Simulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS

The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.

Klasterisasi Penempatan Siswa yang Optimal untuk Meningkatkan Nilai Rata-Rata Kelas Menggunakan K-Means

The implementation of learning by teachers can measure the quality of schools and students. Schools with diverse student backgrounds need to take strategic steps in managing learning to get optimal learning outcomes. Good learning designs and techniques can motivate students' interest in learning. The teacher's role is very important in managing learning to create an effective teaching and learning process. Data Mining or also known as Knowledge Discovery in Database (KDD) is the process of extracting knowledge from large data to find new patterns to get new knowledge and information. Data Mining technology is used to explore existing knowledge in the database. One of the methods used in data mining is clustering with the K-Means algorithm. This study aims to conduct student clustering to obtain a balanced class composition in order to improve the quality and student learning outcomes as seen in the increasing in the class average score. The data processed in this study came from the main school data as many as 90 students of the XI class of Computer Network Engineering Skills Competency at SMKN Negeri 2 Padang Panjang in the 2020/2021 school year. The variables used in data processing are student scores, parents' income and the distance from where students live to school. The student clustering calculation using K-Means succeeded in grouping 90 students into 3 clusters where cluster 1 totaled 47 students, cluster 2 totaled 10 students and cluster 3 totaled 33 students. Each member of the cluster will be divided evenly into 3 groups studying to get a balanced class composition. This research can be used as a basis for decision making by schools in clustering student placements to improve learning outcomes. By the increasing in the grade point average, the school average score will also increased.

Sistem Pakar dalam Mendiagnosis Penyakit Mata dengan Menggunakan Metode Forward Chaining

The eye is one of the organs in the body that has an important role in human life, because the eye is one of the organs that has a function as vision in carrying out every activity. Eye health really needs to be maintained by diligently consulting or having your eyes checked by a doctor so that vision remains clear and there are no eye problems when looking at objects around us. However, eye health is often neglected, so that many various diseases can attack the eye. If not handled properly, diseases that attack the eye can cause visual disturbances and lead to blindness. Therefore, the eye must be kept healthy and kept clean because it is a very important organ of the human body. The purpose of building this expert system is to assist the public in diagnosing eye diseases from the symptoms that are being felt. This expert system will be a way out of eye problems that are suffered by the community, In this way people no longer have trouble going to the doctor. All data and facts to be processed are obtained from an expert, the method used in diagnosing this eye disease is the forward chaining method to apply the rules of the 28 symptoms and 8 diseases described by the expert. The results of the diagnosis using the Forward Chaining method is a very good level of accuracy in determining the type of eye disease that is suffered by the community and can provide early prevention for users who use this expert system.

Pemilihan Kualitas Gambir dengan Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA)

Gambier (gambir plantae) is an half of perdu plantation which in separated in several regions of Indonesia. It is especially live in Sumatra, Java, Maluku, and Burneo. In West Sumatra province, gambir is used to component for menyirih (betle) and also the farmer of gambir asproduction as. It is reserving from hot water. Extraction come from the leaves and twigs of gambir in depositor forms, then printed and then turned into dried forms. The gambir farmers usually sell their productions to the collectors with a certaibty prices. Gambir has many qualities based from it processing, catechin contains, colors, ash contains, water contains, and also its density. Some its barries often occurs from the gambir processing being into product, which a minusly quality suffers, that cause gambir price in decrease or not to expensive conditions in the market by using support decision by Multi-Objective Optimization by Ratio Analysis (MOORA) methode is a multi objektives system from which can be optimated some atributes whom contradicting each other in simultaneously, either lost profit (cost) or getting profit (benefit), the system using these methode used to choose some gambir qualified form for determine its price. These data of sample taken form Pesisir Selatan gambir, which the research result farmed that gambier ranked can be as support as some decisions to make the best gambir as price decision as. Form theseresearch could be conclude that the best gambir have an higher catechin contains, low water contains, a slightly ash contains, with a yellowish skin, and have as highest as density. Based on the data of sample of research, the best gambier in qualified in getting from Siam and pian with the grade in 0.163 with the good one criteria condition. From gambier standardization, all of gambier which have upper grade standars, qualified into good gambier quality, gambier with high quality or good can give an expensive price that encourages some gambir farmers in motivation to process gambir product being increase gambier quality that can be improve the price selling gambir as well as the purchase of gambier products.

Data Mining dalam Mengukur Tingkat Keaktifan Siswa dalam Mengikuti Proses Belajar pada SMP IT Andalas Cendekia

The learning process is essentially to develop the activities and creativity of students through various interactions and learning experiences. The teacher is the most important factor in the process of improving the quality of education. In addition, student learning activeness is also an important basic element for the success of the learning process. The quality and activeness of students in learning at school has a lot of diversity which makes students have different levels of understanding, this needs to be a concern for the school, especially teachers as teachers and educators of students in schools. The purpose of this study is to measure the extent to which students' ability to undergo the learning process as well as a reference and evaluation material for the school in the success of educators when carrying out the teaching and learning process. In this study the data were sourced from the Integrated Islamic Junior High School Andalas Cendekia Dharmasraya which consisted of several variables, namely the presence of student data, Academic value (knowledge), Psychomotor value (skills), Affective value (spiritual and social). In grouping the data, the appropriate method in this study is the Clustering method with the K-Means Algorithm. The results of this study obtained 3 groupings of students, namely students who are very active, students who are active and students who are less active. This research is used as a guideline for teachers in the field of study in selecting students to participate in competitions and Olympics, and can be used as a benchmark for schools of the ability of educators in the teaching and learning process.

Optimalisasi Pelayanan Perpustakaan terhadap Minat Baca Menggunakan Metode K-Means Clustering

Knowledge Discovery in Database (KDD) is a structured analysis process aimed at getting new and correct information, finding patterns from complex data, and being useful. Data mining is at the core of the KDD process. Clustering is a data mining method that is suitable for optimizing library services because it can cluster books effectively and efficiently, with the K-Means algorithm data can be clustered and information from each centroid value of each cluster. Library services can optimize the placement of books so that students can quickly find books according to their reading interest more effectively and can be attracted to other books because they are in one grouping. Meanwhile, the library can prioritize the procurement of the next book. Optimization of library services in the cluster using the K-Means method. Clustering interest in reading has the criteria for the number of books available, borrowed books, and the length of time the books are borrowed. The book data is clustered into 3, namely very interested, in demand, and less desirable. After doing the calculation process from 40 samples of book types, it resulted in 6 iterations, and the final results were 3 clustering, namely cluster 1 of 4 books that were of great interest, cluster 2 of 20 books that were of interest, and cluster 3 of 16 books that were less desirable. This research can be used as a recommendation reference for optimizing library services both for the layout and procurement of books by prioritizing the types of books that are of great interest.

Akurasi dalam Identifikasi Penyakit Sapi Pesisir Menggunakan Metode Forward Chaining

Coastal cattle are livestock that have economic value, such as selling beef and cattle breeds. Cow disease can cause the quality of its sales to decrease. This study aims to help cattle breeders to determine the type of cow disease, from the symptoms that exist in these cows. So that the prevention of the risk of cow disease can be avoided. All data used are sourced from experts. In determining the type of disease in cows, the Forward Chaining method is used. The fact-finding technique is then put into the predetermined rules to get a conclusion. Making a website based expert system makes it easy for breeders to access it online. The accuracy of the system has been tested by related parties so as to produce fast and efficient information. From research, it can help breeders in diagnosing the symptoms experienced by cows and the test results can detect the type of disease accurately.

Prioritas Pengadaan Buku Berdasarkan Data Kerusakan dan Kehilangan Menggunakan Metode Simple Additive Weighting

Supplying book which is estimated each year can fulfill the availability and requirement of books. With supplying book that has been done, it can increase the students reading interest in teaching and learning process. The frequency of using book in learning cause the book will be damaged or lost. The aim of this research is to find out the priority of supplying book based on damaged and lost data so that it can be used as a reference to determine the main priority in supplying book. If this priority can be determined, it will give the effect towards madrasah as well for librarian. The effect for madrasah is to give information about priority supplying book at school’s library. For librarian, the effect could be concluded as consideration in making decision to supplying the book at school’s library. To analyze the research, the researcher used 40 broken and lost data. Which is the broken data was obtained from the librarian of MAN 2 Kota Padang Panjang. In this research, the researcher used the Simple Additive Weighting with PHP programming and MySql database. The main concept of Simple Additive Weighting method is to find out the total rating performance for each alternative. The experiment of broken and lost data is done based on the alternative book which is normalized by attribute criteria (benefit or cost). The broken and lost data criteria was consisted of 4 criteria, they are 1 book’s stock criteria, 2. Book’s sheets criteria, 3. Book’s cover criteria, and 4. Book’s code criteria. The result ranking towards Simple Additive Weighting method based on 40 experiment data was found that 3 alternative books was obtained as priority in supplying book, they are Akidah Akhlak XI, Al Quran Hadist XI, and Ushul Fikih XI, which the Akidah Akhlak XI is the main priority.

Tingkat Efisiensi Penggunaan Resep Dokter Spesialis Menggunakan Metode K-Means Clustering

The National Formulary (Fornas) is a list of drugs stipulated in a Decree of the Minister of Health of the Republic of Indonesia, which is used as a guideline for hospitals in drug supply for participants of the National Health Insurance (JKN) program. Doctor's prescription is one indicator of the quality of hospital services. Prescribing drugs based on guidelines will provide efficiency in the supply of drugs. The purpose of this study was to facilitate controlling drug supplies, safe use of drugs and control costs and quality of treatment. K-Means Clustering is a method of grouping data into clusters using the K-Means algorithm. The data used in this study was a specialist doctor's prescription in December 2019 which was sourced from the Pharmacy department of the Meranti Islands District Hospital. The results of this research with the K-Means Clustering method consisted of 3 (three) clusters, namely cluster 0 obeying Fornas as many as 2 polyclinics, cluster 1 being less obedient to Fornas as many as 2 polyclinics and cluster 2 not obeying Fornas as many as 3 polyclinics. This research can be used as a reference and evaluation to hospital management on the efficiency level of using specialist doctor's prescriptions in improving the quality of hospital services.

Akurasi Pemberian Insentif Menggunakan Algoritma K-Medoids Terhadap Tingkat Kedisiplinan Pegawai

Assessment of a discipline is a performance evaluation stage that is important for the continuity of company activities. Monitoring and assessment of an employee's discipline must be carried out continuously in order to improve the quality of human resources. This research was conducted to make the accuracy of providing incentives based on the level of employee discipline. The data processed in this study is a recapitulation of the attendance of AMIK and STIKOM Tunas Bangsa Pematangsiantar employees as many as 25 employees as a sample. For grouping the employee data using the K-Medoids Algorithm. K-Medoids groups a set of n objects into a number of k clusters using the partition clustering method. Furthermore, the employee data is processed using Rapid Miner software. Research using this method obtained results in the form of grouping employees into 3 groups that have good discipline levels of 12 employees, sufficient discipline levels of 8 employees, and less disciplinary levels of 5 employees. Based on the grouping results that have been produced, it can be a consideration for the leadership to determine the amount of incentives for employees.