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To support green energy and reduce the effects of greenhouse gases, it is necessary to conceptualize and explore the use of renewable energy. In this research, the use of new renewable energy, especially photovoltaics (PV), will be applied to educational buildings, especially at ITS PKU Muhammadiyah Surakarta. This system is intended to reduce the use of conventional electrical energy. This system will be installed on the roofs of campus buildings with installation plans to meet the power requirement of 4.8 kW. This photovoltaic (PV) system will be modeled to determine the number of PV panels needed. Based on the simulation results, the number of panels required is 36 panels (2 series, 18 parallel) to produce 4.85kWh of power. Modeling and analysis of this system was carried out using RETScreen and MATLAB SIMULINK software.

Kruskal's algorithm in searching for minimum spanning trees can be applied to pipelines installed at the location of PDAM Tirtanadi Tuasan where problem identification starts with the water discharge reaching the consumer is small but the discharge flowing from the reservoir is sufficient, so this research is used as a solution to this problem and also as an optimization of the clean water distribution network in the Tirtanadi Regional Drinking Water Company (PDAM) of the Tuasan Branch with the intention of cutting the direction of the pipe flow to overcome this problem. The data obtained from PDAM Tirtanadi Tuasan Branch is in the form of a floor plan and formed into a weighted graph. After the data is obtained, then it is calculated manually that the length of the installed water pipe is 32,645 m with 86 vertices and 100 edges, then the pipe length is represented as a set of paths and the pipe connection ends are represented as nodes. The pipe length obtained using Kruskal's algorithm and inspection of iterations using the QM for windows software is 22,095 m, with 86 vertices and 85 edges. So, using the Kruskal Algorithm and the help of the QM for windows software, the difference in pipe length obtained is 10,610 m.

Process scheduling algorithms play an important role in determining the performance of operating systems, particularly in managing CPU utilization and process execution efficiency. Ineffective scheduling mechanisms can lead to increased waiting time and reduced system performance. This study aims to model and simulate several process scheduling algorithms using MATLAB in order to evaluate their performance characteristics. The research method involves developing simulation models for selected scheduling algorithms, including First Come First Serve, Shortest Job First, and Round Robin. Performance evaluation is conducted based on key parameters such as average waiting time, turnaround time, and processor throughput. The simulation results demonstrate that each scheduling algorithm exhibits different performance behaviors depending on the workload characteristics. Shortest Job First produces the lowest average waiting time, while Round Robin offers better response time fairness for time-sharing systems. The findings indicate that simulation-based analysis using MATLAB provides an effective approach to understanding the behavior and performance trade-offs of process scheduling algorithms. This research contributes as a reference for selecting appropriate scheduling algorithms in operating system design and as a learning model for process scheduling analysis.

This study aims to compile a Lecture Schedule at the Mathematics Education Study Program, Faculty of Mathematics Natural and Earth Sciences Manado State University using the Welch-Powell Algorithm. The scheduling of lectures at the Mathematics Education Study Program, Faculty of Mathematics and Natural Sciences, Manado State University often collides because several lecturers have different numbers of courses and credit rights. This it can be seen that the method of preparing lectures used is still not effective and efficient. Preparation of a course schedule is an action taken so that time can be managed as effectively and efficiently as possible. The preparation of this lecture schedule will use a simple graph with input data, namely the number of lecturers, number of courses, credits for each course, days used in the week, time slots and number of classes used. After getting the input data, point coloring is carried out in coloring on the graph using the Welch-Powell Algorithm assisted by MATLAB software to get an effective and efficient class schedule. Lecture Schedule Arrangement in the Mathematics Education Study Program, Department of Mathematics, Faculty of Mathematics, Natural and Earth Sciences, Manado State University using the Welch-Powell Algorithm produces a schedule that does not collide, so that the Welch-Powell Algorithm can help prepare an effective and efficient class schedule .

Kondisi pandemi COVID-19 tahun selama kurang lebih 2 tahun menjadi pembelajaran bagi Indonesia khususnya di bidang kesehatan. Problematika di bidang kesehatan semakin terlihat jelas di era pandemi COVID-19 ini. Suhu tubuh normal berkisar antar 36,5⁰C - 37,5⁰C dan bila melebihi 38,5⁰C maka ada indikasi terinfeksi covid-19 yang kemudian akan diarahkan untuk isolasi baik mandiri atau di tempat yang telah disediakan. Tujuan adanya ruang isolasi adalah untuk mengendalikan penyebaran penyakit menular yang bisa mewabah. Ruang isolasi adalah ruangan khusus, orang-orang yang bisa masuk ke ruangan ini juga sangat terbatas. Mengingat di ruang isolasi tidak bisa sembarangan keluar masuk, untuk itu dikembangkanlah sistem monitoring yang mampu memantau beberapa parameter yang dibutuhkan agar ruangan tersebut memenuhi standar operasional prosedur. Salah satunya adalah pengelolaan tata udara yang harus dijaga yaitu suhu ruangan dan kelembapan ruangan. Udara dalam ruangan dan kontaminan dalam ruangan minimal 6x pertukaran udara perjam dengan suhu ruangan 24 - 26 C dan kelembaban relatif 40 - 60%. Berdasarkan permasalahan diatas penulis ingin menerapkan Fuzzy logic metode Mamdani pada sistem monitoring suhu dan kelembapan ruangan pasien isolasi Covid-19 berabsis IOT ( Internet of Things ). Hal ini tentunya sangat membantu berbagai pihak mulai perorangan, hingga lembaga kesehatan utamanya rumah sakit umum. Dari pengujian metode Fuzzy Logic tersebut diambil 10 data yang dibandingkan nilainya dengan Matlab, dapat dihasilkan rata-rata error output PWM sebesar 0.1%. Bedasarkan pengujian metode black box yang dilakukan dapat diketahui tampilan sistem sesuai dengan tampilan yang diharapkan, dengan persentase kesesuaian 100%. Untuk pengujian fungsional dapat diketahui tampilan website dapat berfungsi dengan baik pada browser Opera, Chrome, dan juga Microsoft Edge.

Energi matahari dapat dimanfaatkan sebagai sumber energi alternatif yang potensial karena energinya yang sangat besar serta ramah lingkungan dan dapat diperbaharui. Salah satu teknologi yang dapat mengubah energi matahari menjadi energi listrik adalah panel surya yang berdasarkan pada prinsip photovoltaik. Pada tulisan ini akan dijelaskan tentang pemodelan dan simulasi untuk mengetahui karakteristik modul sel surya tunggal dan paralel dengan parameter berupa tegangan, arus dan daya maksimum yang digunakan untuk menganalisa kinerja dari panel surya. Hasilnya, pada iradiasi matahari tetap daya maksimum pada modul tunggal bernilai 156,49 watt dengan efisiensi 15,649 persen , sedangkan untuk modul paralel menghasilkan daya maksimum sebesar 313,206 watt dengan efisiensi sebesar 16,36 persen.

The purpose of this research to revisits methods that are more effective in nonlinear Optimization with single variable polynomial functions at high degrees. Models with linear objective functions and constraint functions are Polynomials of third, fourth and fifth degree reconstructed into subproblems that are easier to solve, namely quadratic programs, using bilinear Auxiliary Functions and solved by MATLAB simulations. The method used is the development of Tawarmalani & Sahinidis' research regarding relaxation with Auxiliary Functions. Examples of nonlinear Optimization with polynomial functions are also given to illustrate the implementation of this algorithm. The results of the research show that the application of the development reconstruction method produces a global solution that is no better than the solution to the original problem so that it is not an effective alternative method to use.

This study aims to analyze the optimality of a quadratic program model using the penalty function. The analysis is carried out in each case that has been made so that in each case optimal results are obtained. There are many methods that can be used to solve the quadratic program problem but in terms of the number of iterations, this research uses the penalty function and then implements it into the Matlab programming language. The results obtained in this study indicate that by using the penalty function as a parameter, the optimal value of a function can be obtained. The results of the analysis will also be more optimal by using the lagrange method depending on the parameter values obtained.

The method fuzzy is one part of the fuzzy inference system that is useful for drawing conclusions or the best decision in uncertain problems. Currently, about 200 countries in the world are experiencing the Covid-19 pandemic. Various policies were carried out to overcome this. In addition to the health protocols that are always implemented, the community must also know the conditions of the area where they live so that they can anticipate any activities carried out. The method is used fuzzy to determine the risk zone for the spread of Covid-19 in North Sumatra Province based on 3 variables, namely positive cases, suspected cases, and dead cases. The data used in this study is weekly Covid-19 data from March 2021 to July 2021 for 4 selected areas, namely Medan City, Pematang Siantar City, Simalungun Regency, and Central Tapanuli Regency. All variables are represented using triangular curves and their membership functions are determined. Then the implication function of the min is used to determine the rules used. From the results of the implication function, the composition between all the rules obtained is carried out by taking the maximum rule then that value is used to modify the fuzzy area so that a new membership function is obtained. The method is used centroid to obtain a crisp or the final result is the value of the risk zone. This research also utilizes the Matlab to calculate the results. The results from the use of the Mamdani method will be compared with the real risk zone data so as to produce a 75% average percentage similarity for the data for 4 regions in North Sumatra so it can be concluded that the model made is good enough to determine the risk zone for the spread of Covid-19 in North Sumatra Province.

The Erlang distribution is a special case of the Gamma distribution with the k shape parameter and the λ rate parameter. In this study, the parameter estimation of the Erlang distribution was carried out using the Maximum Likelihood method. In maximizing the function, an implicit and non-linear form is obtained, then it is solved using the Newton Raphson algorithm. Apart from Newton Raphon, the estimation of parameters was also carried out using the Fisher Scoring algorithm. The Fisher Scoring algorithm is similar to the Newton Raphson algorithm, the difference is that Fisher Scoring uses an matrix information. The result of parameter estimation in Erlang distribution using Newton Raphson algorithm which is applied to outgoing telephone call data that generated by Matlab R2010a software cannot be done simultaneously. Therefore, the parameter assessment is carried out on the k parameter first, then followed by the λ parameter estimation and the parameter and  = 0.6886812 are obtained. Meanwhile, the parameter estimation using the Fisher Scoring algorithm produces an equation that is not different from the Newton Raphson algorithm