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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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Forecasting of Export Value in Indonesia Using Top-Down Hierarchical Time Series Based on Historical Proportion Inas Rafidah; Kartikasari, Mujiati Dwi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art2

Abstract

Export is a trading activity carried out between countries by bringing or sending goods originating from within the country to foreign countries with the aim of selling or marketing them. Exports as a source of state revenue are needed for the economy because exports can make a major contribution to economic stability and growth. Export values that experience a decrease or increase in the future need to be considered. For this reason, the purpose of this study is to forecast the value of exports in Indonesia for the coming period. Export value data is treated as hierarchical time series data. The top-down method is applied based on historical proportions, so only the total series of export values needs to be modeled. This study implements Autoregressive Integrated Moving Average (ARIMA) to model the total series of export values. The performance of the method is evaluated based on the out-of-sample mean absolute percentage error (MAPE). The results show that the MAPE for out-of-sample is 9.91%. These results indicate that the performance of the method for forecasting export values in Indonesia is highly accurate.
Formulation of Nanoemulsion of Gotu Kola (Centella asiatica (L.) Urban) Leaves Extract as Active Ingredients to Produce Antioxidant Facial Serum Fitri, Noor; Tanjungsari, Afifah Adinda; Himmi, Setiawan Khoirul; Solihat, Nissa Nurfajrin
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art10

Abstract

Abstract: Free radicals can cause cell damage such as premature aging. To protect, ward off and stabilize free radicals, antioxidant compounds can be used. Plants that can be used as a source of antioxidants are gotu kola (Centella asiatica (L.) Urban). The aim of this research is formulating a nanoemulsion of gotu kola leaves extract as an active ingredient for producing the antioxidant serum. The steps of this research include: (1) extraction by maceration and Microwave-Assisted Extraction (MAE); (2) extract characterization; (3) formulation of nanoemulsion using Self-Nanoemulsifying Drug Delivery System (SNEDDS) method; (4) nanoemulsion testing: stability test, antioxidant activity test, and irritation test, (5) nanoemulsion characterization which includes particle size, transmittance, pH, and viscosity. The results showed that: (1) yields of the maceration method and MAE were 14,60% and 17,54%; (2) antioxidant compounds in gotu kola leaves extract are squalene, kaempferol, asiaticoside; The IC50 of the maceration and MAE extract were 93,152 ppm and 80,365 ppm; (3) nanoemulsions were made in 3 formulas (0,1; 0,3; and 0,5 g) with fixed variables of capryol 90, tween 20, and PEG 400 (1,5; 2,5; and 1); (4) stability test showed that only F1 was stable; the IC50 value of nanoemulsion is 2604,967 ppm; and the F1 irritation test showed no erythema and edema; (5) The particle size of F1 is 166,7 nm with a transmittance value of 97.4%, a pH of 5,33, and a viscosity of 75,35 cP.
Peramalan Harga Bawang Merah dan Cabai Merah Menggunakan ARIMAX Model Lestari, Dian Widya Lestari; Dini, Sekti Kartika
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art5

Abstract

Shallots and red chilies are superior vegetable crops and contribute quite a lot to the development of the national economy. Prices of these two commodities fluctuate almost every year. At certain times the price of both commodities soared due to high demand while supply in the market was insufficient. So, it is necessary to do an analysis to see what phenomena have a significant influence on the increase in the price of shallots and red chilies. The method used in this study is ARIMAX with exogenous variables, namely variables dummy monthly and various religious holiday calendars such as Chinese New Year, Eid al-Fitr, and Eid al-Adha. The results of the analysis show that the price of shallots is influenced by calendar variations one month after Chinese New Year and one month before Idul Fitri. Meanwhile, the price of red chilies is influenced by the month before Chinese New Year, during Chinese New Year, and a month after Chinese New Year, a month before Eid al-Fitr and during Eid al-Fitr, a month before Eid al-Adha and during Eid al-Adha. Shallots and red chilies ARIMAX models obtained a MAPE value of 17.36% and 25.62%.
Enhancing Air Travel Analysis: Forecasting Domestic Flight Activities in Indonesia based on Aircraft Types using MLP Utari, Dina Tri; Sumarna, Zahra Maharani Putri
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art3

Abstract

The COVID-19 pandemic has succeeded in bringing down various industrial sectors, including the aviation industry. This pandemic impacted the depletion of the operational fleet. In 2022, the number of domestic aircraft ready for operation was only around 55%–60% compared to 2019. However, with all its limitations, the aviation industry must develop the best strategy to revive in this post-pandemic era. One of the strategies undertaken is selecting the most efficient and economical aircraft type to cut costs amid market uncertainty due to this pandemic. In this regard, research was carried out to predict when aviation activity in Indonesia would reach regular in January 2020 and the forecast for the dominance of aircraft types in domestic flight. Multilayer Perceptrons (MLP) show that domestic flight activities in Indonesia will reach the standard point in March 2024. From the forecast result, the error rate using MAPE is 0.52%. The aircraft that dominates Indonesia’s domestic flight activities during 2020–2022 is the Airbus 320 type. Meanwhile, for the next two years—2023 & 2024—it is predicted that the Airbus 320 type will continue to dominate the flights.
Rainfall Conditions When Maden Julian Oscillation Strong and Weak: Temporal Distribution in Jakarta, Bogor, and Tangerang Wibowo, Ofana Tri; Afghani, Fadhli Aslama; Christofelts, John Pieter; Halawa, Jordana Christian
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art1

Abstract

The Indonesian Maritime Continent has high rainfall variability with one of the causes, namely the Madden Julian Oscillation (MJO), especially in phases 3, 4, and 5. Madden Julian Oscillation (MJO) and rainfall have a correlation with one another. Therefore, this study aims to determine the effect of MJO on rainfall conditions in terms of intensity and frequency of occurrence every three months from 2013-2022 in Jakarta, Bogor, and Tangerang. The research method used is descriptive statistical analysis in the form of quarterly rainfall averages and anomalies as well as the Pearson correlation test. The data used is daily rainfall data for the 2013-2022 period. The results of the descriptive analysis show that the highest average rainfall occurs in the DJF period and the lowest is in the JJA period with the anomalies occurring in the DJF and JJA periods. On the other hand, the lowest frequency of strong and weak MJO events occurs during JJA, while the highest occurs during the DJF period. The correlation test conducted between the Madden Julian Oscillation (MJO) and rainfall found that the highest positive correlation value was 0.197073 on MAM and the highest negative correlation on SON was -0.11866, so the relationship is weak.
Negative Binomial Panel Regression Modeling on Amount of Crimes In Lampung Province Suratmin, Idam Abdurrohim Hasani; Agustina, Dian; Agwil, Winalia
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art4

Abstract

Crime in Lampung province is among the 10 highest in Indonesia in 2021. This study aims to obtain a model of the number of crimes and factors influencing it using negative binomial panel regression. The data used is in the form of panel data from the Lampung Province BPS website and publications for 2017-2021. The condition of data on the number of crimes as discrete and overdispersed data makes the negative binomial panel regression method more suitable than Poisson panel regression. Overdispersion is a state where the variance of the data is greater than the mean value of the data. Overdispersion causes the standard error (SE) of the estimated value to decrease, so that variables that should not be significant become significant. The factors thought to be the cause of crime are percentage of poverty (X1), population density (X2), expenditure per capita (X3), unemployment rate (X4), regional gross domestic income (X5), and the average duration of schooling (X6). The results of the analysis obtained for the selected panel data model are the negative binomial random effects (REBN), the influencing factors being X1, X3, X4 and X5. The districts/cities with the largest individual random effects were in the Way Kanan district and the smallest were in Metro City.
Sentiment Analysis and Topic Modelling of Bjorka Using Support Vector Machine and Latent Dirichlet Allocation Muhajir, Muhammad; Rosadi , Dedi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art7

Abstract

A wide range of data is now easily accessible via the microblogging service Twitter thanks to the rapid advancement of technology. The Bjorka controversy, one of the most talked-about topics right now, has generated numerous comments from the general public and thus has risen to the top. The Bjorka phenomenon is an obvious example of cybercrime, with a sharp uptick in incidents occurring in Indonesia during the COVID-19 pandemic. Sentiment analysis employing the Support Vector Machine technique allows for the statistical analysis of public opinion about Bjorka as it appears on the Twitter social network. Latent Dirichlet Allocation (LDA) will be used to analyze the sentiment analysis with SVM results, which have been separated into positive and negative sentiments. In this study, using LDA for sentiment analysis resulted in an accuracy of 89.5%. Dismantling government data, including personal data and government crimes, was the most positively predicted topic, with 75.2% of all predictions leaning in that direction. It is hoped that the government will be able to use the information gleaned from this study to better understand the public’s perspective and the trust deficits that need to be addressed
Analysis of Monthly Rainfall Characteristics in Nusa Tenggara Timur and its Spatial and Temporal Shifts Afghani, Fadhli Aslama; Ofana Tri Wibowo; Imawan Mashuri; Zuhairul A, Hasyid Agha
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art9

Abstract

The spatial characteristics of rainfall in Nusa Tenggara Timu for the periods 1961-1990 and 1991-2020 show similarities in terms of topography influencing local variations in rainfall intensity. Additionally, inland areas and the northern side of region experience higher rainfall compared to the coastal areas and the southern side. On the other hand, temporal characteristics reveal a monsoonal rainfall pattern with peak precipitation occurring in January and the lowest rainfall in August. Furthermore, there is a normal shift in rainfall patterns between the two periods, marked by a reduction in the intensity of dark colors in the 1991-2020 period compared to 1961-1990. There is also a positive shift in normal rainfall values for the months of April and December, while the remaining months experience a negative shift.
K-Means ++ Algorithm for Health Services Clustering Based on Districts in West Java Province Nur, Indah Manfaati; Abdurakhman
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art11

Abstract

A healthy and prosperous life is one of the goal points listed in the Sustainable Development Goals (SDGs). To create a healthy life, support is needed in the form of equal health facilities and services for all people in all provinces of Indonesia. In fact, there are still provinces that have low levels of health service facilities. West Java is ranked last with low health service conditions. Grouping efforts are needed to identify cities or districts in West Java that deserve priority for handling health facilities. In this study, the K-Means++ method was used to group health facilities based on cities or districts in West Java Province. Based on the grouping results, 3 clusters were obtained, namely cluster 1 for groups with low health facilities with 18 cities/regencies as members, cluster 2 for groups with moderate health facilities with 7 cities/regencies, and cluster 3 for groups with high health facilities with 2 cities/regencies
Optimasi Prosedur Kultur H9C2 Kardiomioblas: Sebuah Pembelajaran untuk Membangun Model Studi In-vitro Kardiovaskular Fadhillah, Muhamad Rizqy; Arozal, Wawaimuli; Wibowo, Heri
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art8

Abstract

Cardiovascular disease become one of the leading factors of death in the world. Thus, research is urgently needed to discover newer drugs or therapeutical agents and biological plausibility. The H9C2 cardiomyoblast originated from embryonic BDIX rat ventricular cells and was previously used in numerous in vitro studies because of its similar nature to cardiomyocytes. However, to our knowledge, there are still limited studies on the basic procedure for culturing H9C2 cardiomyoblast and arranging the best strategy to perform a suitable timeline. Here, we shared our experience in culturing the H9C2 cardiomyoblast, including harvesting and subculturing the cells. We also demonstrated the change of cell confluency, depending on the seeding number, serum concentration, and culture flask through days 1, 3, and 6, to determine their doubling-time population. H9C2 cardiomyoblasts’ doubling time is around 48-54 days with Mean±SD 2.38±0.41. However, seeding density, different culture flasks, and serum concentration have become independent factors in determining specific measures to harvest the cells for further experiments.

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