C4.5 algorithm is a decision tree algorithm group. This algorithm has input in the form of training samples and samples. While samples are data fields which we will use as parameters in classifying data. From the variable transaction frequency the company can see which customers are loyal to the company based on historical customer transaction data, but there are still some variables that make customers loyal to the company. These variables are age, customer gender, company sales gender, educational background, customer  transaction frequency. The company knows how to predict customers who will be loyal to the company based on the experience of some of the variables above, but the company does not know the most influential variable in the assessment of loyal customers because of some of the variables above are not interconnected and it is uncertain if one variable can make a decision whether the customer loyal. Based on the decision tree that has made the most influential attribute on customer loyalty is the educational background because it has the highest gain value of 1.545292721 and as the root of the decision tree while the client's gender does not significantly affect customer loyalty because it is always at the last node with the gain value which is 0.623919119.

Cooperatives are a forum that can help people, especially small and medium-sized communities. Cooperatives play an important role in the economic growth of the community such as the price of basic commodities which are relatively cheap and there are also cooperatives that offer borrowing and storing money for the community. Constraints that have been felt by this cooperative are that borrowers find it difficult to repay loan installments, causing bad credit. Because the cooperative in conducting credit analysis is carried out in a personal manner, namely by filling out the loan application form along with the requirements and conducting a field survey. Therefore there is a need for an evaluation to be carried out in lending to borrowers. To minimize these problems, it is necessary to detect customer criteria that are used to predict bad loans and to determine whether or not the elites are eligible to take credit using data mining. The data mining technique used is classification with the Naive Bayes method. Based on testing the accuracy of the resulting model obtained accuracy level of 59%, sensitivity (True Positive Rate (TP Rate) or Recall) of 46.80%, specificity (False Negative Rate (FN Rate or Precision) of 69.81%, Positive Predictive Value (PPV) of 57.89%, and Negative Predictive Value (NPV) of 59.67%.Abstrak-Koperasi merupakan suatu wadah yang dapat membantu masyarakat terutama masyarakat kecil dan menengah. Koperasi memegang peranan penting dalam pertumbuhan ekonomi masyarakat seperti harga bahan pokok yang tergolong murah dan juga ada koperasi yang menawarkan peminjaman dan penyimpanan uang untuk masyarakat. Kendala yang pernah di rasakan oleh koperasi ini adalah peminjam susah untuk membayar angsuran pinjaman sehingga menyebabkan terjadinya kredit macet. Karena pada koperasi dalam melakukan analisa pemberian kredit dilakukan secara personal, yaitu dengan cara mengisi lembar formulir permohonan peminjaman kredit disertai dengan persyaratan dan melakukan survey lapangan. Oleh karena itu perlu adanya evaluasi yang dilakukan dalam pemberian kredit kepada para peminjam. Untuk meminimalisir permasalahan tersebut perlu dilakukan pendeteksian kriteria-kriteria nasabah yang digunakan untuk memprediksi kredit macet serta untuk menentukan layak atau tidaknya peminja m dalam pengambilan kredit dengan menggunakan data mining. Teknik data mining yang digunakan adalah klasifikasi dengan metode naive bayes. Berdasarkan pengujian akurasi dari model yang dihasilkan diperoleh tingkat accuracy sebesar 59%, sensitivity (True Positive Rate (TP Rate) or Recall) sebesar 46,80%, specificity (False Negative Rate (FN Rate or Precision) sebesar 69,81%, Positive Predictive Value (PPV) sebesar 57,89%, dan Negative Predictive Value (NPV) sebesar 59,67%. Kata Kunci-Data Mining, Kredit Macet, Naive Bayes, Prediksi. I. PENDAHULUANKoperasi merupakan suatu wadah yang dapat membantu masyarakat terutama masyarakat kecil dan menengah. Koperasi memegang peranan penting dalam pertumbuhan ekonomi masyarakat seperti harga bahan pokok yang tergolo...

No abstract

In this study aims to determine the classification of Alzheimer’s disease, this disease is a dangerous disease that can eliminate memory loss and can even result in a loss of ability to remember. For this reason, early detection of this disease is needed so that it can prepare for medical treatment. In this study the proposed method is to compare several decision tree methods with feature or attribute selection using the Particle Swarm Optimization (PSO) algorithm with the Alzheimer OASIS 2 dataset: Longitudinal Data from kaggle.com. The results of experiments with ten-fold cross validation, by testing the decision tree algorithm before the feature or attribute selection is performed, the highest accuracy value is obtained from the random forest algorithm with a value of 91.15%. The feature selection process is carried out using the PSO algorithm and the experiment is repeated using the Decision tree, the PSO-based random forest algorithm has the highest accuracy value of 93.56% with a kappa value of 0.884. Feature or attribute selection using the PSO algorithm is proven to be able to improve the accuracy of the decision tree algorithm, and is included in the algorithm with a very good range of values.

The process of data collection and processing of student scores that is carried out continuously from year to year is felt to be unable to produce fast, precise and accurate information, because it takes a long time. Computerized information system processing student grades is expected to be able to ease the work of homeroom teachers, so that they can produce valid information in a short time and can be accessed anywhere. With good processing and management, value data processing will be easier, faster, more accurate. The purpose of this research is to build a web-based digital report card information system as a solution offered to help solve problems faced by schools. The system development method used is Extreme Programming (XP) which has several stages, namely planning, designing, coding, testing and Software Increment. The results of this study are the creation of an information system that can provide several advantages as well as efficiency and effectiveness in processing information and managing value data up to the printing of student report cards.

<p>Beras coklat memiliki kandungan magnesium, serat lebih tinggi dan indeks glikemik lebih rendah dari beras putih, diduga dapat mencegah kenaikan glukosa darah dan menurunkan lemak tubuh. Tujuan penelitian ini untuk mengetahui hubungan antara kepatuhan diet berbasis beras coklat dengan kadar glukosa darah puasa dan komposisi lemak tubuh pada pasien Diabetes Mellitus (DM) Tipe 2. Penelitian ini merupakan penelitian quasi experimental dengan rancangan one group pre test and post test design pada 18 pasien DM Tipe 2 yang memenuhi kriteria inklusi. Responden penelitian diberikan intervensi selama 3 bulan berturut. Pemeriksaan glukosa darah puasa dan komposisi lemak tubuh dilakukan sebelum dan setelah intervensi diberikan. Selama pemberian intervensi diet, 94.4% responden patuh diet. Setelah intervensi diberikan terjadi penurunan kontrol glukosa darah dari kategori buruk sebesar 27.7%, persentase lemak tubuh kategori tinggi sebesar 22.2% dan indeks lemak viseral kategori tinggi sebesar 22.2%, namun tidak terdapat hubungan antara kepatuhan diet dengan glukosa darah puasa, total lemak tubuh dan lemak visceral (p=0.339, p= 0.496, p=0.551, spearman). Kesimpulan dari penelitian ini bahwa pemberian diet berbasis beras coklat pada pasien DM Tipe 2 dapat menurunkan kadar glukosa darah puasa dan komposisi lemak tubuh namun tidak terdapat hubungan antara kepatuhan diet dengan ketiga parameter tersebut.</p>

<p class="Abstrak"><strong>Abstract:</strong> This research and development aims to produce listening test products for entry-level of BIPA students. The test products are packaged in the form of a website that can help carry out tests during a pandemic. To achieve this goal, a development design adapted from the Research Development Research (RDR) model is used. The results of this research and development are in the form of listening test products for beginner level BIPA students that are valid and reliable, reach test takers from various countries, and are equipped with a manual that makes it easy for test users.</p><strong>Abstrak:</strong> Tujuan penelitian pengembangan ini adalah menghasilkan produk tes menyimak untuk pelajar BIPA tingkat pemula. Produk tes tersebut dikemas dalam bentuk website yang dapat membantu pelaksanaan tes di masa pandemi. Untuk mencapai tujuan tersebut, digunakanlah desain pengembangan yang diadaptasi dari model pengembangan Research Development Research (RDR). Hasil penelitian dan pengembangan ini berupa produk tes menyimak untuk pelajar BIPA tingkat pemula yang valid dan reliabel, menjangkau peserta tes dari beragam negara, dan dilengkapi dengan buku panduan yang memudahkan pengguna tes.

In the digital era like today, technology is developing very rapidly. Computers have become a major requirement in business processes today. PT Suma Karya Gemilang is a company engaged in the construction sector. PT Suma Karya Gemilang in running its business is still not computerized such as submitting funds and making project expense reports. The impact of a system that has not been computerized causes ineffectiveness in work, frequent unintentional errors, frequent buildup of unprocessed documents, resulting in documents being easily lost and damaged if not processed quickly, making project expense reports often writing errors and inaccurate in the making. So that the design of a project financial information system with the Waterfall development method is a solution to the problems that exist at PT Suma Karya Gemilang. With a computerized system, the work process becomes more efficient and effective in supporting all company activities. The results obtained by using a computerized system reduce writing errors, report generation becomes accurate and effective, with the use of document databases becoming more organized and not piling up. Overall, a computerized system is much better in all aspects than a non-computerized system.