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INDONESIA
EKSAKTA: Journal of Sciences and Data Analysis
Published by Universitas Islam Indonesia
ISSN : 27160459     EISSN : 27209326     DOI : 10.20885
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology
Ekstakta is an interdisciplinary journal with the scope of mathematics and natural sciences that is published by Fakultas MIPA Universitas Islam Indonesia. All submitted papers should describe original, innovatory research, and modelling research indicating their basic idea for potential applications. The Journal particularly welcomes submissions that focus on the progress in the field of mathematics, statistics, chemistry, physics, biology and pharmaceutical sciences.
Arjuna Subject : Kimia(semua kategori) - Kimia (Lain-Lain)
Articles 231 Documents
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Collective Modified Value at Risk in Life Insurance Muhammad Iqbal Al-Banna Ismail; Abdul Talib Bon; Sukono Sukono; Adhitya Ronnie Effendie
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art4

Abstract

Insurance is seen as a tool which individuals can transfer risks to others, where insurance collect funds from individuals to meet financial needs related to damage. Therefore analysis of risk in life insurance claims is really be needed bt the insurance company actuary. In an insurance system, the risk is the event when an insured party puts forward a claim. Claim is the compensation for a risk loss. Individual claim in one period insurance is called aggregation claim while aggregation claim is collective risk
Preface and Table of Content Editor Editor
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 2, August 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Edisi Agustus  2020
Data Mining Approach for Educational Decision Support Sinta Septi Pangastuti; Kartika Fithriasari; Nur Iriawan; Wahyuni Suryaningtyas
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art5

Abstract

data mining techniques in education sector have begun to evolve, along with the development of technology and the amount of data that can be stored in an education database storage system. One of them is a database of Bidikmisi scholarships in Indonesia. The Bidikmisi data used in this study will be classified using classification data mining technique. The technique that used in this study is random forest in combination with boosting algorithm and bagging algorithms. These algorithms also combine with SMOTE algorithm to handling the imbalance class in dataset. Based on the performance criteria G-mean and AUC, the algorithm combines with SMOTE tended to be better. The classification accuracy of each method being more than 90%
Utilization Copula in Determination of Shallot Insurance Premium Based on Regional Harvest Results Hasna Afifah Rusyda; Achmad Zabar Soleh; Lienda Noviyanti; Anna Chadidjah; Fajar Indrayatna
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 2, August 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol1.iss2.art11

Abstract

Abstract: Shallot is one of the highest-yielding horticultural crops in Indonesia and has the tendency to increase the profits of farmers in Indonesia. But until now in Indonesia there is no insurance for horticultural crops other than corn, whereas the shallot farmers face various sources of risk such as weather changes, pest attacks, or other technical factors that ultimately lead to uncertainty of agricultural yields (revenue risk). To overcome this loss, insurance companies can make products based on shallot yields and shallot market prices. Therefore it is essential to grasp the distribution of risk variables (shallot yields and shallot market prices) that interact simultaneously, not separate from one another. Omitting dependencies among risk variables can cause biased risk estimation. Copula can model the non-linear dependencies and can identify the structure of the dependencies between variables. The suitable copula for modeling yield and price risk of shallot is simulated to compute the premium. Result show that clayton copula is suitable for dependence modelling between risk variables.
Synthesis and Characterization of TiO2 Nanoparticles Doping on Cellulose as Adsorbent for Removal of Rhodamine B in Aqueous Solution Allwar Allwar; Mayla Nur Fatima; Bayu Wiyantoko
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art6

Abstract

Cellulose from banana fruit bunch was used as a precursor for doping titanium oxide (TiO2) in producing of TiO2/cellulose adsorbent.  Cellulose was obtained by chemical impregnation using potassium hydroxide (KOH) and followed by the hydrothermal process at 250oC for 5 h. The mixture of TiO2 nanoparticles and cellulose was carried out into hydrothermal reactor under de-ionized water and ethanol and heated up to 200oC for 4 h in graphite furnace. Surface morphology analysis showed that the TiO2 clearly immobilized on the surface of cellulose with an increasing roughness of surface and irregular size of porosity. The development of the amorphous to the crystalline phase of TiO2/cellulose was clearly observed by the XRD. The effectiveness of TiO2/cellulose for removal of rhodamine B was investigated from different parameters of adsorption in aqueous solution. Kinetic models were well described by the pseudo-first and second-order with the best correlation coefficient (R2) attributing to the occurrence of chemisorption and physisorption mechanism.
Fuzzy Logic of Work Conformity in Small Enterprises of Traditional Medicines Eliza Dwinta; Ajie Kusuma; Baniady Gennody Pronosokodewa; Raden Jaka Sarwadhamana
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art1

Abstract

Good Manufacturing Practices for Traditional Medicine (CPOTB) certification given by National Food and Drug Agency (BPOM) to Small Enterprises of Traditional Medicines (UKOT) is a claim from the production process of traditional medicines that is in accordance with CPOTB. However, not all human resources at UKOT understand and apply existing guidelines in the work practices of traditional medicine production. This study aims to assess the conformity of work by calculating the gap between knowledge of work practices in human resources in one UKOT Yogyakarta with fuzzy method. This assessment is a quantitative, cross-sectional study using a questionnaire that was adapted and modified from six categories of cause and effect. Respondents included in this study were all human resources in UKOT as many as 24 people (total sampling). The results obtained from the gap calculation of work conformity based on the six categories are machinery that have positive values (0,1146). Human resources who work at UKOT have a good understanding of the CPOTB and are already good at implementing work practices in accordance with the CPOTB in the machinery category. The findings that personnel pass through the production area, storage area and quality control area, as well as analysis methods that have not been validated periodically, can be used as an ingredient for improvement by implementing corrective-action-preventive-action on order to improve the quality of work in accordance with CPOTB and guarantee the quality of traditional medicine products from the UKOT Yogyakarta.
Analysis Metallothionein of Carp fish in The Brantas River, Indonesia Putri Ayu Ika Setiyowati; Rofiatun Solekha; Sri Bintang Sahara; Febianti Dwi Hapsari
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 2, August 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol1.iss2.art8

Abstract

This study aimed to detection of protein profile, expression of metalothionein (MT) protein, and analyze difference of MT density in liver and gill in one of Carp fish that is Barbonymus balleroides in the upstream and downstream of Brantas river. The method used observasional analytic, Two individual of Barbonymus balleroides samples taken three times (with difference of month) from two station there are upstream and downstream of Brantas river. Analysis protein profile used electrophoresis SDS-PAGE (15%), expression and density of MT used western blot method and imageJ software. Difference between MT density in liver and gill of Barbonymus balleroides in the upstream and downstream of Brantas river analyzed with Two-way ANOVA. The results showed, protein profile in liver and gill Barbonymus balleroides in the upstream and downstream Brantas river have molecular weight about 8-93 kDa, expression of MT showed band of MT with molecular weight 24 kDa, results of MT density in liver and gill on upstream and downstream, continuously 231.29 MT/µm2 and 229.87MT/µm2, 232.41 MT/µm2 and  231.56 MT/µm2 but there is not significant.
DEVELOPMENT OF ALGORITHM OF SMART GEOGRAPHIC AREA Yusifov S.I; Ragimova N.A; Abdullayev V.H; Khalilov M.E
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art7

Abstract

The rapid development of information technologies accelerates the approximations of industry 4.0, which is why sectors of the economy and science must adapt to these changes. Global changes in geography have led to the emergence of a new scientific discipline called geoinformatics. It then provides insight into the Smart Geographic Area, its structure and the main components. To do this, there used methods for communicating the main components IIoT, IoE), for analyzing data (Big Data, Hadoop), for managing processes (CPs), for storing data (Cloud Computing, Fog Computing). As a result of the study, there was developed a Smart Geographic Area algorithm based on the MapReduce paradigm.
Scholarship’s Payment Modelling for Work Accident Insurance Program (JKK) in Indonesia Yulial Hikmah
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art2

Abstract

Work Accident Insurance (JKK) is a protection for the risk of accidents or illness due to work during the service period. JKK is divided into two benefits, namely care and compensation. Undang-Undang Republik Indonesia No 102/2015 regulates that scholarship assistance is given in lump sum (at once). Giving lumpsum scholarship assistance is felt to be less on target. Some cases that have occurred, the recipient (heir) has not attended school when given scholarship assistance so it is probable that the scholarship assistance is not used properly. This study discusses 3 models, namely the lumpsum model based on Undang-Undang Republik Indonesia No 102/2015, alternative model 1 (Rp 30,000,000 and given when entering a new level of education), and alternative model 2 (Rp 40,000,000 and given when entering a new level of education). There are three criteria in determining the best model, which has a greater benefit value, the burden that must be borne by the company is smaller or the same as the lumpsum method and payment is more targeted. By using these three criteria, it was found that alternative model 2 was the best model.
Implementation of Minkowski-Chebyshev Distance in Fuzzy Subtractive Clustering Annisa Eka Haryati; Sugiyarto Surono; Suparman Suparman
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 2, August 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss2.art1

Abstract

Clustering is a method of the grouping which is done by looking at the similarities between data in a data set. Fuzzy clustering is a clustering method that uses fuzzy set membership values as the basis for grouping data. Fuzzy Subtractive Clutering (FSC) is a fuzzy clustering method where the number of clusters to be formed is unknown. The concept of FSC is to determine the highest data density and the data with the most number of neighbors will be selected as the center of the cluster. Thus, the size of the proximity or distance between points is needed to determine the members of each cluster. The distance used in this study is a combination of the Minkowski and Chebyshev distances. The number of clusters formed will be evaluated using the Partition Coefficient (PC) value where the highest PC value indicates the best number of clusters. The results obtained indicate that the best clusters are three clusters with a PC value of 0.7422

Page 16 of 24 | Total Record : 231

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