Klasifikasi Terjemahan Ayat Al-Quran Tentang Ilmu Sains Menggunakan Algoritma Decision Tree Berbasis Mobile

Setiawati, Devi; Taufik, Ichsan; Jumadi, Jumadi; Zulfikar, Wildan Budiawan

doi:10.15575/join.v1i1.7

Cited by 15 publications

(9 citation statements)

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“…The selected features will differentiate a criterion from other criteria in the same node. This flexibility can improve the quality of the decision's results [21].…”

Section: Modeling With Decision Treementioning

confidence: 99%

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Depression Detection on Twitter Social Media Using Decision Tree

Hidayatullah

Maharani

2022

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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Depression is a major mood illness that causes patients to experience significant symptoms that interfere with their daily activities. As technology has developed, people now frequently express themselves through social media, especially Twitter. Twitter is a social media platform that allows users to post tweets and communicate with each other. Therefore, detecting depression based on social media can help in early treatment for sufferers before further treatment. This study created a system to detect if a person is indicating depression or not based on Depression Anxiety and Stress Scale - 42 (DASS-42) and their tweets using the Classification and Regression Tree (CART) method with TF-IDF feature extraction. The results show that the most optimal model achieved an accuracy score of 81.25% and an f1 score of 85.71%, which are higher than baseline results with an accuracy score of 62.50% and an f1 score of 66.66%. In addition, we found that there were significant effects on changing the value of the maximum features in TF-IDF and changing the maximum depth of the tree to the model performance.

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“…The selected features will differentiate a criterion from other criteria in the same node. This flexibility can improve the quality of the decision's results [21].…”

Section: Modeling With Decision Treementioning

confidence: 99%

“…Then, based on the root node, it will be split into branches representing the possible decision. Finally, the result is a leaf node that represents the resulting class [21]. (1984) to refer to DT algorithms for classification or regression modeling.…”

Section: Modeling With Decision Treementioning

confidence: 99%

Depression Detection on Twitter Social Media Using Decision Tree

Hidayatullah

Maharani

2022

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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“…Decission tree sangat mudah dimengerti dalam mengolah data yang kecil [11]. Decision tree merupakan metode yang tanpa mengurangi hasil dari kualitas yang didapat dengan menggunakan kriteria setiap node [12].…”

Section: Pendahuluanunclassified

Analisis Prediksi Kelulusan Mahasiswa Menggunakan Decission Tree Berbasis Particle Swarm Optimization

2020

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Good accreditation results are the goal of the college. With good accreditation, prospective students can glance at and enter the tertiary institution. To achieve this, there are several aspects that affect good accreditation results, one of which is graduate students who play an important role in determining accreditation. Timely graduate students can benefit the college or a student. Graduates can be predicted before the final semester using a method one of which is the decision tree. Decision tree is a method that is simple and easy to understand by producing rules in the form of a decision tree, but using a decision tree model alone is not enough to produce optimal results. So we need a method for optimization that is particle swarm optimization with advantages can improve accuracy by eliminating unused features. From the results of research with primary data of 2000-2003 graduate students in Amik PPMI Tangerang explained that the particle swarm optimization method can increase accuracy by 87.56% and increase by 01.01% from the decision tree method with a value of 86.55%. From the particle swarm optimization method can also find out which unused attributes have no weight, so that way can improve accuracy. From the results of the increase, it can be used by the Amik University of Tangerang to prevent students from graduating on time.

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“…Text pre-processing means to prepare initial text data that is still various to be used as regular data that can be subjected to or applied by several existing text mining methods [39]. Those text pre-processing process among others: (1) Tokenizing, tokenization process is useful for breaking every sentence from all knowledge documents into terms by using tab delimiters and space characters [40], [41]; (2) Case Folding, which is a step that changes all the letters in the document into letters of uniform size, usually lowercase letters [42]; 3Filtering and Stopwords Removal, which is removing all of the stopwords (unimportant words or words that do not store meaning) that frequently appear in document and will affect the quality of result [43]; then (4) Stemming process, which is stemming process is useful to change a word into its basis so that will increase the quality of result [44].…”

Section: Fig 2 Work Flow Of Chatbot In Quetion Answering Systemmentioning

confidence: 99%