AbstrakPenelitian ini bertujuan untuk mengetahui gambaran efektivitas pembelajaran daring menggunakan media online selama pandemi covid-19 pada mata pelajaran matematika. Penelitian ini merupakan penelitian kuantitatif deskriptif yang fokus pada evaluasi pembelajaran menggunakan media online. Populasi penelitian yakni seluruh peserta didik SMA Negeri 1 Wajo yang diajar pada mata pelajaran matematika menggunakan metode daring. Sampel penelitian yakni peserta didik kelas XI MIPA 1 SMA Negeri 1 Wajo yang dipilih menggunakan teknik simple random sampling dengan mempertimbangkan homogenitas populasi. Instrumen pengumpulan data menggunakan kuesioner pembelajaran daring. Analisis data menggunakan statistik deskriptif. Hasil penelitian menggambarkan peserta didik menilai pembelajaran matematika menggunakan media online sangat efektif (23,3%), sebagian besar mereka menilai efektif (46,7%), dan menilai biasa saja (20%). Meskipun ada juga peserta didik yang menganggap pembelajaran daring tidak efektif (10%), dan sama sekali tidak ada (0%) yang menilai sangat tidak efektif. Akhirnya, untuk meningkatkan kualitas pembelajaran daring matematika selama pandemi covid-19, maka pendidik harus memenuhi sepuluh saran dari responden, yakni: (1) pembelajaran dilakukan melalui video call; (2) pemberian materi pembelajaran yang ringkas; (3) meminimalisir mengirim materi dalam bentuk video berat untuk menghemat kuota; (4) pemilihan materi dalam video harus berdasarkan kriteria bahasa yang mudah dipahami; (5) tetap memberikan materi sebelum penugasan; (6) pemberian soal yang variatif dan berbeda tiap peserta didik; (7) pemberian tugas harus disertakan cara kerjanya; (8) memberikan tugas sesuai dengan jadwal pelajaran; (9) mengingatkan peserta didik jika ada tugas yang diberikan; dan (10) mengurangi tugas.AbstractThis study aims to describe the effectiveness of online learning during the covid-19 pandemic in mathematics. This descriptive quantitative research focuses on the evaluation of online learning. The population of this study was all the students of SMA Negeri 1 Wajo who were taught mathematics. The research sample is XI MIPA SMA Negeri 1 Wajo was selected randomly with population homogeneity consideration. Data was collected by using an online learning questionnaire and analyzed descriptively. The result showed the presentation on students’ who were assuming learning mathematics was very effective with online learning was 23.3 %, the majority of students who assumed it was effective was 46.7 %, 20% of them assume it was nothing special, 10 % assume it was not effective, and 0% assume it was very ineffective . It also found from the study that to enhance the quality of mathematics online learning during the covid-19 pandemic, the teachers should full fill the respondent recommendations, they are; (1) the learning should be done with video call (2) the contents should be simple; (3) minimize the learning video capacity (4) the language that used in the video should be easy to understand; (5) the content should be explained before giving the task; (6) variety task for each student; (7) the task should come with clear instructions; (8) the task should be on schedule; (9) the task should be reminded to the students; (10) reduces the task.

Kebijakan pemerintah untuk belajar dari rumah selama masa pandemi Covid-19 membuat orang tua semakin banyak terlibat dalam pendampingan anak. Tujuan penelitian ini untuk mengukur peran orang tua selama anak belajar dari rumah, dan mengukur tingkat pendampingan belajar anak yang dilakukan orang tua selama masa pandemi. Pendekatan kuantitatif dilakukan dengan teknik statistik deskriptif, dan sampel penelitian sebanyak 40 orang tua peserta didik PAUD SKB Cerme Gresik. Teknik pengambilan sampel dilakukan dengan proportional random sampling, serta analisis data dengan descriptive statics frequencies dan persentase. Uji validitas menggunakan korelasi product moment dan Uji reliabilitas menggunakan Alfa Cronbach. Dari hasil penelitian dapat disimpulkan bahwa orang tua memiliki peran sebagai pembelajar anak, pemenuh kebutuhan anak, pemahaman spiritual, pengawasan, motivasi, dan penyedia fasilitas anak. Pendampingan belajar anak terlihat dari cara orang tua membantu kesulitan tugas anak, menjelaskan materi yang tidak dimengerti anak, dan merespon dengan baik semua pembelajaran daring dari sekolah.

Data mining merupakan pemprosesan sebuah informasi dari suatu database yang dapat digunakan untuk berbagai kebutuhan sektor swasta. Salah satu metode dalam data mining, yaitu Clustering yang bertujuan untuk menemukan pengelompokan dari serangkaian pola, titik, objek maupun dokumen. Algoritma K-Means clustering merupakan algoritma yang berperan penting dalam bidang data mining serta sederhana untuk diimplementasikan dan dijalankan. Selain itu, terdapat pengembangan varian dari metode K-Means  Clustering yaitu K-Medoids yang muncul sebagai penanggulangan kelemahan Algoritma K-Means yang sensitif terhadap outlier dikarenakan sebuah objek dengan sebuah nilai yang besar mungkin secara substansial menyimpang dari distribusi data. Penelitian ini membandingkan kedua algoritma pada suatu dataset. Adapun data yang digunakan merupakan data transaksi bongkar muat selama tahun 2017 pada PT Pelabuhan Indonesia I Cabang Dumai berdasarkan atribut agen, keterangan barang, jenis, dan jumlah ton. Dari percobaan yang dilakukan, diperoleh hasil pengolahan KMeans  hanya membutuhkan waktu rata-rata 1 detik sedangkan pengolahan data pada K-Medoids membutuhkan waktu rata-rata 1 menit 38 detik pada RapidMiner. Nilai DBI pada K-Means  lebih rendah dibandingkan KMedoids yaitu masing-masing 0.112 dan 0.119. Perolehan cluster dominan, menunjukkan bahwa agen Buana Listya Tama TBK, PT mendominasi diikuti agen Samudera Sarana Karunia, PT.

Data mining is the process of handling information from a database which is invisible directly. Data mining is predicted to become a highly revolutionary branch of science over the next decade. One of data mining techniques is classification. The most popular classification technique is K-Nearest Neighbor (KNN). But there is also the Modified K-Nearest Neighbor (MKNN) classification algorithm which is the derived algorithm of KNN. In this paper we will analyze the comparison of KNN and MKNN algorithms to classify the data of Conditional Cash Transfer Implementation Unit (Unit Pelaksana Program Keluarga Harapan) which consist of 7395 records. Comparative analysis is based on the accuracy of both algorithms. Before classification, K-Fold Cross Validation was done to search for the optimal data modeling resulted in data modeling on cross 2 with accuracy of 93.945%. The results of K-Fold Cross Validation modeling will be the model for training data samples and testing data to test KNN and MKNN for classification. Classification result produced accuracy based on the rules of confusion matrix. The test resulted in the highest accuracy of KKN by 94.95% with average accuracy during the test was 93.94% and the highest accuracy of MKNN was 99.51% with the average accuracy during the test was 99.20%, almost all testing from the first test up to the tenth, MKNN algorithm is superior and has better accuracy value than KNN so it can be analyzed that the ability of MKNN algorithm in accuracy is better than KNN. It can be concluded that MKNN algorithm is capable of handling accuracy better for classification than KNN algorithm, by ignoring other aspects such as computerization, time efficiency, and algorithm effectiveness.

<p>Koperasi mempunyai peranan penting bagi perekonomian Indonesia<strong>. </strong>Perkembangan koperasi di Indonesia saat ini cukup pesat, pada data Badan Pusat Stastitik 3 tahun terakhir yang di-<em>update</em> pada tanggal 20 Juni 2016 sementara menyebutkan jumlah koperasi aktif di Indonesia pada tahun 2015 sebanyak 150.223. Pusat Koperasi Unit Desa (PUSKUD) Provinsi Riau merupakan salah satu jenis koperasi sekunder dalam bidang pertanian. Koperasi ini menjadi salah satu penunjang perekonomian rakyat. Proses yang berjalan antara PUSKUD dan anggota adalah pengelolaan sisa hasil usaha (SHU) dan dalam permodalan. Permasalahan yang terjadi adalah partisipasi aktif dari anggota koperasi untuk menunaikan kewajiban masih kurang dari yang diharapkan. Untuk membantu mengatasi permasalahan tersebut, perlu dibentuk suatu pengelompokan Anggota PUSKUD berdasarkan Kabupaten/ Kota domisili dalam pembayaran Simpanan Wajib. Metode yang digunakan adalah <em>Data Mining Clustering</em> dengan algoritma <em>Fuzzy C Means</em>. Dari hasil pengklusteran, pada tahap akhir analisis diketahui, Terdapat 75 anggota yang tersebar pada wilayah Kabupaten/ Kota Rokan Hulu, Kampar, Indragiri Hulu dan Indragiri Hilir serta terdaftar pada tahun 80-an yang perlu untuk ditinjau  kembali. Hasil Pengujian Nilai Validitas PC, didapatkan sebesar 0,323732, dengan demikian kualitas <em>Cluster</em> masih jauh untuk mencapai kata optimal.</p><p><strong> </strong></p><p><strong>Kata kunci</strong>: <em>Clustering, Data Mining,</em><em> </em><em>Fuzzy C Means, Koperasi, Simpanan Wajib, Partition Coefficient</em></p><p class="Judul2"> </p><p class="Judul2"><strong><em>Abstract</em></strong><em></em></p><p class="Judul2"><em>Cooperatives have an important role for the Indonesian economy</em><em>. </em><em>The development of cooperatives in Indonesia is currently quite rapid</em><em>, </em><em>On the data</em><em> from Badan Pusat Statistik (BPS) </em><em> of the last 3 years updated on June 20, 2016</em><em> </em><em>While mentioning the number of active cooperatives in Indonesia in 2015 as much as 150,223</em><em>. Pusat Koperasi Unit Desa (PUSKUD) Provinsi Riau </em><em>is one of the secondary cooperative in agriculture</em><em>. </em><em>This cooperative became one of the supporting people's economy</em><em>. </em><em>The process that runs between PUSKUD dan members is the management of the remaining results of the business </em><em>and</em><em> </em><em>the</em><em> capital. The problem that occurs is the use of members of the cooperative to fulfill the obligations is still less than expected. </em><em>To help overcome these problems, it is necessary to form a grouping of PUSKUD Members by Regency / City domicile in the payment of M</em><em>and</em><em>atory Deposits</em><em>. </em><em>The method used is Data Mining Clustering with Fuzzy C Means algorithm</em><em>. From the results of the clustering, at the final stage of the analysis is known, There are 75 members scattered in the District / City of Rokan Hulu, Kampar, Indragiri Hulu dan Indragiri Hilir dan registered in the 80s that need to be reviewed. </em><em>Test Result Validity Value of Partition Coefficient, obtained for 0,323732, thus the quality of Cluster is still </em><em>far to</em><em> achieve </em><em>optimal</em><em>.</em></p><p class="Judul2"> </p><p><strong>Keywords</strong>: <em>Clustering, </em><em>Cooperative,</em><em> Data Mining, Fuzzy C Means, </em><em>M</em><em>and</em><em>atory </em><em>Deposit</em><em>, </em><em>Partition Coefficient</em></p>

Paddy is one of the important cereal crops as food a main  food for a third of the world's population, including Asia. Production of paddy rice plants can be improved through plant genetic improvement. The ebjective of this study was examine the genetic diversity, heritability, and correlation between the characteristics of several local upland rice cultivars. This study was carried out in Tamarenja Village, Sindue District, Donggala Regency, Central Sulawesi Province. It was began in May to October 2018. A Randomized Block Design with eight cultivars as a genotypic treatment and reapeted three times was used in this study. There were 24 trial plots in total. Variables observed included plant height, number of leaves, length of leaves, number of tillers, number of productive tillers, age of panicle exit, panicle length, harvest age, number of seeds per panicle, seed length, seed diameter, weight of 100 seeds, and total yield. The results showed that the genetic influences were more dominant than the environment on all observed variables except the weight of 100 seeds and seed diameter. The number of seeds per panicle, the number of tillers and the number of productive tillers were traits that have a high value on heritability and genetic progress. Panicle length, seed diameter and weight of 100 seeds were characteristics that have a high genetic correlation coefficient on upland rice yields. The weight of 100 seeds has a direct influence and high genetic correlation to the results so that it can be used as a direct selection criterion to increase upland rice yields.

Majors are important in determining student specialization. If there is an error in the direction of the student, it will certainly affect the education of subsequent students. In SMA Negeri 1 Kampar Timur, there are two majors, namely Natural Sciences and Social Sciences. To determine these majors, it is necessary to reference the average value of student grades from semester 3 to semester 5 which includes the average value of Islamic religious education, Indonesian, Citizenship Education, English, Natural Sciences, Social Sciences, and Mathematics. Naive Beyes algorithm is an algorithm that can be used in classifying majors found in SMA Negeri 1 Kampar Timur. To determine the classification of majors in SMA Negeri 1 Kampar Timur, training data and test data are used, respectively at 70% and 30%. This data will be tested for accuracy using a confusion matrix and produces a fairly high accuracy of 96.19%. With this high accuracy, the Naive Bayes algorithm is very suitable to be used in determining the direction of students in SMA Negeri 1 Kampar Timur.

The purpose of this research is to explain the effectiveness of online learning in growing collaborative learning of the students during Covid-19 pandemic. This research used qulitative research method. Data collection was through google form distributed to 57 subject teachers and the interview on the students who conduct online learning. The research results show that even though the teacher can utilize online learning application well, they still encounter difficulty in building collaborative learning among the students whereas collaborative learning is a pivotal thing in building active learning activity on the students. This occurs because there are various obstacles such as the presence of the students is in different places until it is difficult to do coordination, difficulty in accessing the internet network especially the students living in the region, the teacher finds difficulty in monitoring the students' activity during the online learning until the learning model is more on using lecture method. Therefore, the coordination and support from the government, parents, the school, even the teacher are necessary in creating online collaborative learning effectively. On the other hand, that online learning encourages the emergence of social distancing behavior and can minimize direct contact between the teacher and students.