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The impact of the Covid-19 pandemic requires that every employee in a university maintains his health. One of the most important body parts to maintain during this pandemic is body temperature. The purpose of this study was to develop a non-contact digital thermometer to measure the body temperature of FKIP employees, Mataram University. The digital thermometer development method starts from literature studies, tool specifications, hardware design, software design and thermometer testing to measure employee body temperature in the morning and afternoon. The results of the digital thermometer test showed that the employee’s body temperature in the morning with an average of 33.36 °C and in the afternoon with an average of 33.96 °C. So it can be concluded that the Mataram University FKIP employees who came to work did not experience Covid-19 symptoms.

Length expansion is an increase in the length of an object due to receiving heat. If a solid object is heated then the object will expand in all directions, in other words the length increases the length of an object because it receives heat. A tool for comparing the length expansion of various metals is the Musschenbrock. To measure the temperature of an object can use a sensor. The sensor used in this research is the LM 35 based on Arduino Uno. The development method for this Length expansion tool temperature detector starts from tool design, hardware design, software design, tool calibration and tool testing. From the results of research using an Arduino Uno-based temperature detector, it can be said that this research was successful because the values obtained were almost the same as the existing theory. So, this detector is suitable for use in laboratories or schools as a learning medium to determine the length expansion of metals.

Universitas Maarif Hasyim Latif (UMAHA) is a College that organizes scholarship programs for its students. However, in the implementation of the program, some problems occur, namely the University has difficulty in making decisions, and a large number of student data applying for scholarships causes a long time to select the process. So, we need a tool/system to help solve the problem. The purpose of this study is to apply the ID3 decision tree algorithm in a decision support system that can help facilitate the decision making of scholarships by the UMAHA. Referring to Pressman, this study uses the Waterfall Method. Waterfall method is a systematic and sequential software approach starting from analysis, design, coding, and testing. The test results by applying the ID3 decision tree algorithm indicate that the decision support system built can help the effectiveness and efficiency of the scholarship selection decision making the process by UMAHA, and the decision support system built has a high level of decision-making accuracy. For the development of further research, decision making can be based on more criteria such as student activity. Then in addition to academic achievement in this case using the GPA of the previous semester using non-academic achievements such as achievements in the fields of sports, arts, music.

The clay deposit in the coal mining area of Tanjung Enim has a deposit about five times its coal deposit. This clay has not been utilized except as glue on brick briquettes which are relatively small quantities. As a rubber filler, clay can be used, but the silica content is preferred in the clay. Therefore the composition of silica in clay must be known. This study aims to determine the content of silica in the clay contained in the coal mining area of Tanjung Enim. The research begins with clay drying, followed by the fineness of clay grain size to a size of about 10-50 microns. Furthermore, the analysis of the compounds there in is carried out using XRF. The results show that the silica content in the clay is about 53.74 - 75.29% and the highest content is in the Lower D layer 75.29% and followed by the Int B2-C layer 56.87% and Lower C 56.65 %. In general, the compounds in this clay are dominated by SiO2, Al2O3, Fe2O3, MgO, TiO2, and K2O.

Microcrystalline cellulose(MCC) was isolated from corncobs waste. It was activated by NaOH solution with varied concentration in range from 4%, 6%, 8%, 10%, 12%, 14% and 17%. Characterization of physicochemical properties of microcrystalline cellulose (MCC) molecular weight was conducted by using Mass Spectrofotometer (MS).Preconditioning of MS used 20 μl injection volume, 10 μl concentration, acethonitrile: ultra water (50:50) as eluent. The result showed that NaOHconcentration affect to the type of oligosaccharides fragmentationwith an increased abundance. MS spectra for NaOH 4% showed four major peaks at 834 m/z, 623 m/z, 425 m/z, 383 m/z that indicated 2-5 glucose polymers respectively, with an increased abundance withadditional Na+ and K+ ions. NaOH8%, 12%, 14%, 17% indicated the type of oligosaccharide fragmentation with equal three major peaks at 827 m/z, 623 m/z, 425 m/z. The fragmentatition type of NaOH 10% and avicel standard pH 102, indicated 2-5 glucose polymers respectively,with an increased abundance with additional Na+ and K+ ions, there are peak at 827 m/z and 425 m/z, and there is no peak at 623 m/z because there are no Na* and K+ ions.

The Ministry of Research, Technology and Higher Education of Indonesia has introduced several national and international indexers of scientific works. This policy becomes a guideline for lecturers and researchers in choosing the reputable publications. This study aimed to describe the understanding level of Indonesian lecturers related to indexing databases, i.e. SINTA, DOAJ, Scopus, Web of Science, and Google Scholar. This research used descriptive design and survey method. The populations in this study were Indonesian lecturers and researchers. The primary data were obtained from a questionnaire filled by 316 lecturers and researchers from 33 Provinces in Indonesia recruited with convenience sampling technique on October-November 2017. The data analysis was performed using frequency distribution tables, cross tabulation and descriptive analysis. The results of this study showed that the understanding of Indonesian lecturers and researchers regarding publications in indexing databases SINTA, DOAJ, Scopus, Web of Science and Google Scholar is that, on average, 66,5% have known about SINTA, DOAJ, Scopus, Web of Science and Google Scholar. However, based on empirical frequency 76% of them have never published with journals or proceedings indexed in Scopus.