http://repository.kalbis.ac.id/handle/123456789/1429 Skripsi Sistem Informasi Tahun 2024 Fri, 01 May 2026 02:24:16 GMT 2026-05-01T02:24:16Z http://repository.kalbis.ac.id/handle/123456789/1676 Title: Perancangan Sistem Informasi Pembukuan Kas Berbasis Web Studi Kasus Yayasan Pesona Jakarta Authors: Abdullah, Faizal; Ziveria, Mira Abstract: With technological developments continuing to develop, business actors must continue to follow developments that occur in the world of entrepreneurship. This study designs online cash bookkeeping for the Pesona Jakarta Foundation. The foundation's cash bookkeeping is still done manually, which means it takes a long time to prepare reports and the results are not optimal. The aim of this research is to create an easy and accurate way to record cash incoming and outgoing transactions. The Waterfall research method and Laravel framework were used. Black Box Testing is the testing method used. Data collection uses observation, interviews and literature research. The results of this research show that the system designed based on business needs was successfully built and has features that help business processes. Fri, 16 Feb 2024 00:00:00 GMT http://repository.kalbis.ac.id/handle/123456789/1676 2024-02-16T00:00:00Z http://repository.kalbis.ac.id/handle/123456789/1553 Title: Perbandingan Algoritma NaÏve Bayes, SVM dan Random Forest pada Analisis Sentimen Pengguna X terhadap IKN Authors: Cahyani, Putri Abstract: Sentiment analysis was explored to understand social media users' opinions towards the Indonesian Capital City (IKN) through the X platform with machine learning and lexicon-based algorithms. This research uses three algorithms: Naïve Bayes, Support Vector Machine (SVM), and Random Forest. The aim of this research is to test and compare the performance of the three algorithms to determine the best in classifying sentiment data from the X platform. The data consists of 10,000 tweets collected using the crawling method with the Python Harvest Library and Node.js, using keywords related to IKN. Based on the algorithm performance test, it was concluded that SVM had the highest performance compared to Naïve Bayes and Random Forest, producing an accuracy of 87%, precision 87%, recall 87%, and f-1 score 87%. This research uses the CRISP-DM Data Mining framework to ensure a structured and systematic approach to the analysis process. Mon, 15 Jul 2024 00:00:00 GMT http://repository.kalbis.ac.id/handle/123456789/1553 2024-07-15T00:00:00Z http://repository.kalbis.ac.id/handle/123456789/1514 Title: Penerapan Algoritma Regresi Linear Sederhana untuk Prediksi Penjualan Produk pada PT. Bintang Graha Makmur Authors: Rifky, Muhammad Abstract: PT Bintang Graha Makmur in Jakarta is a company that has been operating since 2010 in the field of food and beverages, especially alcoholic beverages. Until now, PT Bintang Graha Makmur has distributed alcoholic beverage products to various restaurants, hotels and bars. The problem that often occurs at this time is the difficulty in determining the right stock of goods, resulting in delays in shipping goods. This prediction is done to estimate future sales to make decisions in stocking goods so that they are able to adjust to the amount of demand for goods. The sales prediction method used is Simple Linear Regression and then the prototyping system development method which is applied in the form of a website. The results of this study are to produce an average value of MAPE from each prediction result of each product and help to process records on sales of goods, stock items and customers. Thu, 30 May 2024 00:00:00 GMT http://repository.kalbis.ac.id/handle/123456789/1514 2024-05-30T00:00:00Z