http://repository.kalbis.ac.id/handle/123456789/22 Sun, 15 Mar 2026 06:58:37 GMT 2026-03-15T06:58:37Z http://repository.kalbis.ac.id/handle/123456789/1766 Title: Analisis Celah Keamanan Pada Website PDDIKTI Menggunakan Metode Penetration Testing Dan Framework ISSAF Authors: Darno, Nabila Daniasti Abstract: Keamanan website merupakan aspek krusial dalam menjaga integritas, kerahasiaan, dan ketersediaan data, terutama pada sistem informasi yang menyimpan data sensitif seperti Pangkalan Data Pendidikan Tinggi (PDDikti). Sebagai platform resmi penyedia data pendidikan tinggi di Indonesia, PDDikti rentan terhadap serangan siber seperti SQL Injection, Cross-Site Scripting (XSS), dan Denial of Service (DoS). Penelitian ini bertujuan menganalisis kerentanan keamanan pada website PDDikti menggunakan metode Penetration Testing yang dipadukan dengan kerangka kerja Information System Security Assessment Framework (ISSAF). Penelitian dilakukan melalui tiga fase utama: Perencanaan, Penilaian, dan Pelaporan. Hasilnya menunjukkan adanya celah kritis pada autentikasi pengguna dan enkripsi data. Temuan ini kemudian dianalisis untuk memberikan rekomendasi perbaikan. Penelitian ini diharapkan dapat meningkatkan keamanan sistem informasi PDDikti serta menjadi acuan bagi pengelola sistem serupa dalam melakukan evaluasi keamanan secara berkala. Sat, 08 Mar 2025 00:00:00 GMT http://repository.kalbis.ac.id/handle/123456789/1766 2025-03-08T00:00:00Z http://repository.kalbis.ac.id/handle/123456789/1724 Title: Perancangan Sistem Dashboard Proses Validasi Pengiriman Unit Mobil Berbasis Website Authors: Ebeneizer, Daniel Abstract: Di era digital yang terus berkembang, kebutuhan akan sistem yang cepat, tepat, dan mudah diakses menjadi sangat penting, khususnya dalam dunia bisnis dan industri otomotif. Seiring bertambahnya skala perusahaan, volume data yang dikelola juga meningkat, sehingga dibutuhkan sistem yang mampu membantu efisiensi kerja, salah satunya melalui penerapan dashboard. Dashboard memungkinkan penyajian data secara visual dan interaktif dalam bentuk grafik, tabel, dan indikator yang dapat disesuaikan dengan kebutuhan masing-masing divisi. Penggunaan dashboard tidak hanya mempermudah proses kerja, tetapi juga menghemat waktu dan biaya, terutama dalam proses yang membutuhkan koordinasi antar divisi, seperti approval pengiriman unit mobil. Pengalaman peneliti selama mengikuti program magang Kemendikbudristek dan magang mandiri menunjukkan bahwa hampir seluruh perusahaan sangat membutuhkan sistem dashboard untuk mendukung operasional mereka. Penelitian terdahulu juga membuktikan bahwa dashboard yang terintegrasi dengan baik dapat meningkatkan performa visual sekaligus efektivitas sistem database yang digunakan. In the rapidly growing digital era, efficiency and accessibility of information have become crucial aspects in various sectors, including business, government, start-ups, education, and automotive. Along with the increasing scale of the company, the amount of data managed is also getting bigger, so a system that can simplify work and increase the productivity of each division is needed. Dashboard comes as an effective and adaptive data visualization solution to the needs of each user, both in the form of graphs, tables, and other indicators. By integrating dashboards in the company's workflow, previously manual processes such as cross-divisional decision making or approval can be done digitally, faster, and more efficiently, saving time and budget. This is especially relevant in the automotive industry, which demands high coordination in the process of shipping units from factories to end consumers. Based on the researcher's experience in the Kemendikbudristek internship program and independent internship, it is found that the dashboard system has a vital role in the smooth operation of the company. Previous research also supports that implementing a good dashboard not only improves visual performance, but also the efficiency of the database system used. Wed, 02 Jul 2025 00:00:00 GMT http://repository.kalbis.ac.id/handle/123456789/1724 2025-07-02T00:00:00Z 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