No abstract

Employee career paths are one way for companies to improve employee performance in educating their students. The problem of manager in decision making uses the selection of methods and assessment processes subjectively so that the process is not in accordance with the goals of the career path. Therefore, an Analytical Hierarchy Process (AHP) method is needed to help make decisions. In this study, using the criteria of Planning, Teaching, Evaluating and Learning. Ranking results obtained that Learning criteria are very important criteria with calculation results of 0.602 when compared to the other three criteria. The Decision Support System (DSS) application provides the final results obtained from testing the calculation that the alternative Employee C is the best employee with a calculation of 0.227 compared to the other alternatives. The DSS application using the AHP method has a data accuracy rate of 86.67% and can be used as a support for manager decisions to make recommendations for increasing employee career paths.

ABSTRAK Absensi kehadiran pegawai merupakan faktor penting bagi sebuah instansi atau perusahaan untukmencapai tujuan, hal ini berkaitan pada kedisiplinan dan berdampak pada kinerja dari masing-masing pegawai.Oleh karena itu, perlu adanya pendataan khusus untuk mencatat absensi kehadiran dan ketidak hadiran agaraktifitas kerja dapat tercatat secara realtime dan baik. Banyak cara yang dapat dilakukan untuk mencapai sisteminformasi absensi yang baik, salah satunya menggunakan teknologi komputer dimana penerapannya denganaplikasi absensi berbasis website. Pada PT. Swadaya Absi Manunggal-Jereh consortium sistem yang digunakandalam proses absensi masih manual menggunakan buku absensi harian yang berdampak pada efisiensi danefektifitas pendataan, pencarian data sekaligus perhitungan rekap data yang membutuhkan waktu yang relatiflama. Disamping itu resiko kesalahan dan kehilangan data absensi semakin besar. Berdasarkan permasalahandiatas dibuatlah Sistem Informasi Absensi Karyawan Pada PT.Swadaya Abdi Manunggal-Jereh consortium.Metode penelitian merupakan metode yang digunakan dalam pengumpulan data yang meliputi: metodeobservasi, wawancara dan studi pustaka. Sedangkan pengembangan perangkat lunak menggunakan waterfallyang meliputi : analisa kebutuhan, desain, pengkodean, pengujian dan implementasi. Dengan dihasilkannyasistem absensi karyawan berbasis web dapat memberikan kemudahan dalam proses absensi, pencarian data danperhitungan rekap absensi, serta meminimalisir kehilangan dan kesalahan pencatatan data absensi pada PT.Swadaya Abdi Manunggal-Jereh consortium.

Social media is one of the most common sources used to communicate, such as Twitter. Every tweet on Twitter contains data such as text which when collected can be processed into information. Data processed from Twitter tweet will create a trend which can be used for information such as in education, economics, politics, etc. This then created the concept of text mining. Text mining techniques are needed to find an interesting pattern in search of trends based on Twitter text with topics related to Pilkada Pekanbaru 2017. This research is intended to cluster Twitter text data using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm. This research was conducted with several experiments using different Eps and MinPts parameters for 2,184 text data which has been through several stages, such as cleaning, duplication removal, pre-processing like stemming and stopwords. Based on the highest average of Silhouette Index, Eps 0.1 and MinPts 10 with SI = 0.413 were chosen as paramaters, thus forming 31 clusters. According to the frequency of word occurrences in the cluster, the highest are “kpu”, followed by “firdaus”, “kota”, “pasang”, and “ayat”. As can be seen that the candidate pairs most often appear on cluster results are Firdaus-Ayat, and based on the results of Pilkada 2017, Firdaus-Ayat was chosen as Mayor and Vice Mayor of Pekanbaru.

The Qur’an is an Islam holy book used as life guidance. Since its function as human life guidance, some strategies and ways are necessary in learning al Qur’an. Many strategies are usable in learning Qur’an, one of them is by learning munasabah science and the relationship between the topic and verses of Qur’an. The development of Data Mining that is expanded with text mining makes it easy to divide and find out the relationship of the topic of Qur’an especially in its translation. FP – Growth Algorithm is one of algorithm with many excellences in obtaining association pattern, in this case by determining topic relationship on Qur’an. The experiment in this research was carried out with 4 models where the best parameter is at minimum support 80% and its minimum confidence is 40%. Rule that is produced by algorithm is 159 with lift ratio 1.203. The best rule is implemented on android programming language as Qur’an learning media.