Kajian Komparasi Algoritma C4.5, NAÏVE BAYES dan Neural Network dalam Pemilihan Penerima Beasiswa (Studi Kasus pada SMA Muhammadiyah 4 Jakarta )

Pauziah, Ulfa

doi:10.30998/string.v1i1.968

Cited by 2 publications

(3 citation statements)

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“…Untuk mengukur kinerja kedua algoritma tersebut digunakan metode pengujian Cross Validation dan Split Percentace, dan pengukurannya dengan menggunakan Confusion Matri. d. Kajian Komparasi Algoritma C4.5, Naïve Bayes Dan Neural Network Dalam Pemilihan Penerima Beasiswa (Studi Kasus Pada Sma Muhammadiyah 4 Jakarta)[6]. Dalam penelitian ini menggunakan data siswa sebagai objek pengujian oleh tiga algoritma klasifikasi.…”

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Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan

Fitriani¹

2020

SISTEMASI

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PKH is a program that provides conditional cash transfer to very poor households where they have been determined as PKH participants with certain conditions. Sometimes, this assistance is not in its target. Therefore, it is becoming a problem in this Government empowerment program. This problem arises due to ineffective data verification in the selection of citizens who are eligible to receive PKH assistance. Therefore, it is necessary to analyze PKH for determining the feasibility of a PKH Program problem. Through the results of the PKH analysis, it could be seen whether or not the citizens were feasible to get assistance. Based on this problem, comparative data mining classification methods were used to find out which algorithm is good for predicting citizenship feasibility. There were two algorithms used, namely the C4.5 algorithm and Naïve Bayes. After testing with the two algorithms using RapidMiner tools, the results showed that C4.5 algorithm produced an accuracy value of 91.25% and AUC value of 0.930 with a diagnosis level of Excellent Classification. While the Naïve Bayes algorithm produced an accuracy value of 87.11% and AUC value amounted to 0.923 with a diagnosis level of Excellent Classification. In conclusion, C4.5 algorithm is a good algorithm to be applied to the feasibility of PKH.

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Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan

Fitriani¹

2020

SISTEMASI

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“…Literature Review Sartika and Sensure (2017) explained that data mining was an analysis process towards a group of data in the database which helped to obtain information that will be used in the following phases. They also argued that classification was the commonly used technique in data mining process.…”

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“…They also argued that classification was the commonly used technique in data mining process. It was known as a data mining modeling technique that requires unclassified data to be applied in classifying new data [3].…”

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Designing and Implementing an Organoleptic Test Application for Food Products Using Android Based Decision Tree Algorithm

Tanone

Prasetya

2019

Int. J. Interact. Mob. Technol.

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<p>The development of food and beverage products increases over the years. The high level of food consumption led to the presence of new food and beverage brands produced in Salatiga. In accordance with this fact, Organoleptic Tests or in other words evaluation of food products could be conducted well if the obtained dataset had a complete, rapid, and accurate information. The required information could be clarified into the dataset that was used to calculate the testing. Manually calculating the process was a problem that usually appeared. As a result, losing or having a broken report on the organoleptic test often occurred. Mileage of the research setting became another problem that appeared when the research conducted out of the town, Salatiga. A combination of R&D method and application of algorithm was implemented in this research by using the performed stages. These stages started from the identification of problems to the testing of the systems. During the process of organoleptic testing, <em>Weka 3.8.2</em> was used as a tool to test the C4.5 algorithm and an implementation of the applied algorithm on the android. The results of this study revealed that the average classification accuracy of the J48 algorithm in Weka could achieve above 90% accuracy and average score of hedonic scaling system was in “agree” category. It also showed that the algorithm and the testing of the systems which implemented on android has a credible performance in classifying data.</p>

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Kajian Komparasi Algoritma C4.5, NAÏVE BAYES dan Neural Network dalam Pemilihan Penerima Beasiswa (Studi Kasus pada SMA Muhammadiyah 4 Jakarta )

Cited by 2 publications

References 0 publications

Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan

Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan

Designing and Implementing an Organoleptic Test Application for Food Products Using Android Based Decision Tree Algorithm

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