Penelitian ini bertujuan untuk merancang sistem monitoring deteksi dini kebakaran pada ruang server. Kebakaran merupakan ancaman serius yang dapat mengakibatkan kerusakan fatal pada peralatan di ruang server dan potensi kehilangan data pada storage. Untuk menunjang penelitian yang memanfaatkan otomatisasi dan hal yang bersifat real time, maka diperlukan komunikasi antara sensor-sensor dan software yang juga disebut teknologi Internet of Things (IoT). Dalam penelitian ini, sensor-sensor yang dimaksud yaitu Flame Sensor yang berguna sebagai pendeteksi radiasi dari nyala api, Sensor MQ 2 sebagai  pendeteksi asap dan Sensor DHT 11 untuk mendeteksi perubahan suhu yang  signifikan. Untuk mempermudah dalam pemantauan, juga di lengkapi dengan laman web server yang dapat diakses dengan mudah serta menggunakan beberapa output, antara lain buzzer sebagai sirine bahaya, pilot lamp untuk memberikan sinyal visual adanya suhu yang tidak normal serta outpur exhaust fan untuk membantu sirkulasi udara di dalam ruang server. Implementasi dalam rancang bangun sistem monitoring ini diharapkan dapat membantu memastikan performa server dalamkondisi yang selalu optimal dan mengurangi resiko kebakaran yang lebih fatal serta dapat mengurangi beban kerja staf pengelola di Dinas Kependudukan dan Pencatatan Sipil Kabupaten Semarang.

Guava Komputer adalah toko yang menyediakan berbagai produk komputer dan laptop, termasuk laptop, desktop, aksesori, perangkat keras, dan perangkat lunak dari merek-merek terkemuka. Namun, dalam proses bisnisnya, toko ini menghadapi masalah dimana pelanggan sering kesulitan memilih laptop yang sesuai dengan kebutuhan mereka, akibat banyaknya tawaran yang diberikan oleh pegawai toko. Selain itu, pegawai juga merasa kesulitan saat melayani banyak pengunjung. Untuk mengatasi masalah ini, diterapkan sistem pendukung keputusan berbasis web menggunakan metode Analytical Hierarchy Process (AHP), yang dikembangkan dengan bahasa pemrograman PHP dan basis data MySQL. Metode AHP membantu dalam menentukan urutan alternatif dan memilih alternatif terbaik berdasarkan kriteria yang ditetapkan. Hasil penelitian ini menunjukkan bahwa sistem ini efektif membantu pelanggan menemukan laptop yang sesuai dengan kebutuhan mereka, dengan nilai tertinggi yang disarankan. Sistem ini diuji dengan skor validitas 4,63 (sangat baik) dan efektivitas 90% (sangat efektif), serta telah berhasil diuji oleh penguji internal dan eksternal, menunjukkan bahwa sistem ini bekerja sesuai harapan dan memberikan informasi yang valid dan efektif.

Intrusion Detection Systems (IDS) are an efficient defense against network attacks as well as host attacks as they allow network/host administrators to detect any policy violations. However, traditional IDS are vulnerable and unreliable for new malicious and genuine attacks. In other case, it is also inefficient to analyze large amount of data such as possibility logs. Furthermore, for typical OS, there are a lot of false positives and false negatives. There are some techniques to increase the quality and result of IDS where data mining is one of technique that is important to mining the information that useful from a large amount of data which noisy and random. The purpose of this study is to combine three technique of data mining to reduce overhead and to improve efficiency in intrusion detection system (IDS). The combination of clustering (Hierarchical) and two categories (C5, CHAID) is proposed in this study. The designed IDS is evaluated against the KDD'99 standard Data set (Knowledge Discovery and Data Mining), which is used to evaluate the efficacy of intrusion detection systems. The suggested system can detect intrusions and categorize them into four categories: probe, DoS, U2R (User to Root), and R2L (Remote to Local). The good performance of IDS in case of accuracy and efficiency was the result of this study.

Intrusion Detection Systems (IDS) are an efficient defense against network attacks as well as host attacks as they allow network/host administrators to detect any policy violations. However, traditional IDS are vulnerable and unreliable for new malicious and genuine attacks. In other case, it is also inefficient to analyze large amount of data such as possibility logs. Furthermore, for typical OS, there are a lot of false positives and false negatives. There are some techniques to increase the quality and result of IDS where data mining is one of technique that is important to mining the information that useful from a large amount of data which noisy and random. The purpose of this study is to combine three technique of data mining to reduce overhead and to improve efficiency in intrusion detection system (IDS). The combination of clustering (Hierarchical) and two categories (C5, CHAID) is proposed in this study. The designed IDS is evaluated against the KDD'99 standard Data set (Knowledge Discovery and Data Mining), which is used to evaluate the efficacy of intrusion detection systems. The suggested system can detect intrusions and categorize them into four categories: probe, DoS, U2R (User to Root), and R2L (Remote to Local). The good performance of IDS in case of accuracy and efficiency was the result of this study.

Abstract The function in the development of information technology in human activities today is indeed developing very rapidly. Information empowerment technology has become a major facility in business activities. In information technology in the part of business contributes greatly to fundamental changes to structural, operational and organizational management. Human resources has provide a large influence in the management of information systems in an information technology organization that develops significantly, it also results in important changes in accounting and financial governance. The function of Information Technology in the development of financial bookkeeping in each part varies. Rapid of development of information systems is in line with the rate of development of financial accounting. In terms of internal control, data processing and improving the quality and quality of information, it is very influential in the development of information technology. Computer-based Accounting Information Systems in generating financial information also affect the audit process. The development of information systems that ultimately provide new opportunities as the auditor

The human need for technology and the availability of adequate infrastructure is evidence that technology is now a part of basic human needs. The increasing number of journals and scientific papers, it must be more selective in selecting and sorting even though there are already many online service providers and journal portals. Research on search engines and plagiarism and recommendation systems has been carried out with various methods deemed appropriate to improve the performance of the system itself, this paper has the purpose of calculating the similarity between one article with another article by implementing n-gram and tanimoto cosine. The number of articles tested was forty-three titles and abstracts, tested fifty times with randomly selected keywords, by breaking down each title and abstract sentence into n characters (n = 2 to 8) including spaces and punctuation, then counted similarity with the query or keyword used for system testing. The test was conducted using several threshold variations from n = 2 to 8. After observing fifty times the threshold test of 0.15 has the highest accuracy at n = 4 at 0.92, the highest precision at n = 3 at 0.42 and the highest recall at the test n = 2 = 0.44 .