Prediksi Kepuasan Mahasiswa Terhadap Pelayanan Akademik Menggunakan Model Decision Tree

Perguruan Tinggi merupakan sebuah lembaga pendidikan dimana didalamnya mempunyai tugas dalam pelayanan akademik. Kepuasan mahasiswa dalam memperoleh pelayanan akademik  merupakan hal yang sangat penting dalam menilai sebuah Perguruan Tinggi. Tujuan dari penelitian ini adalah agar dapat mengetahui bagaimana tingkat kepuasan mahasiswa program studi Teknik Informatika dalam hal memperoleh pengajaran oleh dosen, mengenai sarana dan prasarananya. Metode klasifikasi dan prediksi yang digunakan pada penelitian ini diambil dari salah satu model Decision Tree yaitu algoritma C4.5. Algoritma C4.5 berfungsi untuk mengekspolari data, menemukan hubungan tersembunyi antara sejumlah calon variabel input dengan sebuah variabel target. Hasil pengukuran yang didapat adalah nilai akurasi sebesar 94,23%. Nilai recall dari setiap kelas sebesar 94,12% untuk kelas Ya dan 100% untuk kelas Tidak. Sedangkan nilai presisi setiap kelas adalah sebesar 100% untuk kelas Ya dan 25% untuk kelas Tidak

Korelasi CO2 Terhadap Suhu dan kelembapan Dengan Multivariate Linear Regression

Sekarang ini keadaan udara di daerah perkotaan  sudah sangat tercemar oleh polusi. Semakin banyak gas CO2 yang mulai menyebar ke udara dapat menyebabkan meningkatnya suhu udara.. Hal ini dikarenakan bahwa CO2 dapat meningkatkan suhu di permukaan bumi. CO2 mempunyai peran yang dapat menyebabkan pemanasan global karena gas CO2 mempunyai  di udara bebas dan dapat menyerap panas Matahari sehinggs suhu Bumi meningkat dampak pencemaran udara seperti asap kendaraan, asap rokok, asap dari pembakaran pabrik, dan kontribusi terbesar dalam pemanasan global mempunyai pengaruh sebesar 50% dan mempunyai lama hidup 50 200 tahun di atmosfer. Peningkatan suhu udara dan konsentrasi CO2 merupakan masalah yang sering terjadi pada daerah perkotaan dimana salah satunya adalah meningkatnya jumlah kendaraan bermotor sehingga konsentrasi CO2 juga ikut meningkat. Dengan melihat korelasi CO2 Terhadap Suhu dan kelembapan Dengan mengunakan Multivariate Linear Regression, kita dapat melihat bagaiman korelasi antara suhu serta kelembapan. Regresi linier multivariat merupakan model regresi linier dengan lebih dari satu variabel respon Y berkorelasi dan satu atau lebih variabel prediktor X. Hasil penelitian menunjukkan bahwa  Dalam penelitian tersebut dikatakan bahwa terdapat korelasi antara CO2 suhu serta cahaya.

Decision Tree Implementation in IT Job Recommendation System

Employment is the primary activity that humans engage in to generate income. With the advancement of technology and research, there are many new job opportunities leading to confusion in choosing a job path. This leads to individual confusion in making job choices. Ignorance of one's own talents and personality, as well as ignorance of the various options available, can be the source of this ignorance. This research aims to develop a Decision Tree model to assist users in determining the appropriate IT field. The system uses AI Project Cycle and data processing tools such as Google Collaboratory, which is based on Python programming language. The results show that the Decision Tree algorithm can be applied to recommend jobs in the IT field to help users find suitable fields in the IT field

An Examination of Negative Correlations Using Pearson Correlation Analysis to Optimize the Diversification of Cryptocurrency Portfolios

The purpose of this study is to employ the Pearson correlation approach in order to assess the association between different types of cryptocurrencies. The dataset included in this research comprises daily peak price information for 10 distinct categories of cryptocurrencies with the biggest market capitalizations from October 1, 2017 to December 31, 2022. Assessing and computing the correlation between cryptocurrency pairs with the Pearson correlation coefficient is the objective. The information utilized in this study was acquired from the website www.coinmarketcap.com. Pairs of stablecoins and crypto coin assets have the largest negative correlation, according to the findings of this study, in contrast to pairs of crypto currency assets. The pair ETH-BNB has the strongest positive correlation with a value of 0.948, while the pair LTC-USDT has the most negative correlation at -0.347. In order to replicate the impact of the negative correlation on trading activities, an exchange simulation was performed between the LTC and USDT pairings. Based on the outcomes of the simulation, the asset rise resulting from the exchange of the LTC and USDT pair from January 1, 2022 to December 31, 2022 was 12.09 percent. During the same time period, the asset's value would have declined by -48.69 percent if LTC was held. Conversely, an expansion of the time period from October 1, 2017 to December 31, 2022 yields an asset gain of 251,047.85 percent as a consequence of the exchange between LTC and USDT. Those individuals interested in reducing risk and diversifying their portfolios with cryptocurrency investments may find this information highly beneficial. The results of this research offer significant contributions to the current body of literature on bitcoin investment and offer investors valuable informatio

Sistem Pendukung Keputusan Penyesuaian Nutrisi Makanan Berdasar Rekam Medis Pasien Berbasis Forward Chaining

Fulfilling nutrition for patients certainly does not only pay attention to the last illness they suffered, but nutritionists also need to pay attention to the patient's medical history. Providing certain foods to support the body's recovery after treatment for certain diseases may not necessarily be in accordance with the history of previous illnesses. Fulfilling nutritional intake according to certain disease conditions is not easy, especially if the patient has a medical history with a variety of diseases, so nutritionists need to be more selective in providing nutritional intake from a number of alternative foods that will be provided. A management decision system based on artificial intelligence is able to choose a food balance that is balanced with the various complaints experienced by patients. The method used in the food management information system for medical records uses the forward chaining method, namely by determining forward, in this case, food nutritional information that is suitable for the patient, by reading the facts that have been arranged as a representation to produce a conclusion. The accuracy value resulting from comparing manual nutrient selection and using forward chaining was 86

Kombinasi Analytical Hierarchy Process dengan Weighted Product untuk Penerima Beasiswa Prestasi Sistem Pendukung Keputusan

Scholarships are an appreciation given by universities in the form of educational assistance, one of which is for prospective students who have achievements in non-academic fields. Mercu Buana University Jakarta provides as many as 20 quotas per year for merit scholarships. The decision-making process for merit scholarship recipients is still focused on manual calculation using the average value method process. Based on these problems, a study was conducted to design a decision support system using analytical hierarchy process and weighted product methods. Variables used in achievement weighting, level, test scores. The process of weighting the AHP method produces an achievement priority value of 0.260, a level of 0.633, and a test score of 0.106 and the results on the consistency criteria matrix are 0.033. The results of the WP ranking are the scores on the achievement criteria, namely -0.260, the level is 0.633 and the test score is 0.106. The results on the user acceptance test are 84.4%, it can be concluded, functionality can be accepted by user

MANAJEMEN SISTEM PENILAIAN KINERJA GURU TAMAN KANAK-KANAK DENGAN SIMPLE ADDITIVE WEIGHTING

Teacher performance according to Law Number 14 of 2005 includes the main activities of planning, learning, implementing, assessing learning outcomes, mentoring and training children as well as additional tasks related to the main activities in accordance with the main workload. Teacher performance influences student learning outcomes, with good teacher performance it should produce good quality students as well. Therefore, it is natural that teacher performance needs to be measured every period. The assessment certainly contains the main and additional tasks. Based on these problems, it is also necessary to improve the existing performance appraisal system. There needs to be an appropriate method to assist the teacher performance assessment process, one of which is the weighted method, namely simple additive weighting (SAW). Performance assessment every semester using the SAW method will be able to bridge the results of increasingly better teacher performance. The assessment is carried out on a weighted basis for each parameter. The final result is a ranking of the performance of all teachers in descending orde

DECISION SUPPORT SYSTEM PEMBUKAAN LOKASI BARU JASA SERVIS MOTOR BERBASIS PROFILE MATCHING

As the volume of motorbikes increases, the number of motorbike service outlets also increases. However, not all service places get customers equally, from the customer's side various variables really determine visits such as location, level of spare parts availability, level of service to consumers and price. Likewise, in terms of service owners, when opening a new service location, they need to pay attention to various variables such as proximity to residential areas, number of competitors, capacity of passing vehicles, and proximity to spare parts suppliers. To collaborate several influential variables to produce a decision regarding the right place, a method is needed that is capable of carrying out calculations to produce a ranking of locations that will have an influence. One method that can be offered is profile matching. This method performs by finding the difference between the weight value determined at the beginning and the input value for each location object. The ranking results of all location objects can be used as alternative locations for appropriate service locations.

Robusta London Coffee Price Forecasting Analysis Using Recurrent Neural Network – Long Short Term Memory (RNN – LSTM)

Coffee price forecasting has a significant role in preventing price fluctuations at a time. Therefore, a method is needed that can be used to forecast the price of coffee. This study discusses the analysis of coffee price forecasting using the Recurrent Neural Network – Long Short-Term Memory (RNN – LSTM) method. This study will be determined the best LSTM model that aims to get the results of forecasting the price of London robusta coffee with the smallest  Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) values. Using the LSTM model with units of 128 and dropouts of 0.1, forecasting the price of London robusta coffee has an RMSE value of 1,303 and MAPE of 3.53%. Therefore, the LSTM model can indicate the cost of London robusta coffee with an accuracy rate of 96.47%.

Distributed MD5 Brute Force Using Message Passing Interface (MPI) on ARM Architecture

Over the years, there has been a computing paradigm shift towards smart devices. However, the security aspect of this type of device is questionable. In this research, the writer provides a design, implementation, and testing of a distributed MD5 brute-force attack method. Testing is performed using two systems. The first system is an ARM Cluster consisting of four single-board computers. The second system is a conventional server with two Xeon processors. From this research, the writer wants to answer the question of whether distributed brute-force attacks using IoT nodes can be realized in the real world by doing a comparison between increases of ARM Cluster performance with node addition to conventional server performance. From the test result, Xeon model performance is equivalent to 8 ARM Clusters and around 30 ARM nodes are required to match Xeon model performance