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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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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
Prediction of Outstanding Claims Liability in Non-Life Insurance: An Application of Adaptive Grey Model Mujiati Dwi Kartikasari; Hani’atul Maghfuroh
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.art4

Abstract

In order to assess the solvency of non-life insurance companies, the prediction of outstanding claims liability is very important. Prediction of outstanding claims liability is usually done by using a run-off triangle data scheme. However, if data are not available to form the scheme, the prediction of outstanding claims liability cannot be made. Another alternative for predicting of outstanding claims liability is to use time series analysis. This research uses an adaptive grey model that has the advantage of being free of assumptions of data patterns and a minimum amount of data used to predict is small (at least 4 data). To determine the accuracy of the adaptive grey model, we compare the prediction of outstanding claims liability using a grey model classic. Based on the analysis results, the adaptive grey model is better than the classic gray model in predicting outstanding claims liability.
Composite of Polylactic Acid/Chitosan/Ag-Hydroxyapatite Synthesized Using Turmeric Leaves Extract-Mediated Silver Nanoparticle and Snail Shell as Antibacterial Material Rahmania Audita; Khoirunisa khoirunisa; Hasna' Azizah Azzahra'; Bambang Hernawan Nugroho; Habibi Hidayat; Is Fatimah
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.art5

Abstract

The development of an antibacterial composite of polylactic acid/chitosan/silver nanoparticle-doped hydroxyapatite has been synthesized. The composite was prepared using the silver nanoparticles (AgNPs) green synthesized by using turmeric (Curcuma longa Linn) leaves extract-mediated AgNPs and snail shell as biogenic calcium for hydroxyapatite synthesis. The precipitation method of hydroxyapatite by the doping of AgNPs was the first step, followed by composting with polylactic acid and chitosan as the polymer binder. Physicochemical characterization of the material was studied by using XRD, SEM, and FTIR analyses, and the antibacterial catalytic performance was examined against Escherichia coli (E. coli). The results showed that the synthesized AgNPs are within the <100 nm range in size and not significantly influence the crystallinity of the Ag/HAp. The composite materials maintained the antibacterial activity against E. coli.
Microwave and Ultrasound Irradiations for the Intensification on Biodiesel Productions: a Mini Review Suresh Sagadevan; Amri Yahya; Is Fatimah
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.art6

Abstract

This mini review discusses the roles of intensification process in biodiesel production. Due to the Twelve Principles of Green Chemistry as a foundation for sustainability, the shorter time and efficient energy consumption highlighted the use of microwave and ultrasound irradiation for increasing conversion of biodiesel.The principles and some examples for the process are exhibited. It can be summarized that the intensifications are important innovations, but some optimization and life cycle analysis are required in applicable scales.
Evaluation of Heavy Metals Concentration in Milk Products by using Atomic Absorption Spectroscopy Nurul Auni Zainal Abidin; Nur Sofiah Abu Kassim Kassim; Sheikh Ahmad Izzadin; Sheikh Mohd Ghazali; Noor Hidayah Pungot; Siti Sufiana Kamni
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.art7

Abstract

Milk products are essential food in the human diet because it contains many essential trace minerals such as calcium, magnesium, copper, zinc, sodium, potassium and phosphorous. The utilization of, milk is increasing at a large scale throughout the world. It is essential to maintain the good quality of milk during production and manufacturing because the presence of toxic metals in the milk becomes the cause of health disturbance in human life. Therefore, the present investigation was carried out to determine concentrations of lead, nickel, iron, copper, and chromium in powdered milk and fresh milk products by Atomic Absorption Spectroscopy. Different milk samples of products (two fresh milks and two powdered milks) were purchased from the local market. For the decomposition of the organic substances in milk samples, wet digestion was used with a mixture of nitric acid and sulfuric acid in volume proportions 1:3 (v/v). The analytical curve for all metals covered the linear range from 0.5 to 4.0 ppm with correlation coefficients higher than 0.9994. The limit of detection (LOD) for Pb, Ni, Fe, Cu, and Cr were found to be 0.25, 0.023, 0.012, 0.0067, and 0.073 ppm, respectively. While the limit of quantification (LOQ) in the range of 0.02 to 0.76 ppm. Of all the metals determined, Pb, Ni, and Fe were the most abundant with concentrations between 1.233 and 1.677 ppm while Cr was not detected in all the samples. The results showed that fresh milk samples have a higher concentration of heavy metals compared to powdered milk samples.
Utilization of Cassava Processing Liquid Waste as Raw Material for Making Biodegradable Plastics with the Addition of Glycerol Plasticizer Iswendi Iswendi; Iryani Iryani; Alpira Alpira; Regi Fadila Putra
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.art2

Abstract

This study aimed to utilize cassava processing liquid waste into biodegradable plastic with glycerol as a plasticizer. This experimental study varies the amount of glycerol: (0, 1, 2, 3, 4, and 5) mL. The resulting biodegradable plastics were analyzed for physical properties consist of (water content and degree of swelling), mechanical properties consist of (tensile strength, elongation, elasticity), biodegradation, and structural properties. Fourier Transform Infra-Red and x-ray diffraction were employed for the studies. The results showed that the more glycerol added, the greater the percentage of water content and the degree of swelling were obtained. The optimum tensile of the biodegradable plastic was reached with 3 mL of glycerol, giving the strength of 27.49 N/mm2, elongation 0.107 N/mm2, elasticity 4.804 MPa. Biodegradable plastic with the addition of 5 mL of glycerol degraded up to 60.777%. The FTIR spectra showed almost the same peaks between plastics without the addition of glycerol and glycerol. Meanwhile, XRD data shows that the degree of crystallinity of plastic without glycerol is higher than that of plastic with the addition of glycerol.
Impacts of Human Development Index and Percentage of Total Population on Poverty using OLS and GWR models in Central Java, Indonesia Duhania Oktasya Mahara; Achmad Fauzan
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.art8

Abstract

Central Java province is one of the provinces with the highest number of poor people on the island of Java, with the number of poor people in 2020 increasing by 0.44 million people from the previous year. Poverty is caused by several factors, one of which is the Human Development Index (HDI) and the Total Population level. Each region has different characteristics from other regions. These differences in characteristics cause more specific spatial effects, namely spatial heterogeneity. Geographically Weighted Regression (GWR) is a statistical method that can analyze spatial heterogeneity by assigning different weights and models to each observation location. This study aims to determine whether the HDI variable and percentage of total population significantly impact the number of poor people in Central Java Province in 2020 without eliminating the spatial effect. There are three groupings of variables that affect the Number of Poor People for GWR with the Adaptive Kernel Bisquare weighting function and four groups for the Adaptive Kernel Tricube weighting function. The Key Performance Indicators (KPI) used are Mean , Akaike Information Criterion (AIC), Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). Based on these KPIs, the GWR model with the Adaptive Kernel Bisquare weighting function provides better results when compared to the OLS model.
Hierarchical Clustering Approach for Region Analysis of Contraceptive Users Dina Tri Utari; Denesa Salma Hanun
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.art3

Abstract

Through increasing the use of contraceptives to limit births, the Family Planning (KB) Program is one of the government's efforts to control the rate of population growth. Klaten Districts is one of the regencies in Central Java Province with a relatively high number of births and relatively low coverage of active family planning. This study aimed to determine the grouping of sub-districts and these characteristics in the Klaten Districts in 2020. The method used in this study was a hierarchical cluster analysis method, with the best method being the centroid method. In this study obtained 3 clusters with cluster 1 consisting of 23 sub-districts, cluster 2 consists of 2 sub-districts and cluster 3 with 1 sub-district. The cluster characteristics based on the highest number of users of contraceptive methods are cluster 1-contraceptives injection, cluster 2- contraception implant, and IUDs in cluster 3
Analysis of Hotels Spatial Clustering in Bali: Density-Based Spatial Clustering of Application Noise (DBSCAN) Algorithm Approach Achmad Fauzan; Afdelia Novianti; Raden Rara Mentari Ayu Ramadhani; Marcelinus Alfafisurya Setya Adhiwibawa
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 1, February 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss1.art4

Abstract

Bali is one of the hearts of tourism in Indonesia. The existence of the Covid-19 pandemic has made this tourist paradise also affected the wheels of the economy. Based on this, this study aims to determine the density clustering of one of the economic supporters in Bali, namely hospitality. The study began with the quadrant method and Ripley's K-Function to measure the distribution pattern of hospitality. From the results of the two methods, the distribution pattern of hotels in Bali is more towards clusters than random or regular distribution. If the point distribution pattern is more towards the cluster, it is continued with the Density-Based Spatial Clustering of Application Noise (DBSCAN) algorithm to form spatial clustering. In the DBSCAN algorithm, a combination of parameters, namely minimum points (MinPts) and epsilon (Eps), is carried out with evaluation using the silhouette average width value. From the results of the DBSCAN algorithm, the clustering results show that the distribution of hotels in Bali forms clusters and tends to approach the surrounding tourist attractions, such as near the beach, city market, and mountainous areas. It can help policymakers if they want to prioritize economic recovery after the Covid-19 pandemic.
Validation Method on Green Analysis of Nitrite in Domestic Wastewater Yuli Rohyami; Lutfiana Aida Rahmah; Endah Iniati
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 1, February 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss1.art1

Abstract

The development and validation of methods on green analysis of nitrite in domestic wastewater has been carried out. This study is focused on the development and validation of nitrite determination using a smaller sample size with test kit nitrite from phosphoric acid, acid sulfanilamide, and N-(-naphthyl)-ethylenediamine dihydrochloride. The validation parameters studied include linearity, the limit of detection, the limit of quantification, precision, accuracy, and uncertainty. Based on the study, the green analysis procedure has good linearity with the linear regression equation of y = 2.8405x + 0.0043 with the correlation coefficient of 0.9992. Green analysis can be used detection and quantification nitrite in domestic wastewater at low concentration levels with the limit of detection of 0.01 mg/L and the limit of quantification of 0.03 mg/L. This green analysis procedure has good precision and accuracy with a % RSD of 1.61% and % recovery of 109.61%. Based on the study, the determination of nitrite with the green analysis method in domestic wastewater can be used at low concentration levels. The concentration of nitrite is 0.05 + 0.01 mg/L for inlet sample and 0.04 + 0.01 mg/L for outlet sample

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