bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of Ontology on Crime Investigation process
Authors: Srimukh P V , Shridevi S 
Published: January 2021

Abstract
This paper is an extended version of the research paper “Ontology based crime investigation process” which deals with the working principle and the construction of an ontology based extensively on organized crime. Ontologies on various domains are created in which their assistance has been widely recognized. They are being developed for providing basis for allocation of knowledge in a domain and imparting reasonable information. In this paper we describe the structure of the ontology we created and also by validating the ontology via an online ontology evaluating tool.
Discrimination between the final state of t

t¯

H and t

t¯

b

t¯

using neural network
Authors: Putri R P , Sumowidagdo S , Primulando R , Mart T 
Published: January 2021

Abstract
After the discovery of the Higgs boson in 2012 at the Large Hadron Collider (LHC), the effort to understand the detailed properties of the Higgs bosons started. Of particular importance is study of the Higgs coupling to the top quark. This coupling can be studied through the associated production of Higgs boson with top-antitop quark pair, t

t

¯

H. This process however suffers from the indistinguishable background t

t

¯

H

b

¯

, since the Higgs boson decays predominately into bottom anti-bottom quark pair, b

b

¯

. This study presents systematic approach of using machine learning (ML), specifically neural network method to distinguish between the process t

t

¯

H and t

t

¯

b

b

¯

. Using input variables of kinematic variables (momentum), we found a signal efficiency of 46.7 % for signal events that have passed the preselection criteria. We conclude that the currently used input variables are not sufficient to discriminate between signal and background events, and we suggest that inclusion of input variables calculated from the fully reconstructed event could provide stronger discrimination between signal and background.
Preparation of LaMnO3/TiO2/NGP composites for methylene blue dye removal via adsorption and photosonocatalysis
Authors: Susanti Y D , Afifah N , Saleh R 
Published: January 2021

Abstract
In this study, LaMnO3/TiO2/nanographene platelet (NGP) composites with different loadings (3, 5, and 10 wt.%) of NGP were successfully synthesized by co-precipitation. The as-prepared composites were characterized by X-ray diffraction (XRD) and Raman spectroscopy. The XRD patterns confirmed the combination of the desired nanoparticles. The Raman spectra of the LaMnO3/TiO2/NGP composites revealed the D-and G-band structures of NGP. Furthermore, the composites were investigated for the degradation of methylene blue (MB) via adsorption and photosonocatalysis. The maximum degradation of MB via adsorption was achieved at 10 wt.% NGP loading in LaMnO3/TiO2/NGP, whereas for photosonocatalysis, the maximum degradation of MB was observed at 5 wt.% NGP loading. In addition, the pseudo-first-order and second-order adsorption kinetic models and the effect of scavengers on photosonocatalysis were evaluated.
Preparation of CeO2/TiO2/NGP composites as efficient catalyst for removal of organic dye using photo-, sono-, and sonophotocatalytic activity
Authors: Tju H , Taufik A , Saleh R 
Published: January 2021

Abstract
A simple hydrothermal technique was used to incorporate nanographene platelets (NGP) with CeO2/TiO2 composites with different NGP contents. The prepared samples were then evaluated as a heterogeneous catalyst to degrade methylene blue (MB) under visible light irradiation, ultrasonic irradiation, and a combination of the two. The structural and morphological properties of CeO2/TiO2/NGP composites were investigated by X-ray diffraction (XRD). The XRD spectra of CeO2/TiO2/NGP revealed the spectra of NGP, CeO2, and TiO2 nanoparticles indicating the desired combination. Further investigation using TGA measurements show that weight was lost at around 600 °C due to the combustion of carbon. The surface area of the composites was further increased. The prepared CeO2/TiO2–10 wt.% NGP composites were able to degrade MB four times higher than pristine CeO2/TiO2 composites, which may be due to a lower recombination rate; however, further increments of NGP decreased the degradation efficiency.
Influence of carbon-based material incorporation on Ag/Fe3O4/ZrO2 composite as highly efficient catalyst for photo- and sonodegradation of organic pollutant
Authors: Kristianto Y , Saleh R 
Published: January 2021

Abstract
In this work, a novel quaternary composite, Ag/Fe3O4/ZrO2/NGP and Ag/Fe3O4/ZrO2/graphene, as highly efficient catalysts were prepared through ultrasonic-assisted and co-precipitation methods. The prepared composite was characterized by X-ray diffraction (XRD), thermal gravimetric analysis (TGA) and vibrating sample magnetometer (VSM). The photo- and sonocatalytic activity of prepared composite were studied through the degradation of methylene blue (MB) as a model of organic pollutant under UV light and ultrasonic irradiation, separately. The experimental results showed that the composite contained a combination of the desired nanoparticles. In the catalytic activity, Ag/Fe3O4/ZrO2/graphene exhibited much higher efficiency than Ag/Fe3O4/ZrO2/NGP and Ag/Fe3O4/ZrO2 composite. Furthermore, the influence catalyst dosage was studied. To understand the role of reactive species in the sonocatalytic activity, several scavengers were tested. The reusability study suggested that the prepared composite remain stable even after four cycles reused.
Detection of Alzheimer’s disease with segmentation approach using K-Means Clustering and Watershed Method of MRI image
Authors: Holilah D , Bustamam A , Sarwinda D 
Published: January 2021

Abstract
Alzheimer’s disease is a common form of neurodegenerative disorders characterized by defective brain cells, such as neurofibrillary tangles and amyloid plaque that is progressive. One of the physical characteristics of someone suffering from Alzheimer’s disease is shrinking of the hippocampus area of the brain. The hippocampus is the smallest part of the brain that serves to save memory. The detection of Alzheimer’s disease can be done using a Magnetic Resonance Image (MRI) which is a technique of noninovasive for an analysis of the structure of the brain in the Alzheimer’s patient. In this research, K-Means Clustering and Watershed method are used to segment the hippocampus area which is one part of the brain that was attacked by Alzheimer’s disease. The analysis used to detect Alzheimer’s is comparing the value of the threshold with the number of white pixels in the images. The data used in this research are Open Access Series of Image Studies (OASIS) database by using the image of coronal slices. Based on the our experiment result, both K-Means Clustering and Watershed method can segment the hippocampus area to detect Alzheimer’s disease.
Bayesian logistic regression and its application for hypothyroid prediction in post-radiation nasopharyngeal cancer patients
Authors: Lukman P A , Abdullah S , Rachman A 
Published: January 2021

Abstract
Logistic regression models are commonly used to model response variables in the form of categorical variables with several predictor variables. The contribution of the predictor variable to the response variable is expressed through a regression coefficient (β). Therefore, it is necessary to estimate β. This study discusses the estimation of β using the Bayesian method. Bayesian approach utilizes a combination of information from sample data and prior information about the characteristics of the parameters of interest, resulting in the updated information, namely the posterior. Bayesian method thus can overcome the problem if the quality of the sample data does not support observation. Bayesian logistic regression method will be used in analyzing post-radiation nasopharyngeal cancer (NPC) patient data, using measurement on Zulewski’s score components. Markov Chain Monte Carlo with Gibbs Sampling were used to obtain the sample from posterior distribution. Convergent estimates were obtained, and the result showed that Zulewski’s component scores only were not enough to explain the hypothyroidism in NPC. Additional information is required in order to explain the incidence of hypothyroidism in NPC.
Multiclass classification of leukemia cancer data using Fuzzy Support Vector Machine (FSVM) with feature selection using Principal Component Analysis (PCA)
Authors: Fauzi I R , Rustam Z , Wibowo A 
Published: January 2021

Abstract
Cancer is the second leading cause of death globally. According to WHO prediction (2015) cases of cancer deaths will increase to 21.6 million cases by 2030. Therefore, early detection of cancer is necessary to avoid the spread of cancer and machine learning is required to increase performance in the detection of cancer. In general, microarray cancer data consist of many features. However, there are several features in cancer data that did not have important information in classification cancer. Therefore, these features will be summarized from several features under some common underlying factors into fewer components using the Principal Component Analysis (PCA) method. Then, we select the most features who have important information for classification cancer. This paper focuses on the comparison of using and without the PCA method on cancer data coupled with the Fuzzy Support Vectors Machines (FSVM) method for cancer classification. The experimental results, without the PCA method on cancer data coupled with the FSVM method for cancer classification the accuracy is 87.69 % and by using the PCA method on cancer data coupled with the FSVM method for cancer classification the accuracy is 96.92 % (obtained by using 60 features).
Mathematics model of measles and rubella with vaccination
Authors: Amelia D , Tasman H 
Published: January 2021

Abstract
Measles and rubella are two contagious diseases in human population which are caused by viruses. Measles and rubella can be prevented by vaccination. In this article, a mathematical model of the spread of measles and rubella with vaccination was constructed and analyzed. The population was divided into 9 classes. It was obtained four equilibrium points, these were the disease-free equilibrium point, the measles-free equilibrium point, the rubella-free equilibrium point, and the endemic equilibrium point. There were two basic reproduction numbers, corresponding to spread of measles and rubella. These numbers correspond to the stability of the equilibrium points. Numerical simulation is done to see the dynamics of population and to confirm the analytical result.
Predicting risk factors for postoperative coronary artery bypass grafting using logistic regression and CHAID
Authors: Nabilah A , Lestari D , Mardiyati S , Devila S 
Published: January 2021

Abstract
Non-fatal postoperative complications are postoperative morbidity that can affect the patient’s functional status and quality of life. Evaluation of postoperative morbidity is the step needed to assess and improve the quality of patient care. Therefore, a method is required in order to predict risk factors in evaluating a patient’s postoperative morbidity. After this the results will be used to determine the insurance premiums. In this research, the Logistic Regression are used to know the risk factors that would occur in patients who had undergone Coronary Artery Bypass Grafting (CABG) surgery. Then we use the CHAID method to classify readmission based on patient characteristics. Based on the two analyzes, it can be concluded that the CHAID analysis supports the Logistics analysis, there are two risk factors significantly influence the complications of patients after Coronary Artery Bypass Graft (CABG), namely Sex and Ejection Fraction.
Multivariate Bühlmann-Straub credibility model for claim reserving
Authors: Winarta V T , Novita M , Nurrohmah S 
Published: January 2021

Abstract
One of the approaches that is used for claim reserving in insurance companies is credibility theory, which allows claim reserving by combining claim payment data with other information. In this paper, the Bühlmann-Straub credibility model is used. Furthermore, in general, claim reserving in a company is done by calculating the claim reserve in each line of business (LoB) in the company, then the total claim reserve for the company (aggregate reserve) is obtained by adding up the claim reserve in each LoB. Considering the possibility that there is correlation between the existing LoBs, the value of aggregate reserve can actually be less than the sum of the claim reserve in each of the existing LoB. Therefore, research on the claim reserving then evolves by considering claim payment data from various LoBs in a company, or also called claim reserving in multivariate context. In this paper, a research is conducted on the development of multivariate Bühlmann-Straub credibility model for claim reserving along with estimation for model’s parameters. The model is used to calculate claim reserve for three LoBs of insurance company in United State, based on the data of claim amount during the period of 2008-2017 that was published by Association of Insurance Commisioners of the United State. It appears that the error of multivariate Bühlmann-Straub credibility model is lower than the error of standard Bühlmann-Straub credibility model.
Identification of factors associated with hypothyroidism due to radiotherapy in patients with nasopharyngeal cancer (Case study of nasopharyngeal cancer in one of the hospitals in Jakarta)
Authors: Lestari D A , Abdullah S , Rachman A 
Published: January 2021

Abstract
Nasopharyngeal cancer is an abnormal cell growth that develops around the nasopharynx. Treatment of nasopharyngeal cancer patients includes chemotherapy or radiotherapy. Both treatments have side effects in patients. In this study, we will focus on hypothyroidism as a side effect of radiotherapy in the treatment of patients with nasopharyngeal cancer. Hypothyroidism is a condition when the thyroid gland is unable to produce enough thyroid hormone. The main goal of this study is to identify the factors associated with hypothyroidism. To achieve this goal, classification tree and logistic regression methods will be used. Classification tree is used to obtain important variables in the classification of subject classes. Then, logistic regression is used to quantify the risk of variables that appear in the classification tree, hypothyroidism risk factors, and hypothyroidism marker factors. Based on the analysis, it was found that the factors associated in this study were variable symptom, physical sign, smoking habits, gender, age, BMI (Body Mass Index), TSH (Thyroid Stimulating Hormone) and fT4 (free thyroxine) hormones, and also all items on Zulewski score, except items delayed ankle reflex and slow movements. These factors associated tended to increase the risk of hypothyroidism, except for the fT4 hormone and BMI.
Comparing factors which affect Visceral Fat Area (VFA) for male and female weight management X participants with chow method and meta regression
Authors: Delmiana B , Setiadi R , Widyaningsih Y 
Published: January 2021

Abstract
The spread of fat in human’s body divided into two parts. The first is subcutaneous fat area and the second is visceral fat area (VFA). The largest fat deposit in human’s body is in the subcutaneous area. This fat is called body fat, while the remains of fat in human’s body is located in visceral area inside abdominal cavity and chest cavity. VFA is a dangerous fat, so this study proposes multiple linear regression models to know how to control VFA level more precisely based on body mass index (BMI), basal metabolic rate (BMR), chronological age, biological age, body fat, and skeletal muscle variables. There is presumption that VFA level and other variables that are considered in weight management are different between male and female, so the regression models for male and female groups are built separately. The Chow test is performed to test the similarity of both regression models for male and female groups. If both regression models for male and female groups are same, the combined regression model will be built for male and female groups which can explain the control of VFA level to relate variables in both male and female.
Clustering analysis of senior high school in West Java based on educational facilities
Authors: Putri M A , Abdullah S 
Published: January 2021

Abstract
The problem of education in senior high school remains. One of the roots of the problem is the lack of educational facilities. The government has responded to this case by giving the state budget (APBN) for education. Nevertheless, the large number of senior high schools in Indonesia is one of the barriers to efficient distribution of APBN funds. Thus, clustering analysis of senior high school facilities in Indonesia especially in West Java is expected to be a solution. The number of observations is 13,486 with nine categorical variables recorded on a website of the Ministry of Education and Culture in August 2019. The method used is Robust Clustering Using Link (ROCK). To get a clearer profile of the clusters, we used ROCK method modified with Nested Clustering. The results of this study indicate that 14 clusters were formed and have their profiles. Cluster 3 is a relatively good cluster while cluster 1a is a relatively poor cluster. Clusters representing poor facilities were found to be dominant in West Java Province.
Community structure of tree at three location points of Ciliwung riparian zone in Depok–South Jakarta
Authors: Pratiwi A D , Wardhana W , Putrika A 
Published: January 2021

Abstract
Rapid urban development leads to changes of vegetation community structure in the riparian zone. Research on tree community structure has been done at 3 location points of Ciliwung riparian zone in Depok–South Jakarta with different habitat condition. Habitat at location 1 is known to be natural, habitat at location 2 has undergone land use conversion, and habitat at location 3 has undergone river bank concretization. This study aimed to compare tree community structure in the 3 locations. We used plot method for data sampling. A total of 4 plots at each location with size of 20x20 m were determined purposively. The results showed that the 3 locations showed differences in the tree community structure. Compositions of tree at location 1, 2, and 3 respectively consists of 11 species in 8 families, 14 species in 10 families, and 4 species in 4 families. Overall, all three locations have low to moderate level of tree diversity (H’ 1.26–2.3) and high level of tree evenness (E 0.81–0.90). Based on Importance Value (IVi), location 1, 2, and 3 respectively are dominated by species of Cecropia peltata (85.12 %), Paraserianthes falcataria (142.40 %), and Leucaena leucocephala (105.94 %).
Effective concentration of Water Hyacinth (Eichhornia crassipes) and Corncob (Zea mays) as a growth medium for the development of Sludge Worm (Tubifex spp.)
Authors: Safitri S D , Khaerunnisa S , Ikhsan C , Purwanti D , Lestari R 
Published: January 2021

Abstract
Feeds with high protein characteristics and relatively small size are needed to support the growth of fish seeds. One source of feed that meets these criteria is sludge worm. Water hyacinth and corncobs are waste in the community. The mixture of these two ingredients contains organic material that is able to provide nutrients for the growth of sludge worms. This study aims to optimize the development of sludge worm cultivation media based on water hyacinth and corncobs as raw material. Sludge worms are cultured with recirculation system with 3 design combination treatment variation of water hyacinth and fermented corncob. Those 3 design are 15 % water hyacinth and 5 % corncob (treatment I), 10 % for both of water hyacinth and corncob (treatment II), and the last is 5 % water hyacinth with 15 % corncob (treatment III). The parameters measured in this study were water quality and dissolved oxygen. Treatment I and treatment II present good results as potential sludge worms cultivation media.
Estimation of carbon stocks from tree stands vegetation in Universitas Indonesia’s urban forest, Depok
Authors: Febiriyanti A , Pradana D H , Putrika A 
Published: January 2021

Abstract
Urban forest has a function as CO2 emissions absorbers derived from human activities around the city. Universitas Indonesia (UI) Urban’s Forest is one of the Urban Forest which has potential carbon stocks. A study has been conducted to analyze the potential of carbon stocks and tree stands that have the highest carbon stock in UI Urban’s Forest. Tree stands are woody vegetation with a diameter ≥ 20 cm. The research was conducted in October-November 2017 in UI Urban’s Forest area covering three locations, west Wallace, east Wallace, and natural vegetation. Method of collecting data of vegetation was done by nondestructive sampling by measuring Breast Height Diameter (DBH). Data processing uses allometric equations with the specific wood density of each tree species. Results showed that the potential of carbon stocks in UI Urban’s Forest is 468.02 ton/ha with west Wallace, east Wallace, and natural vegetation are 138.62 ton/ha, 162.75 ton/ha, and 182.64 ton/ha. Overall, potential carbon stocks in UI Urban’s Forest is 11752.48 ton/ha. Species of trees with the highest potential of carbon stocks is Delonix regia.
Microplastic in mangrove horn snail Telescopium telescopium (Linnaeus, 1758) at mangrove ecosystem, Rambut Island, Jakarta Bay, Indonesia
Authors: Putri F T , Patria M P 
Published: January 2021

Abstract
This study was done to identify the type and amount of microplastic particle in the sediment, water and the horn snail Telescopium telescopium (soft tissue, respiratory and digestive organs) in the coast of Rambut Island, Jakarta. This research also aimed to know the correlation between the amount of microplastic particles in the sediment and the snail body mass. The result showed that average amount of microplastic were found 764.81 particles/ind in the snail, 31.7 particles/g in sediment and 15.46 particles/mL water samples. The microplastic type of film was dominant in all of the samples, with average amount 368.51 particles/ind in snail, 15 particles/g sediment and 9.46 particles/mL water samples, respectively. The respiratory organ contained higher microplastics (102.33 particles/ind) than the digestive organ (66.85 particles/ind). There were significantly positive correlation (r=0.744) between amount of microplastics in the snail and the snail body mass.
Poles carbon stock estimation of urban forest in Universitas Indonesia, Depok
Authors: Salsabillah S H , Pradana D H , Putrika A 
Published: January 2021

Abstract
The study of carbon stock estimation on pole vegetation was done in the urban forest of Universitas Indonesia, Depok. The aims of this study were to estimate the carbon stock of pole stage in Urban Forest of Universitas Indonesia, which were divided into three zones: West Wallace, East Wallace and natural vegetation. In addition, this study was conducted to determine species in pole stage that hold the largest carbon stock. The research was conducted in August-December 2017 using a non-destructive method. The carbon stock value obtained from the biomass calculation based on pole’s diameter at breast height (DBH). We measured the DBH of pole stage on 75 plots of 10 x 10 m2 which was divided to 3 zones, 25 plots each. The biomass calculation was done using an allometric equation B = 0.11 ρ D (2+0.62). The allometric equation used wood density of each species found. The average of carbon stock value in Urban Forest of Universitas Indonesia is 11.505 ton/ha, with East Wallace have the largest carbon stock of 17.262 ton/ha and natural vegetation have the smallest carbon stock 6.876 ton/ha. Species of pole stage with largest average carbon stock in Urban Forest UI is Hopea sp. (Merawan) with 0.327 ton/ha.