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Journal : International Journal Software Engineering and Computer Science (IJSECS)

Application of the Naive Bayes Algorithm in Twitter Sentiment Analysis of 2024 Vice Presidential Candidate Gibran Rakabuming Raka using Rapidminer Amini, Tasya Aisyah; Setiawan, Kiki
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2236

Abstract

In the current era of digital democracy, social media sentiment analysis has become a relevant method for understanding public views of political figures. As one of the leading social media platforms, Twitter provides a public space for sharing opinions and expressions regarding political issues. This research aims to classify and measure the accuracy of people's responses to the positive and negative sides. Sentiment analysis was carried out using the Naïve Bayes method using a dataset of 3223 tweets. The final results of this research show that implementing the Naïve Bayes Method in sentiment analysis regarding political dynasty polemics, especially regarding the 2024 Cawapres Gibran Rakabuming Raka, provides an accuracy value of 82.19%. Of the 1696 negative and 112 positive sentiments predicted, there were 462 harmful and 953 positive predicted data. These results indicate that most public responses tend to be detrimental to the Constitutional Court's (MK) decision, which grants political legitimacy to Gibran Rakabuming Raka as the 2024 vice-presidential candidate.
Implementation of RFM Analysis to Enhance Sales Patterns of Food and Beverages at Bonjour Café and Resto Using the Apriori Algorithm Sibarani, Julvan Marzuki Putra; Akbar, Yuma; Sutisna; Setiawan, Kiki
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3073

Abstract

The rapid growth of the culinary business has made business competition in this field increasingly tight, so a strategy is needed to increase food and beverage sales patterns. Bonjur Cafe Resto serves many food and beverage menus, but business actors need to try to produce product innovations in order to provide satisfactory service to customers. In this condition, a data processing technique is needed to determine customer segmentation and menu recommendations at Bonjur Cafe Resto. The analysis method used is RFM Analysis by analyzing customer behavior, analyzing purchase transaction data consisting of Recency Frequency Monetary (RFM) attributes and data mining techniques with the Apriori algorithm, where this algorithm is used to determine the most frequently appearing data set (frequent itemset). The results of this study are grouped into five categories of customers based on their purchasing behavior and association rules are formed with predetermined parameters, support 28% and confidence 70%. This can later be a recommendation for a menu combination from the data that has been collected and applied using the apriori algorithm so that it is expected to be used for service evaluation and be able to increase customer satisfaction so that Bonjur Cafe Resto can develop better
K-Means Clustering Analysis of Poverty Data in Cilacap District Setiawan, Kiki; Kastum; Pratama, Yuliya Putri
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3759

Abstract

Poverty stands as a complex structural obstacle within social development frameworks. The COVID-19 pandemic intensified poverty dynamics in Indonesia which saw poverty rates increase by 9.78% in March and reach 10.19% by September. Local Bureau of Statistics data shows that the poverty rate in Cilacap Regency dropped to 10.99% (around 191,000 people) in March 2024 from 10.68% (186,080 people) in March 2023. The study uses k-means clustering methodology for analysis and maps poverty-prone areas utilizing QGIS software. The analysis revealed 12 sub-districts and 14 neighborhood units (RW) alongside a single community unit (RT) that show unique poverty characteristics. The silhouette coefficient evaluation produced a 0.55 score which showed a moderate cluster structure and acceptable cluster placement. The research provides empirical evidence about poverty distribution which shows how data mining methods can enhance spatial socioeconomic studies. The study presents a detailed analysis of poverty stratification across Cilacap Regency through the application of sophisticated computational methods.
Implementation of Educational Game System Using MDLC with Adobe Animate Application Setiawan, Kiki; Sarikah, Dede
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4727

Abstract

Digital gaming has transformed educational practices across Indonesia, creating new pathways for curriculum delivery through interactive entertainment. Educational games now serve as effective learning tools that capture student attention while building essential skills. The research develops and evaluates a multi-level educational puzzle game using Adobe Animate 2022, targeting cognitive skill enhancement and problem-solving abilities across different age groups. Development followed the Multimedia Development Life Cycle (MDLC) approach through six phases: conceptualization, design planning, resource gathering, system building, testing procedures, and final deployment. The puzzle application includes three difficulty levels with varying complexity parameters. Adobe Animate 2022 handled vector graphics creation, interactive programming, and multi-platform publishing. User evaluation involved testing across target demographics to assess usability and learning effectiveness. The finished application successfully demonstrates structured game development using MDLC principles. Testing showed positive user responses with balanced difficulty progression and completion rates that indicate effective entertainment-education integration. The development process provided organized workflows that supported quality control and user satisfaction goals. Adobe Animate 2022 proved capable for educational game creation, enabling smooth asset management and publishing operations. The study establishes a reproducible model for future educational gaming projects while validating game-based learning methods in Indonesian educational settings. Findings suggest that systematic development approaches produce superior educational outcomes compared to informal development practices.