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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 9 Documents
 1 
Search results for , issue "VOLUME 2, ISSUE 1, February 2021" : 9 Documents clear
Identification of TENORM in Zirconium Oxychloride with Gamma Spectrometry Kharistya Rozana; Devi Swasti Prabasiwi; Dewi Puspa Ariany
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.art8

Abstract

Abstract: Gamma spectrometer used to determine the type and activity of gamma emitting radionuclides, such as the measurement of TENORM (Th-232, U-238, Ra-26 dan K-40) in the zirconium oxychloride or environmental radioactivity.  This research was carried out to know each the TENORM on the zirconium oxychloride (ZrOCl2.8H2O) which accommodation of environment data the radioactivity in draft job safety about the workers.  Zirconium oxychloride is a result of chloride acid leaching process from sodium zirconate, containing uranium and thorium, so that it has the potential for contamination and increase the radiation exposure.  The instrument used for counting by HPGe detector and the spectrum were analyzed further using software Genie 2000.  Mean measured activity concentrations (radioactivity) of U-238, Th-232, Ra-226 and K-40 respectively were 13,43±0,876 Bq/kg, 12,040±1,483 Bq/kg, 11,400±0,582 Bq/kg dan 32,940±3,270 Bq/kg.
Hidden Markov Model for Sentiment Analysis using Viterbi Algorithm Nursyiva Irsalinda; Haswat Haswat; Sugiyarto Sugiyarto; Meita Fitrianawati
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.art3

Abstract

Data mining is an activity to extract the knowledge from large amounts of data as very important information. The type of data in the era of 4.0 is data in the form of text, which is very much derived from social media. Recently, text becomes very important in some applications, such as the processing and the conclusion of a person's review and analysis of political opinion which is very sensitive in almost all countries, including Indonesia. Online text data that circulating on social media has several shortcomings that could potentially hinder the analysis process. One of the drawbacks is the people can post their own content freely, so the quality of their opinions cannot be guaranteed such as spam and irrelevant opinions. The other drawback is the basic truth of the online text data is not always available. Basic truth is more like a particular opinion, indicating whether the opinion is positive, negative and neutral. Therefore, the main objective of this study is to improve the forecasting accuracy of online text data analysis from social media. The method used os Hidden Markov Model (HMM) with Viterbi Algorithm that applied to extract the dataset sentiment at the 2015 elections in Surabaya from the popular site micro blogging called Twitter. The result of the study is Viterbi algorithm has predicted the best route with the candidate Tri Rismaharini gained a prediction of neutral sentiments, whereas ratio candidates gained sentiment negative predictions as well. The proposed Model is accurate to predict candidate features. It also helps political parties to introduce candidates based on reviews so that they can increase candidate performance or they can manage broad publicity to promote candidates.
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
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%
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.
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.
Fuzzy Logic Application for Drought Risk Determination in Kulon Progo Regency, Daerah Istimewa Yogyakarta Province, Indonesia Bertolomeus Laksana Jayadri; Agus Maman Abadi
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.art9

Abstract

This study aims to determine the drought risk of Kulon Progo Regency using fuzzy logic and study the characteristics. The input variables used in this study are the drought level, exposed population, and vulnerable population. The Mamdani method used in the fuzzy inference to obtain the output variable, that is, the Drought Risk Index (DRI). Then, the DRI are mapped to generate the drought risk map. The result shows that the fuzzy logic can be used to determine the drought risk. The drought risk level of the subdistricts in Kulon Progo Regency was fluctuated from 2010 to 2019. The drought risk level in 2010-2015 and 2019 were dominated by the low category. Meanwhile, the drought risk level in 2016-2018 was dominated by the very low category. Furthermore, the result also shows that the subdistricts located in the southern region of Kulon Progo Regency had a higher risk than those in the middle and northern regions during the last 10 years

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