The development of the internet network and network equipment is currently very rapid, to meet the needs of internet usage, network devices are used as supporting tools in service access and network deployment. According to research conducted in a performance comparison analysis between the default firmware and the openwrt firmware [1], the performance of the network device is not only determined by the hardware specifications contained in the network device, but is also determined by the firmware in the network device. according to a literature review from various sources that the openwrt firmware can be used as a firmware solution to improve the performance of network devices that have limited service features and as firmware updates for network devices that do not get development support from vendors.The research will be conducted by analyzing the comparison of the performance of the Gl iNet Wireless Router network device which was created for the openwrt firmware and already using the openwrt firmware from the manufacturer, with the Tp Link Wireless Router network device, which is a network device that will implement the openwrt firmware. The design is carried out using the PPDIOO Life-Cycle Approach network development method, and a comparative analysis of network quality using QoS (Quality of Service) parameters.The final result of this research is how to implement and how the openwrt firmware runs on network devices that are not actually using the original firmware based on the results of network parameters jitter, delay, packet loss, throughput and signal strength testing in internet service access. Keywords : OpenWrt, Quality of Service, PPDIOO, Life-Cycle Approach.

When someone experiences obstacles in making decisions that must be done, they will usually ask for recommendations from those around them. Similarly, when a prospective student has difficulty determining the faculty when they want to continue their education to the higher education level, they will ask for recommendations from those closest to them who have not provided objective recommendations in accordance with their potential, even though a person's potential is very instrumental in making faculty selection decisions so that they can achieve learning success which can be seen from the achievement index. The same happened to prospective students of Amikom University Yogyakarta. It is necessary to build a system of recommendations for faculty selection. The potential of prospective students explored in this study includes school origin, personality expression, and the values of several subjects that have been obtained in high school. Cluster sampling was chosen to determine respondents where the Faculty as a cluster, respondents were selected from the student population who had taken at least 4 semesters with a grade point average of at least 3.00. The application of the Naïve Bayes algorithm in this study shows good accuracy results so that it can be used on research objects, but it would be more perfect if this system is later developed again into a recommendation for the selection of smaller educational units, namely study programs.

Sebagai salah satu sarana pelayanan kesehatan apotek harus selalu menjaga efisiensi biaya agar dapat bersaing. Persediaan merupakan elemen dari organisasi yang paling dinamis yang selalu bergerak mengikuti jumlah barang masuk yang harus dipesan dari pemasok dan barang keluar pada penjualan kepada pelanggan. Pengendalian persediaan yang tidak terkendali menyebabkan kekosongan barang yang berisiko terhadap kehilangan pelanggan namun jumlah barang persediaan yang terlalu banyak menimbulkan biaya simpan semakin yang besar pula. Diperlukan perencanaan persediaan yang baik yang dapat membantu menentukan waktu dan jumlah pemesanan suatu barang tertentu sehingga memperoleh biaya pemesanan yang optimum. Economic Order Quantity (EOQ) merupakan satu dari beberapa metode untuk optimalisasi biaya pemesanan yang dihitung berdasarkan biaya setiap kali dilakukan pemesanan, biaya penyimpanan dan kebutuhan barang pada kurun waktu tertentu. Kata Kunci: Apotek, Sistem Informasi, Persediaan, Economic Order Quantity

At the beginning of 2020, citizens all around the world were streaked by the Corona Virus (Covid-19) pandemic which caused terror far and near. Millions of people were infected and thousands more died ever since the World Health Organization or WHO has declared the Corona Virus (Covid-19) as a global pandemic. Following up on this, the Indonesian government also stated that the Corona Virus problem had become a non-natural national disaster. The President of the Republic of Indonesia and the Regional Government along with their staffs worked  hand in hand to take several tactical steps as an effort to prevent the spread of the Corona Virus (Covid-19) in the community. In this study, authors use one method to make predictions or forecasting, that is the Cheng Fuzzy Time Series method, to predict the number of Covid-19 cases in Indonesia so that the government can take tactical steps after knowing the predicted number of the case. The actual data used is the number of Covid-19 case from July 2020 up until October 2020. From the results of calculations that have been carried out using this method, the conclusion is that the performance is splendid, in the range of MAPE <10, whose error value is 5%. With 95% value of accuracy.

The graduation rate on time in college cannot be taken lightly. In many cases, it is found that there is an imbalance in the number of students who enter and who have completed their studies so that there is a high accumulation of the number of students in each batch. It is necessary to know the factors that cause students not to graduate on time. Data classification techniques can be used to predict the timeliness of student graduation. The algorithm used is the Naïve Bayes algorithm with data from 122 students from the Informatics Engineering and Information Systems study program at the Faculty of Computer Science, AMIKOM University, Yogyakarta. Based on the results that have been carried out, it can be concluded that the Naïve Bayes algorithm is applied accurately to predict the timeliness of students' graduation. The results of testing the level of prediction accuracy resulting from the trial reached 90.16%.