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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

Training Evaluation Analysis Using Text Mining Mas Akhmad Nainunis; Imam Yuadi
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.27607

Abstract

Training evaluation is an evaluation of the results of training that has been carried out. This evaluation includes technical and non-technical factors which are very important for the company to pay attention to when implementing training in the future. Many companies only implement training evaluations as a formality and only include evaluations that are limited by choice, such as closed questionnaires, training evaluations using open questionnaires can provide the freedom to provide positive or negative input that can be of concern to the company. This research aims to find out the words or topics that appear most frequently in open comments on training evaluation results by using the FP Growth algorithm and association rules to find out the relationship between topics or words from the training evaluation results. They are applied to 516 open-ended comments submitted via the post-training questionnaire. The research results showed that 15 association rules were created using Rapidminer using the FP-Growth algorithm with a minimum support of 0.02 and a minimum confidence of 0.5. All rules have a lift value>1 which indicates that all rules are valid or have a strong association relationship. This research can determine the pattern of comments or suggestions given by workers regarding training evaluation.
Implementation of Supervised Learning Method In Grapevine Leaf Classification Lifindra, Stevanie Aurelia; Yuadi, Imam
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.31633

Abstract

Grapevine leaves are a type of leaf variety that is difficult to identify because it will take time if processed manually so research will be carried out using the help of machine learning. This research aims to classify 5 varieties of grapevine leaves using orange data mining and several classification methods namely k-Nearest Neighbors (kNN), logistic regression, random forest and support vector machine (SVM). The dataset used is 500 images and 5 classes where each class consists of 100 images, namely Ak (100), Buzgulu (100), Ala_Idris (100), Dimnit (100), and Nazli (100). The stages in the analysis process are to enter the image into orange data mining by passing several stages so that the image dataset can be processed and read on the test and score so that the confusion matrix can be obtained. The results of the research conducted using orange data mining show that classification using logistic regression gives the best results at a precision value of 0.848% and a recall value of 0.847%. This research shows that classification using orange data mining also provides good results, besides that this research can also help in the classification process so that it does not require a long time.
Co-Authors AA Sudharmawan, AA Abdul Halim, Yunus Alifka Cellina Velby Anastasya, Diva Berta Andini, Aulia Rizqi Anggraini, Pramudya Galuh Suci Anita Elizabeth Wettebossy Artha Rachma Widiastuti Azmi, Muhammad Izharul Berliani, Kezia Putri Bias Vilosa Christia, Tifani Dewi Condro Rahino Mustikaning Pawestri Dama Putri, Kania Dewanty, Alifia Kaltsum Endang Gunarti Fadilia Rinarwastu, Fadilia Febriano, Rizki Dwi Ferdiansah, Gilang Fitri Mutia, Fitri Fitria Wulandari, Martina Frisca Maria Unas Gunarti, Endang Halim, Yunus Abdul Handari Niken Anggraini Hapsari, Ratih Addina Hardevianty, Melissa Yunda Hasna, Dhia Alifia Izdihar Hendrawati, Lucy Dyah Hikmah Sabrina Hartianingrum Ira Puspitasari Irvan Zidny Ismi Choirunnisa Prihatini Kartika Sari, Della Kezia Rahmawati Santosa Koko Srimulyo Lathifah, Lathifah Lestari, Santi Dwi Desy Lifindra, Stevanie Aurelia M Kafi Maulana Mahardika, Synthia Amelia Putri Margono, Hendro Marsaa Salsabiila Mas Akhmad Nainunis Maulidah, Nofiyah Mochammad Edris Effendi Nabilla Salsabil Damayanti Zahraa Nazikhah, Nisak Ummi Niken Ayu Pratiwi, Bertha Novia, Asradiani Nur Muhammad, Rizqi Nurul Firdausy Owen Baihaqie Prasetyo Yuwinanto, Helmy Prasyesti Kurniasari, Meinia Prayitna, Thomas Wigung Aji Putra, Dwi Permana Putri Kinanti, Novrianti Putri, Selviana Azzira Ragil Tri Atmi, Ragil Tri Rahmadani, Sinta Raka Gading Raihanzaki Rosiana, Lidya Rosyani, Widha Sabayu, Brian Safina Innaf Mia Ardelia Santoso, Yuniawan Heru Sari, Tri Kartika Setiadi, Yusuf Sheva Alana Brilianty Sinta Rahmadani Soesantari, Tri Sugihartati, Rahma Suhada, Hofur Tri Atmi, Ragil Tri Hadi Wicaksono Ullin Nihaya Vivia Adriyanti, Elvetta Wardani, Hesti Ari Wildan Habibi Yuwinanto, Helmy Prasetyo