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All Journal Pelita Perkebunan Sistemasi: Jurnal Sistem Informasi Journal of Blockchain, Nfts and Metaverse Technology
Ucu Sumirat
Pusat Penelitian Kopi dan Kakao Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science

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Adaptation of introduced Robusta coffee clones in some agroclimate types in East Java. Sugianto, Pingkan; Sudarsono, Sudarsono; Sukma, Dewi; Sumirat, Ucu
Pelita Perkebunan (a Coffee and Cocoa Research Journal) Vol. 38 No. 2 (2022)
Publisher : Indonesian Coffee and Cocoa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iccri.jur.pelitaperkebunan.v38i2.323

Abstract

Indonesia is the fourth largest coffee producer in the world, even though it is not the original plant. Efforts to increase coffee genetic diversity in Indonesia through the results of the introduction are also carried out to improve the quality and quantity of coffee in the international market. The aim is to obtain robusta coffee clones that are able to adapt in several agroclimates in Indonesia and have stable yield potential, so that they can be cultivated extensively. The analytical method is AMMI biplot with six clones are FRT04, FRT06, FRT07, FRT09, FRT23, FRT65, and six locations are Bangelan, Kalibendo, Kaliselogiri, Gumitir, Malangsari, Silosanen.Then the agroclimate is suitable for widespread cultivation. The results of the study based on observations made on the production of coffee plants, which are climate types, which are somewhat wet and are getting good production results in the locations of Bangelan, Kaliselogiri and Silosanen. FRT07and FRT09 clones is the best clone of production and able to adapt, has interaction between locations with clones tested annually.
Growth and Plant Architecture of Several Introduced Coffea canephora Clones Under Different Shade Levels Yuliasmara, Fitria; Sumirat, Ucu; Wicaksono, Karuniawan Puji; Widaryanto, Eko
Pelita Perkebunan (a Coffee and Cocoa Research Journal) Vol. 38 No. 3 (2022)
Publisher : Indonesian Coffee and Cocoa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iccri.jur.pelitaperkebunan.v38i3.517

Abstract

Introducing superior plants is one of the efforts to increase coffee produc- tivity in Indonesia. Three clones from France de Torino (FRT), FRT 07, FRT 09, and FRT 65, have been introduced to Indonesia. However, their cultivation is not widely distributed yet. Analysis of the responses of FRT clones against differences in climate and cultivation is needed to determine the right cultivation system to produce maximum growth and productivity. This study examines the vegetative growth of FRT clones introduced at some levels of shade. The study employed a split-plot design with 36 experimental units. The primary factor was the levels of shade consisting: without shade, 25% of shade, 50% of shade, and 100% of shade. The three introduced FRT clones (FRT 07, FRT 09, and FRT 65) were used as the subplot. Observations were done on several growth variables. The results showed that shade treatment affected all growth parameters and plant architecture. Clones significiantly affected plant height, orthotropic internode length, number of leaves, and average leaf area. Increased levels of shade caused an increase in internode length, branch angle, and crown diameter but decrease in number of internodes and leaves. A low level of shade (25%) produced an optimal value on parameters related to the productivity of FRT coffee plants, such as the number of plagiotropic internodes and the number of leaves. Parameters related to vegetative growth, such as plant height, stem diameter, and internode length, showed optimal values in a moderate level of shade (50%). Treatment without shade and a heavy shade resulted in impaired growth of FRT coffee. There was no interaction between levels of shade and clone treatment on most of the variables related to plant morphology, which indicated that the three introduced FRT clones gave relatively similar response to shade; thus, the three clones can be managed with the same shade management.
Analysis of Distributed File System Replication Using the NDLC Method with Hyper-V Virtual Simulation Machine Sumirat, Ucu; Setiawan, Antonius; Wilyanti, Sinka; Al-Hakim, Rosyid
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 1 No. 1 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v1i1.59

Abstract

The need to access file sharing easily on an organization's computer network was increased. Users didn't have to worry about the number of file server addresses that can be accessed and are made with only one access address to use file sharing. The availability of data on the network to file storage availability in an organization was also essential. Data would be permanently lost, following a reason including hardware failure, or even accidentally deleted. It was important to ensure that there was a copy of the data. Achieving good data availability requires a system strategy built in the organization's data center. This research used Distributed File System Replication (DFSR) based on active directory domain services with Windows Server. The research method used NDLC (Network Diagram Life Cycle) method. This research was conducted through analysis with the Hyper-V virtual simulation machine. The results of the research with this simulation are that the Distributed File System (DFS) makes it easy for users to access file shares on several file server nodes using only one URL address. DFSR makes it easy for users to clone files automatically on multiple nodes file servers at other locations. DFSR, with its Share and Publish features, provide good data availability. If one of the file server nodes experiences an interruption, the file server nodes at another location would be taken over to provide the data. This system makes it easy for administrators to manage file servers
Using Regression Model Analysis for Forecasting the Likelihood of Particular Symptoms of COVID-19 Pangestu, Agung; Sumirat, Ucu; Al-Hakim, Rosyid Ridlo; Yusro, Muhammad; Ekawati, Risma; Alrahman, Mahmmoud H. A.; Arif, Machnun; Muchsin, Achmad; Wahyudiana, Nadhilla H
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3463

Abstract

A certainty factor (CF) rule-based technique is frequently used by traditional expert systems (TES) in the medical industry to compute several symptoms and identify the inference solutions. The primary concern for this TES was predicting the likelihood of a particular ailment in the circumstances of new patients. Based on symptoms connected to clinical indicators in patients' diagnosis, CF is estimated. This TES probably won't be able to forecast unknown things, like the possibility of a particular ailment. Therefore, supervised learning techniques like linear regression can address this issue. We attempted to analyze the current COVID-19 TES by modeling the regression equation to forecast the chance of a particular disease that is COVID-like based on the CF value and the confidence level of the symptoms. To examine the most effective regression model to address the issue, we employed multi-linear regression (MLR) and multi-polynomial regression (MPR). The findings demonstrate that the MLR and MPR models are the most accurate regression models for estimating the chance of a disease associated with COVID-like symptoms. Our work built a basis for the creation of expert systems by concentrating more on MLES (machine learning expert systems) analytical techniques than TES.
Co-Authors Achmad Muchsin Agung Pangestu Al-Hakim, Rosyid Al-Hakim, Rosyid Ridlo Alrahman, Mahmmoud H. A. Arif, Machnun Dewi Sukma Eko Widaryanto Fitria Yuliasmara Karuniawan Puji Wicaksono Muhammad Yusro Risma Ekawati, Risma Setiawan, Antonius Sudarsono Sugianto, Pingkan Wahyudiana, Nadhilla H Wilyanti, Sinka