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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
Core Subject : Economy, Health, Science, Education, Art, Social, Engineering,
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Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 5 Documents
 1 
Search results for , issue "Vol 5 No 12 (2025): May 2025" : 5 Documents clear
Best E-Wallet Selection Decision Support System using MOORA Method and ROC Weighting Mesran, Mesran; Ramli, M Saidina; Bintang, Muhammad Rizki Olihta; Rohayani, Hetty; Sallaby, Achmad Fikri
TIN: Terapan Informatika Nusantara Vol 5 No 12 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i12.6602

Abstract

E-wallet is an electronic payment service that is widely used by Indonesian people. Currently, there are many e-wallets on the market, making people confused about choosing an e-wallet that suits their needs. This research implements this system in a simulation environment to test and validate the effectiveness of the approach in selecting the best E-Wallet. Experimental results show that the proposed approach can provide more accurate and relevant recommendations for users in choosing an E-Wallet that suits their preferences. This research aims to build a decision support system for selecting the best e-wallet using the Multi-Objective Optimization by Ratio Analysis method (MOORA) and ROC weighting. MOORA is a multi-objective system that optimizes two or more conflicting properties simultaneously. This method is used to perform complex mathematical calculations. Decision support systems can help in the above problems. The aim of this research is to apply the MOORA algorithm to help users choose the best e-wallet that suits their needs. For the process of inputting alternative criteria weight values, the results of the system and manual process are the same, according to the results of the validity of the MOORA calculation. Where the application of the MOORA method is carried out by calculating alternative values from the algorithm and weighting, then calculations are carried out to determine the best option. The four e-wallets that are alternatives in this research are GoPay, OVO, ShopeePay, and DANA. Where the application of the Moora method is carried out by calculating alternative values from the algorithm and weighting then, calculations are carried out to determine the best option. The final results of this research showed that Alternative 1 (DANA) was chosen as the best alternative in the Best E-Wallet Selection with a preference value of 0.507.
Analisis Kepuasan Masyarakat dan Evaluasi Kinerja Sistem pada Layanan Akta Kelahiran Online Berbasis EUCS+ dan PIECES Machfud, Syaeful; Prasetia, Okky
TIN: Terapan Informatika Nusantara Vol 5 No 12 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i12.7175

Abstract

In the rapidly advancing digital era, the Indonesian government has implemented an online birth certificate service to improve the efficiency and accessibility of public services. This study aims to evaluate both user satisfaction and system performance using two distinct approaches: End User Computing Satisfaction Plus (EUCS+) and Performance Information Economy Control Efficiency Services (PIECES). The EUCS+ model measures user satisfaction based on content, accuracy, format, ease of use, and timeliness, while the PIECES framework assesses system performance from the perspectives of performance, information, economy, control, efficiency, and service. This research employed a quantitative method by distributing questionnaires to 100 respondents who had used the online birth certificate service within the last six months. The results indicate that the highest satisfaction scores were recorded in the dimensions of format (3.81) and ease of use (3.89), whereas system speed and content quality received the lowest scores (2.30 and 2.97, respectively). In the PIECES model, the economy and efficiency dimensions showed strong performance with scores above 3.80, while the control dimension emerged as an area for improvement (2.92). These findings suggest that although the service is relatively effective in terms of visual interface and cost accessibility, significant enhancements are needed in system speed and information quality. This study contributes to a comprehensive evaluation of digital public services and offers recommendations for continuous improvement by government agencies.
Clustering Data Penduduk Menggunakan Algoritma K-Means Ikhsan, Tomi; Haerani, Elin; Wulandari, Fitri; Syafria, Fadhilah
TIN: Terapan Informatika Nusantara Vol 5 No 12 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i12.7328

Abstract

Economic inequality is still a crucial factor facing Indonesia today, from big cities to remote villages, economic inequality is still a major problem. Bina Baru Village is no exception, a village inhabited by 5,760 people with a total of 1,742 families, spread across 30 neighbourhood associations (RT) and 8 community associations (RW). Various efforts are made to overcome the problem of economic inequality, one of which is by channeling assistance or providing policies that are right on target. One of the steps to overcome this problem is to group population data in Bina Baru village using the K-Means Clustering method which aims to determine the economic level of families in the region, so that local governments can more accurately make policies on the problem of economic inequality that occurs. The data used comes from a questionnaire of 1,005 family data with 64 attributes and 1,005 individual data with 84 attributes. The application of the k-means algorithm is carried out using python, also using DBI (Davies-Bouldin Index) to determine the optimum k value. In this study, the optimal k value is 3 clusters. Based on testing, it is found that Cluster 0 represents households with medium economic conditions, cluster 1 represents groups with better economic conditions and Cluster 2 is a group of households with low economic conditions. By clustering the population's economy, it is hoped that it can help stakeholders to provide targeted policies.
Implementasi Business Intelligence Menggunakan Tableau dalam Analisis Kasus Kematian Akibat Penyakit Demam Berdarah Dengue Gilang, Oprin Muhammad; Irwansyah, Irwansyah
TIN: Terapan Informatika Nusantara Vol 5 No 12 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i12.7426

Abstract

Dengue Hemorrhagic Fever (DHF) remains one of the most serious infectious diseases in Indonesia, particularly in the West Java Province. The high population density, combined with environmental conditions that support the proliferation of dengue virus-carrying mosquitoes, has led to the continuous emergence of cases each year. Based on data analysis, during the period from 2014 to 2023, a total of 225,481 deaths caused by DHF were recorded in this province. When categorized by gender, the number of male fatalities reached 117,107 cases, while female deaths amounted to 108,374 cases. Among all regions, Bandung City and Bogor City recorded the highest numbers of fatalities, with 54,900 deaths in Bandung and 23,802 in Bogor during the same period. One of the obstacles faced in efforts to manage DHF is the lack of informative, concise, and easily accessible data for various relevant stakeholders. In fact, such information is crucial as a basis for determining more targeted disease prevention and control strategies. In response to this situation, this study seeks to offer a solution by applying the concept of Business Intelligence (BI) through the use of Tableau software to visualize mortality data related to DHF. The process begins with an Extract, Transform, Load (ETL) stage applied to secondary data obtained from the Satu Data Indonesia portal, involving a total of 540 data records on DHF deaths. This is followed by analysis and presentation in the form of an interactive dashboard. The visualization results are displayed using various types of charts, including geo mapping, line charts, horizontal bar charts, stacked bar charts, and pie charts. Each visualization provides clearer insights into the annual trends of DHF cases, distributions by gender, and the geographical spread of fatalities across all regions in West Java. In conclusion, the implementation of Tableau within the Business Intelligence framework has proven effective in processing and simplifying initially complex data into visual information that is easier to interpret. Furthermore, these visualizations can serve as a valuable reference for data-driven decision-making processes, particularly in supporting the prevention and control efforts of DHF cases in the West Java Province.
Penerapan Business Intelligence dalam Analisis dan Visualisasi Tren Bencana Alam Menggunakan Tableau Murti, Aqmal Bastian; Irwansyah, Irwansyah
TIN: Terapan Informatika Nusantara Vol 5 No 12 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i12.7427

Abstract

DKI Jakarta is highly vulnerable to natural disasters due to geographical conditions, high population density, and the impact of climate change. Recurring disasters such as floods, fires, landslides, fallen trees, and tornadoes demand an effective data management and visualization system. This study applies Business Intelligence (BI) using the Tableau platform to analyze and visualize disaster trends in DKI Jakarta from 2018 to 2024. A total of 413 incident records were collected from Satu Data Jakarta and Satu Data Indonesia. The research involved ETL (Extract, Transform, Load) processes, data validation, and the development of interactive dashboards. The visualization presents key information such as disaster types, number of victims, incident locations, and yearly trends. The analysis revealed that South Jakarta recorded the highest fatalities (40,325), followed by East Jakarta (38,550). Tableau’s interactive features enable clear and accessible data presentation through charts, maps, and diagrams, supporting evidence-based decision-making. The implementation of BI successfully simplifies complex data and assists stakeholders—both government and the public—in comprehending disaster patterns. This approach offers a strategic solution for enhancing disaster preparedness, formulating effective mitigation policies, and increasing public awareness of environmental risks.

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