Abstrak Perkembangan teknologi semakin memudahkan kegiatan manusia dan hampir semua kalangan memiliki ponsel. Sehingga ponsel menjadi alat yang penting dalam berkomunikasi bagi kebanyakan orang terutama SMS. Banyaknya pesan yang masuk bisa tidak memungkinkan untuk mengklasifikasikan SMS spam secara manual. Untuk itu dilakukan pengklasifikasian SMS spam menggunakan teknik klasifikasi dalam data mining. Banyaknya algoritma yang tersedia memungkinkan kita untuk menggunakan salah satunya sebagai algoritma terbaik untuk klasifikasi SMS spam. Untuk itu dilakukan pengujian beberapa algoritma klasifikasi dengan dataset SMS yaitu algoritma Naïve Bayes, Decision Tree dan SVM. Dari hasil Analisa pengujian didapatkan bahwa algoritma Naïve Bayes memiliki kemampuan yang lebih baik dibandingkan algoritma SVM dan Decision Tree. Karena nilai recall algoritma Naïve Bayes sebesar 0.93 pada kelas SMS fraud dan 0.92 pada kelas SMS promo, sedangkan f1-score algoritma Naïve Bayes lebih tinggi dibanding algoritma lainnya dan nilai accuracy Naïve Bayes sebesar 0.94.
The purpose of this research is to further improve the design of the project management information. PT. XYZ is a company located in Kiarapayung, West Bandung, Indonesia. This company is engaged in services in the procurement of building construction or road construction. The company has not used an integrated information system in the management of project data, companies have difficulty in managing both transaction data and create reports. Information system aims to support operations, management, and decisionmaking [1]. Data that has not been integrated has resulted in difficulties in managing reports, and has made it difficult to process the salary of workers who are involved in ongoing project implementation which needs a management information system to help the project data so that data management and report generation can be easily created, because the data is already integrated with the database. It can be concluded from the problems described earlier that the company needed a data management information system project. Object-oriented approach method and prototype system development method were used for this study. The result is that project management system can improve the process of managing data more easily and quickly.
The high public interest in transactions using credit cards in the banking sector has the potential for higher credit card fraud. This study uses a credit card fraud dataset that consisting of 284,807 data obtained from Kaggle. The dataset in this study is class-imbalanced data with a comparison between the major class of 99.8% and the minor class of 0.2%. This class-imbalanced data problem will be solved by applying undersampling. In order to determine the performance of the classification algorithm that is most suitable for solving class-imbalanced data problems, a comparison of the Naïve Bayes, k-Nearest Neighbor (kNN) and Neural Network algorithms will be carried out. The t-test in this study was conducted to determine the significance of differences between algorithms. Algorithm performance evaluation uses accuracy and AUC (area under the curve) values. The test results in this study is Neural Network has better performance than other algorithms because it has the highest accuracy value of 93.59% and AUC value of 0.977. Based on the t-test results, the Neural Network with k-NN has a significant difference, in contrast to the Neural Network with Naïve Bayes there is no significant difference.
Proses bisnis adalah suatu kumpulan aktivitas atau pekerjaan terstruktur yang saling terkait dalam sebuah organisasi untuk menghasilkan produk atau layanan. Untuk kualitas produk dan layanan, tentu diperlukan proses bisnis yang efektif dan efisien. Selama ini proses bisnis masih banyak digambarkan dalam bentuk gambar mati berupa flowchart, karena belum mengenal notasi bernama BPMN (Business Process Model and Notation) yang bisa membuat gambar proses bisnis sekaligus memodelkannya dalam sebuah simulasi. Dengan menggunakan BPMN dapat disimulasikan proses bisnis yang paling efektif dan efisienuntuk menghasilkan produk atau layanan organisasi. Penelitian ini mengimplementasikan BPI (Business Process Improvement) dengan metode lean management, dan framework DMAIC (Define, Measure, Analysis, Improve, Control). DMAIC digunakan untuk perbaikan proses bisnis secara bertahap. Tools yang digunakan dalam membantu DMAIC pada penelitian ini diantaranya yaitu diagram SIPOC (Supplier, Input, Process, Output, Customer), identifikasi CTQ (Critical to Quality), mengukur kapabilitas proses menggunakan DPMO (Defects Per Million Opportunities), root cause analysis, kemudian disimulasikanmenggunakan toolBizagi Modeler. Dari penelitian pada proses bisnis STAI Attanwir diperoleh hasil bahwa ada dari 46 proses bisnis ada 15 yang mengalami waste. Dari 7 jenis waste, di STAI Attanwir ada 2 waste yang terjadi yaitu waste waiting dan waste movement. Dari 15 proses bisnis As-Is dan To-Be yang mengalami waste tersebut setelah dilakukan simulasi menggunakan BPI diperoleh hasil 12 proses bisnis mengalami perubahan yang signifikan dari segi waktu dan sumber daya. Namun ada 3 proses bisnis yang tingkat utilizationnya tetap tidak normal meskipun sudah dilakukan improvement.
Micro, small and medium enterprises (UMKM) in Indonesia is increasing every year. The increase in the number of UMKM has a significant impact on the Indonesian economy, so the government lowers the UMKM tax so that UMKM businesses develop rapidly. However, that does not make the other problems faced by the UMKM to be overcome. One problem that arises is the marketing and distribution of product results. The purpose of this research is to build a local shoe product distribution system based on a website to make it easier for resellers or shops to order shoes to the production. Processed data include retailer and store data, distributor data, product data, transaction data, and ordering data. Using the waterfall development model and using the Unified Modeling Language (UML) to visualize system modeling. This research generates reports of every activity carried out in the system including reports for factories, distributors and retailers.
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