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All Journal Dinamik JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Ilmiah Wahana Pendidikan Jurnal Informatika Polinema (JIP)

Yuyun Umaidah

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Author-ID : 2211623

Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Library & Information Science Social Sciences Other

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Clustering Tingkat Kedisiplinan Warga Bekasi Dalam Menjalankan Protokol Kesehatan Di Masa Pandemi Covid-19 Dengan Algoritme K-Means Andri Dwi Noviandi; Tesa Nur Padillah; Yuyun Umaidah
Jurnal Ilmiah Wahana Pendidikan Vol 7 No 4 (2021): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Health protocols during the Covid-19 pandemic are very necessary because health protocols can speed up breaking the chain of spreading the Covid-19 virus. Violations that are often found in the Bekasi city environment are related to health protocols, namely maintaining distance, wearing masks and washing hands, or using hand sanitizer. There are still many who do not comply with the rules of the health protocol. The purpose of knowing the cluster level of discipline towards health protocols into five clusters spread by the number of respondents in various sub-districts in the city of Bekasi with the categories of discipline, somewhat disciplined, rarely disciplined, less disciplined, and undisciplined. Data mining is the process of extracting data to obtain new information. The technique used in this research is simple random sampling. This study using the CRIPS-DM methodology. This study calculates the k-means algorithm by obtaining a value of k = 2. The results of the test using the RapidMiner Studio 9.3 tools obtained two clusters or 2 categories of discipline levels against health protocols, namely cluster 0 with a percentage of 55.08% which is categorized as the most disciplined level, and cluster 1 with a percentage of 44.92% which is categorized as the least disciplined level. The results of clustering are evaluated by using the Silhouette Coefficient with the best cluster, k = 2 with a value of 0.926989, which is the best cluster.

Penerapan Data Mining untuk Klasifikasi Penjualan Baju Muslim Dimasa Pandemi Covid-19 Menggunakan Metode Algoritma C4.5 Chella Aprianti; Muhammad Faishal; Yuyun Umaidah
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 1 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

During this Covid-19 pandemic, it has become a global pandemic that continues to experience an increase in daily infection rates in Indonesia. The most obvious example is the decline in the income turnover of MSME actors, this impact requires a special strategy to increase sales during the pandemic. Garaya Collection store is a store that is engaged in selling Muslim clothes, but from the various types of clothes that are sold, not all of them are necessarily sold and are not selling well. Sales data, purchases of goods, incoming goods, and unexpected goods expenditures at the Garaya Collection Store are not well structured, so the data only functions as a store archive and is not used for developing sales strategies. Therefore, it is necessary to apply the classification using the C4.5 algorithm data mining method at the Garaya Collection Store. The C4.5 algorithm can be applied to the Garaya Collection Store to determine the sales of clothes that are selling very well, selling well, and not selling well. Application of the C4.5 Algorithm method at the Garaya Collection Store, namely the classification of sales data stock. Then using the C4.5 Algorithm method on rapidminer, it is done by entering data on categories, brands of goods, prices, selling times, and selling well. Storage of data taken through MS.EXCEL, the data is connected to the rapidminer tools and will be processed and in the form of a decision tree. After that, rapidminer will generate which ones are sold, sold, and not sold well.

Analisis Sentimen Pada Pembelajaran Daring Menggunakan Metode K-Nearest Neightbour Alfina Novi Yanti; Yuyun Umaidah; Rini Mayasari
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 12 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Corona Virus Disease-2019 has been rampant throughout the world, including in Indonesia. Covid-19 has greatly affected several sectors, one of which is the education sector. The Indonesian government itself implements a policy of courageous learning or distance learning which is carried out from their respective homes. SMA Negeri 3 Cikampek is one of the schools that implements bold learning, this bold learning affects the achievement of learning outcomes. Various students from this bold learning, there are those who agree that this bold learning has an effect on the achievement of learning outcomes and some even give a response that does not agree because it has no effect. For this reason, data mining is applied, especially text mining with the K-Nearest Neighbor algorithm to analyze various student responses to bold learning. The data used is a questionnaire data as much as 592 data. Before the data mining stage, the data is divided into 80% of the training data and 20% of the testing data. The classification with K-Nearest Neighbor quality is 85.35% accuracy, 81.19% precision, 92.42% recall and Auc is 0.902. Based on the quantity of negative classes which are more than positive classes, it is known that students will not agree to bold learning because it affects the achievement of learning outcomes. Keyword: Text mining, Online Learning , Covid-19, K-Nearest Neightbour.

Pemetaan Daerah Produksi Perkebunan Kelapa Sawit Pada Provinsi Indonesia Menggunakan Algoritma K-medoids Fatma Eka Zulfiakhoir; Yuyun Umaidah; Purwantoro Purwantoro
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 16 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

In the National Leading Plantation Statistics yearbook issued by the Directorate General of Plantation, Ministry of Agriculture of the Republic of Indonesia, it is stated that Indonesia is the world's number one producer of palm oil and also the owner of the largest oil palm plantation area in the world. Indonesia's palm oil production reached 43.5 million tons, with an average growth percentage of 3.61%. The Coordinating Minister for Economic Affairs considered that the palm oil sector had a major role in the economy during the Covid-19 pandemic. The palm oil sector is able to maintain 16.2 million workers who depend on it in the midst of the pandemic. Therefore, it is necessary to map oil palm plantations from each province of Indonesia so that it can be seen which areas have the potential to produce oil palm. Thus, later the area can be maximized again productivity. Then, to find out also which provinces have a low potential level of palm oil production so that later the productivity of the area can be assisted by analyzing what patterns can be found from the highest potential level of oil palm production. In this research, mapping will be carried out using clustering techniques in data mining, using the k-medoids algorithm. The results showed that there were 3 clusters, namely cluster 1 (category of provinces with low production areas of oil palm), cluster 2 (category of provinces with high production areas of oil palm), and cluster 3 (category of provinces with medium production areas of oil palm). ). The silhouette coefficient evaluation result in the model calculation using this technique is 0.64. This range value is included in the medium structure criteria (good cluster structure).

Co-Authors Alfanda Novebrian Maharadja Alfina Novi Yanti Andri Dwi Noviandi Apriade Voutama Aries Suharso Chella Aprianti Farras Salsabila Fatma Eka Zulfiakhoir Genta Triyandana Heryana, Nono Ika Fitrianti Iqbal Maulana Jaman, Jajam Haerul Lala Aprianti Putri Muhammad Faishal Purwantoro Purwantoro Rijal Abdulhakim Rika Nursyahfitri Rini Mayasari Riva Arsyad Farissa Stevanus Ertito Pramudja Syahrul Dwi Hilda Tesa Nur Padillah Tiara Safitri Wahyuningrum Ayu

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