Comparison of Naive Bayes Algorithm and C.45 Algorithm in Classification of Poor Communities Receiving Non Cash Food Assistance in Wanasari Village Karawang Regency

Abstract

Non-Cash Food Assistance or Bantuan Pangan Non-Tunai (BPNT) is food assistance from the government given to the Beneficiary Family (KPM) every month through an electronic account mechanism that is used only to buy food at the Electronic Shop Mutual Assistance Joint Business Group Hope Family Program (e-Warong KUBE PKH ) or food traders working with Bank Himbara. In its distribution, BPNT still has problems that occur that are experienced by the village apparatus especially the apparatus of Desa Wanasari on making decisions, which ones are worthy of receiving (poor) and not worthy of receiving (not poor). So one way that helps in making decisions can be done through the concept of data mining. In this study, a comparison of 2 algorithms will be carried out namely Naive Bayes Classifier and Decision Tree C.45. The total sample used is as much as 200 head of household data which will then be divided into 2 parts into validation techniques is 90% training data and 10% test data of the total sample used then the proposed model is made in the RapidMiner application and then evaluated using the Confusion Matrix table to find out the highest level of accuracy from 2 of these methods. The results in this classification indicate that the level of accuracy in the Naive Bayes Classifier method is 98.89% and the accuracy level in the Decision Tree C.45 method is 95.00%. Then the conclusion that in this study the algorithm with the highest level of accuracy is the Naive Bayes Classifier algorithm method with a difference in the accuracy rate of 3.89%.

Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition

“…The application of the C45 algorithm can be optimized, such as the addition of swarm particle optimization which achieves an accuracy of 97.13% in measuring the readiness of junior high school students to face the national exam [25] . Another result of the C45 algorithm in predicting customer or customer loyalty is reflected in 2 similar results, namely the C.45 algorithm has good accuracy [26] compared to other algorithms such as Naïve Bayes [27] , although in certain cases the results are sometimes contradictory, the resulting accuracy is still relatively good [28] . Apart from the C45 and Random Forest algorithms, the LMT algorithm is one of the algorithms that can be used for the classification process, such as in Natuthe ral Language Processing-based Mental Health Risk Prediction study, the most accurate prediction results were achieved in the DASA dataset using the sentiment dictionary and the LMT and SVM algorithms [29] .…”

Implementasi Data Mining Clustering Data Penduduk Miskin Menggunakan Metode Algoritma C4.5 Untuk Merekomendasikan Bantuan Sosial Pada RT. 05/01 Kelurahan Jati Mekar Kecamatan Jati Asih Kota Bekasi

“…Penelitian lain dikerjakan oleh Siti Badriah [6] berjudul "Kualifikasi Perhitungan C4.5 Dalam Penentuan Penerima Bantuan Covid-19" menghasilkan aturan dari perhitungan C4.5 dengan nilai ketepatan yang terbagus terdapat pada pembandingan 90% informasi latih dan 10% informasi pengujian dengan nilai ketepatan senilai 79,54%. Penelitian lain dikerjakan oleh Muafi [7] berjudul "Kualifikasi Pemberian Bantuan Kepada Masyarakat Terkena Covid-19 Dengan Memakai Perhitungan C4.5 Di Desa Demung Kecamatan Besuki Kabupaten Situbondo" dengan hasil aturan atau decision tree C4.5, dengan ketepatan yang terbagus 90% latih dan 10% pengujian, dengan nilai ketepatan 74.09%.…”

Pelatihan Pengembangan Kelembagaan Kelompok Usaha Bersama (KUBE) di Kecamatan Moramo Utara

“…Pengelolaan sumberdaya alam suatu wilayah meningkatkan pendapatan melalui perantara kelompok usaha Bersama, pemberdayaan keluarga nelayan pesisir dengan program KUB, seperti bantuan perahu, bantuan beras, bantuan tunai langsung, dengan tujuan agar nelayan mengembangkan usahanya dan menjadi individu yang lebih baik (Putra et al, 2021). Bantuan Pangan Non Tunai (BPNT) adalah bantuan sembako dari pemerintah yang diberikan kepada Keluarga Penerima Manfaat (KPM) setiap bulannya melalui mekanisme rekening elektronik yang hanya digunakan untuk membeli makanan di Electronic Shop Mutual Assistance Joint Business Group Hope Family Program (e-Warong KUBE PKH) atau pedagang makanan yang bekerja sama dengan Bank (Alkhalifi et al, 2020).…”