Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING ITEJ (Information Technology Engineering Journals)
Nunsina Nunsina
Malikussaleh University
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Measuring The Efficiency of Social Assistance Recipients in the Family Hope Program Using the Data Envelopment Analysis Method Fadilah Suryani Hasibuan; Dahlan Abdullah; Nunsina Nunsina
ITEJ (Information Technology Engineering Journals) Vol. 10 No. 2 (2025): December
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v10i2.268

Abstract

This study aims to measure the efficiency of aid distribution in the Family Hope Program (PKH) across six sub-districts in Medan Denai using the Data Envelopment Analysis (DEA) method. DEA allows a relative efficiency evaluation of multiple decision-making units (DMUs) by comparing inputs such as budget, number of officers, and recipients, against outputs like targeted beneficiary rate, distribution timeliness, and satisfaction level. The findings reveal that three sub-districts—Medan Tenggara, Tegal Sari Mandala I, and Tegal Sari Mandala II—achieved full efficiency with a score of 1. In contrast, Binjai, Denai, and Tegal Sari Mandala III were found to be inefficient due to higher input consumption not matched by proportional output. The study suggests that inefficient sub-districts can improve their performance by adopting the practices of efficient ones. These insights are expected to assist local governments in optimizing social assistance programs and ensuring better resource utilization.
Application of the Rule-Based Pattern Matching Method to Detection of Types of Mujarrad and Mazid Verbs in the Qur'an Based on Arabic Morphology Patterns Suci Khairani; Rini Meiyanti; Nunsina Nunsina
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13235

Abstract

Arabic has a complex morphological system, particularly in the formation of fi’il (verbs), which in sharaf are classified into fi’il mujarrad and fi’il mazid. Fi’il mujarrad refers to basic verbs without additional letters, while fi’il mazid involves added letters that form specific wazan (patterns). The main problem addressed in this study is the similarity of morphological patterns between fi’il and non-fi’il, which affects classification accuracy. This study aims to identify fi’il in Surah Al-Baqarah and classify them into mujarrad and mazid, along with their wazan patterns, automatically using a rule-based pattern matching approach. The method applies rules based on Arabic morphological patterns, such as fi’il mudhari’ prefixes, word length, and the presence of additional letters in accordance with sharaf principles.The data consist of Qur’anic text processed through preprocessing stages, including load data and tokenization. The system detected 916 candidate fi’il, of which 468 data points were used for evaluation by comparison with manual annotations using a confusion matrix.The results show that the system achieved an accuracy of 75% for fi’il type classification, with precision, recall, and F1-score of 0.77, 0.75, and 0.75, respectively. For wazan classification, the system achieved an accuracy of 69.23%, with weighted average precision of 0.66, recall of 0.69, and F1-score of 0.65. These findings indicate that the rule-based approach is sufficiently effective in detecting fi’il mujarrad and mazid, although performance for certain wazan patterns remains limited due to structural similarities. Therefore, further development of more specific rules and integration with machine learning methods are recommended to improve system accuracy.  
Co-Authors Dahlan Abdullah Fadilah Suryani Hasibuan Rini Meiyanti Suci Khairani