is still being done manually to be digitized by building mobile-based applications. The method to be used is the Design Science Research Methodology (DSRM) known as the fast method because it includes the Agile software development model. The programming language used is the Dart-based Flutter framework. As a result of the research carried out, the mobile-based PMB application on the Cyber University was successfully constructed and in line with expectations. Candidate students can download the app on the Google PlayStore with the keyword Cyber PMB

Dempster Shafer Analysis in Mental and Emotional Health Monitoring

Asyahri Hadi Nasyuha, Dini Fakta Sari, Azanuddin, Muhammad Hafidz Ady Khoiri — Thu, 03 Oct 2024 00:00:00 +0700

Monitoring and diagnosing mental and emotional health is a significant challenge in the healthcare field due to its complex and subjective nature. This research aims to develop an expert system using the Dempster-Shafer method in monitoring and diagnosing mental and emotional health conditions. The Dempster-Shafer method was chosen because of its ability to handle uncertainty and combine various evidence from different information sources. This analysis is designed to identify seven types of mental and emotional illness by considering twenty-four related symptoms. The results of the analysis show that this expert system can provide a more accurate and comprehensive assessment compared to conventional methods. It is hoped that the implementation of this expert system can be an effective tool for medical personnel in making diagnoses and determining appropriate treatment steps for patients with mental and emotional health conditions. This study also highlights the potential of the Dempster-Shafer method in other applications that require evidence-based analysis under uncertainty.

Sipkumhamai Application Success Analysis Using the Delone And Mclean Model

Fadillah Said, Chintia Octenta, Adi Octaviantara — Mon, 30 Sep 2024 00:00:00 +0700

Evidence-based policy aims to increase the efficiency and effectiveness of policy settings and increase alternative opportunities. The Legal and Human Rights Policy Strategy Agency created the SIPKUMHAMAI application to support evidence-based legal and human rights policies, support legal and human rights research with better data, and provide information to the public about legal and human rights issues. It is very important to make efforts to provide comprehensive and systematic data and information on legal and human rights issues originating from real situations on the ground. In addition to overall legal and human rights issues, this data and information can be used to find out more about the causes of legal and human rights problems, identify deficiencies in law enforcement and human rights protection, and carry out analyzes and provide various recommendations to strengthen systems and mechanisms for enforcing law and human rights in Indonesia. To achieve this goal, a system evaluation must be carried out to determine which components need to be improved. This is necessary to determine whether the system used provides significant benefits for users and the organization. Using the Delone and McLean model, from the six relationships of Information System Success Model, it was obtained that only Hypothesis 7, Hypothesis 8, and Hypothesis 9 were significantly supported and accepted by the data. These findings provide several implications for eGovernment research and practice, especially regarding how to maximize applications. This paper concludes by discussing the limitations that the proposed hypotheses are not fully supported by the research results.

Implementation MFEP Method in Developing Recommendation System for Program Keluarga Harapan (PKH) Recipients

Mon, 30 Sep 2024 00:00:00 +0700

Poverty occurs because of the imbalance between unlimited human needs and limited resources. This results in a lack of income to meet basic living needs. The Indoonesian government's efforts to alleviate poverty include providing assistance to the poor or underprivileged with assistance called Social Assistance, one of which is the Program Keluarga Harapan (PKH). Problems often occur in determining who is entitled to receive PKH assistance. The conventional selection process is considered inefficient because it requires a long process and the influence of the committee's subjectivity in the assessment, the criteria used in the survey are not in accordance with government regulations and the limited quota of total PKH recipients, so there are still people who do not receive PKH even though they meet the criteria. This research uses the Multi Factor Evaluation Process (MFEP) method. System testing uses the black box method and Boundary Value Analysis techniques which focus on finding system errors. To test the system's accuracy by comparing the MFEP process from the system results and facts based on PKH recipients in 2022 and producing an accuracy value of 91%.

Development of a Website-Based Rubber Tender System for Cooperatives Tanjung Telang Village

Khana Wijaya, Riza Kartina — Mon, 30 Sep 2024 00:00:00 +0700

The development of technology in today's modern era is progressing very rapidly, where everyone can find various technologies in various fields around human life, one of which is information technology. The existence of information technology can simplify and speed up data processing, information technology that is often used by an agency or organization is information system technology. Tanjung Telang Village Cooperative is a village engaged in processing and selling rubber residents. Currently, the promotional process carried out by the Village Cooperative only uses via telephone, resulting in very limited competition for the sale of rubber residents. The purpose of this research is to build a website-based rubber tender system that is expected to be more efficient and transparent to residents. This research uses descriptive quantitative and uses User Centered Design (UCD) system development. And the results obtained in this research are the creation of an online-based tender system that can be used by the Tanjung Telang Village Cooperative in the auction process to prospective buyers in the South Sumatra region.

Classification of Dog Emotion Using Transfer Learning on Convolutional Neural Network Algorithm

Steven Tribethran, Nicolas Jacky Pratama Hasan, Abdul Rahman — Mon, 30 Sep 2024 00:00:00 +0700

Recognizing your pet's emotions are very important to improve health, welfare and to detect certain diseases in the animal. The emotions in question are categorized into four categories, namely anger, happiness, calmness, and sadness. The model is designed by utilizing transfer learning techniques using the VGG16 architecture to perform image feature extraction for dog emotion classification based on the image of the animal's facial expression. The research produced an accuracy value of 96.72% on the training set and 88.05% on the validation set, as well as an average F1-Score value of 84.30% on the test set. This research shows the great potential of utilizing transfer learning in dog emotions classification and contributes to more advanced emotion recognition techniques to improve pet’s welfare.