Halil Akhyar
Program Studi Teknik Informatika, Universitas Mataram

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Studi Pemodelan dan Prediksi Aktivitas Antibakteri Biopo-limer Kitosan Menggunakan Response Surface Methodology (RSM) Halil Akhyar; Selvira Anandia Intan Maulidya; Muhammad Mukaddam Alaydrus; Maz Isa Ansyori; Mohammad Zaenuddin Hamidi; I Gede Pasek Suta Wijaya; Ramaditia Dwiyansaputra; Pahrul Irfan
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.713

Abstract

Infections occured in the human are mostly caused by uncontrolled growth of Staphylococcus aureus bacteria. A strategy to inhibit bacterial growth can use antibacterial agents such as chitosan. The mechanism of the effectiveness of chitosan as an antibacterial is quite complex, even the data on its antibacterial activity is quite fluctuating so that it is difficult to analyze accurately and efficiently. Therefore, the purpose of the study was to predict the inhibition zone of s.aureus bacteria through laboratory experiments combined with modeling using the Central Composite Design (CCD) approach. The research was carried out with two main stages, including chitosan isolation and calculation of bacterial inhibition zones. The production of chitosan leverages the microwave isolation and FTIR to examine for the degree of deacetylation and its functional group using. Furthermore, the antibacterial activity of chitosan biopolymer was tested using the diffusion method combined with modeling using the RSM CCD approach. The results showed that chitosam from oyster shell was obtained by DD of 83.29% and the emergence of typical chitosan groups, such as amine (NH2) and hydroxyl (OH). Chitosan can hamper the growth of s. aureus bacteria with an inhibition zone of up to 0.40 mm. The experimental data were combined with computational modeling obtained the values of the determination coefficient R2 = 0.6083. The modeling was assessed by p-value of < 0.0001 and F-value of 13.46. Statistically, the obtained model is relevant to the relationship between the number of bacterial colonies and the concentration of chitosan solution with the bacterial inhibition zone. Based on numerical analysis and modeling, the predicted values of the number of s. aureus bacterial colonies and chitosan concentrations were 550,000 CFU/ml and 42.5%. Therefore, Pearl shells can be isolated into chitosan, as well as chitosan has the potential to be a good antibacterial agent. The model has good prediction performance, but it rquires to increase the number of point spreads and it is necessary to validate the prediction results to obtain actual predictions.
Rancang Bangun Sistem Satu Data sebagai Strategi Peningkatan Mutu Pendidikan Tinggi di Universitas Mataram Mohammad Zaenuddin Hamidi; Ahmad Zafrullah Mardiansyah; I Wayan Sudiarta; Halil Akhyar
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.781

Abstract

The quality of higher education greatly depends on the accuracy and consistency of data used in decision making and accreditation processes. At the University of Mataram, various information systems have been developed separately, such as the Academic Information System (SIA), the New Student Admission System (PMB), the Research and Community Service Information System (SIMLITABMAS), and the Lecturer Performance Information System (BKD). However, the lack of integration among these systems has resulted in fragmented data, which is often unsynchronized and complicated the quality reporting process. This study aims to design and develop an integrated information system based on the One Data approach, which consolidates various primary data sources into a centralized platform within the University of Mataram. The advantages of the developed system lie in its direct integration with PDDIKTI, enabling automated data retrieval and submission through the national central system. This research adopts a Research and Development (R&D) approach with a Waterfall based software development method, consisting of the stages of requirement analysis, system design, implementation, testing, and evaluation. The results show that the developed system is able to integrate data from various existing systems and presenting it in a consistent format that is easily accessible by relevant units, with testing results achieving a 100% success rate. The system has been proven to support efficiency in reporting and monitoring processes for higher education quality in a more accurate manner. In conclusion, the One Data system contributes significantly to improve the quality of data governance and quality assurance processes in higher education and can serve as a foundation for the development of a more holistic and sustainable academic data ecosystem.