bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Text Data Compression Using Yamamoto Recursive Codes and Punctured Elias Codes
Authors: Hardi S M , Putra M R , Tarigan J T , Jaya I
Published: July 2020

This research aims to study the efficiency of two variants of variable-length codes (i.e., Yamamoto Recursive codes and Punctured Elias codes) in compressing texts. The parameter being examined are the ratio of compression, the space savings, and the bit rate. As a benchmark, all of the original (uncompressed) texts are assumed to be encoded in American Standard Codes for Information Interchange (ASCII). The overall result shows that the Punctured Elias codes are consistently more efficient to compress texts than Yamamoto Recursive codes.
Analysis of Deep Learning Cyclical order for Prediction of Fresh Milk Production in Sumatera
Authors: Saefullah Asep , Hendri Muhammad , Lindawati Sri , Badaruddin Muliati , Hutahaean Jeperson
Published: July 2020

Milk is one of the most preferred and most easily absorbed nutrients. This drink naturally contains important nutrients, such as vitamins A, D, B12, protein, calcium, magnesium, phosphorus, and zinc, and others. Milk is also beneficial for children and adults. Starting from maintaining healthy bones and teeth, as a source of energy, and so on. In Indonesia, especially on the island of Sumatra, fresh milk production is carried out by cattle and goat farmers in cooperation with milk companies. This research have a purpose is to predict the production of fresh milk on the island of Sumatra so that the local government, as well as cattle and goat breeders on the island of Sumatra, have benchmarks to further increase the production of fresh milk in their respective regions in the future. The method that will be used in this research is Deep Learning Cyclical order which is the development of ANN. The research data used were data on the production of fresh milk on the island of Sumatra in 2009-2018 sourced from the Indonesian Statistics Agency. This research will be analyzed using 3 network architecture models, namely 4-5-1, 4-10-1 and 4-5-10-1 with the best network model chosen is 4-5-10-1 with an accuracy level of 90% and MSE value of 0.0157179042. Based on this best model a prediction of fresh milk production in Sumatra will be carried out in 2019-2020.
An Online Collaborative Mind Mapping Feature on Student-Centered E-Learning Environment
Authors: Hakim H , Santoso H B , Junus K
Published: July 2020

The Faculty of Computer Science of Universitas Indonesia has implemented online learning facilitated by a learning management system called Student-Centered E-Learning Environment (SCeLE). One of its important features is the online discussion board that enables students to construct knowledge collaboratively. Connecting and comparing several ideas in an online discussion forum are challenging for both students and teachers, especially when the discussion runs very fast with long messages. This study proposes an online collaborative mind mapping feature integrated to the discussion forum. A prototype was developed using the Go programming language and Gin web framework. The usability testing was employed to gather data about user experience in using the application. The participants of the study were all students of the Faculty of Computer Science of Universitas Indonesia. The result of the study shows that the application benefits most of the users. The participants acknowledged that the features help them follow the discussion and it supports the collaborative work. However, in terms of the design and the user experience, more works are required to improve the feature needs.
Improving The Performance of K-Nearest Neighbor Algorithm by Reducing The Attributes of Dataset Using Gain Ratio
Authors: Hasdyna N , Sianipar B , Zamzami E M
Published: July 2020

Data that has many attributes or higher dimensions will affect the performance of the K-NN classification algorithm. In this study, the Gain Ratio implemented for selecting and reducing the dataset attributes to form a new dataset for the classification process is carried out with the K-NN. The dataset used in this study are the Breast Cancer Coimbra dataset and Hepatitis C Virus dataset obtained from the UCI Machine Learning Repository. The results showed that the Breast Cancer Coimbra dataset, Gain Ratio can improve the performance of K-NN with average value 0.535596 TPR, TNR = 1, NPV = 0.608279, FNR = 1, FOR = 0.391721, Accuracy = 72.85%. In Hepatitis C Virus dataset also managed to improve the performance of K-NN with average value TPR = 0.665596, TNR = 0,876667, NPV=0,738279, FNR=0,88, FOR=0,521721, and Accuracy=86,25%.
Decision Support System to Determine Uang Kuliah Tunggal (UKT) by Combining Naïve Bayes Classifier and Fuzzy-TOPSIS
Authors: Mauladi  , Utomo P E P , Hutabarat B F , Putra R A
Published: July 2020

Uang Kuliah Tunggal (UKT) is a portion of the single tuition fee that is borne by each undergraduate student at a state university in Indonesia. UKT is the number of fees that have to be paid by students in each semester. Basically, UKT is implemented to impose tuition fees according to the income and the condition of students’ families. However, there is an issue in regard to the inappropriate classification of UKT. This issue is caused by several factors such as manual method is still used in determining UKT Classes and there is likely an element of subjectivity in determining UKT Classes of new students. Based on these issues, a decision support system that can determine UKT Class of new students is needed. The Naïve Bayes Classifier (NBC) method is used to classify data into eight UKT Classes. Whereas Fuzzy-TOPSIS is used in the optimization selection process of UKT Class 1 to 8. This method was chosen for its capability in choosing the best alternative out of several possibilities, in this case, the intended alternative is the most suitable new student to be selected in UKT Class based on six predetermined criteria. Research results show that the NBC Model can identify UKT groups of students with mean values of precision and recall testing are 77.8% and 77.8% and the model accuracy is 77.8% as well. In optimization selection process of UKT using Fuzzy-TOPSIS results obtained the percentage of UKT 1 group recommendations was 5.33%, UKT 2 was 5.33%, UKT 3 was 10.22%, UKT 4 was 24.89%, UKT 5 was 24.89%, UKT 6 was 10.22%, UKT 7 was 10.22% and UKT 8 was 8.00%. Based on the results above, it can be concluded that the combination of Naïve Bayes Classifier and Fuzzy-TOPSIS can be implemented for determining the UKT Classes. Then the recommendations of the UKT Classes can be considered in determining the UKT Classes of students for the Decision-maker.
A Meta-Review of the Smartphone as the Measurement Device
Authors: Hantono B S , Nugroho L E , Santosa P I , Musaddiq R
Published: July 2020

With the development of increasingly affordable smartphone technology that is owned by almost everyone, making some activities can be done only by using this device. Smartphone computing capability that is quite powerful, accompanied by various sensors embedded in it, allows the smartphone to be used as a measurement device in various fields of research. This article tries to review the use of smartphones as a measure of one’s mentality by conducting a meta-review of several review articles that have been done before. This article tries to look at research trends that measure a person’s mental state by using sensors found on smartphones and also to help researchers decide on topics to explore.
RETRACTED: Performance of news clustering using ant colony optimization
Authors: Jenson T , Girsang A S
Published: July 2020

Humans are basically curious creatures. We always look for all the latest information through books or news. News usually contains tags or categories to make it easier to find similar news. It can be done manually by a human or with a machine to make it easier. Data mining techniques such as clustering and classification can be used to help the categorization process. Clustering is a technique that can be used to grouped news based on their similarity. There is some algorithm that can be used to clustering data. One of them is Ant Colony Optimization (ACO). ACO is a metaheuristic algorithm that mimics how ants bring food to the colony. ACO also can be used to solve the clustering problem. In this paper, we will use the ACO version for clustering to cluster news and find the performance of the said method. Then we compare the result with ground truth.
Web Based Application for Controlling Data Quality in Phenotype Prediction of Indonesian Rice Genomes
Authors: Nababan E B , Nurhasanah R , Huzaifah A S
Published: July 2020

Single Nucleotide Polymorphism (SNP) is a form of Deoxyribonucleic Acid (DNA) variation that can be used in predicting phenotypes. Data quality control is a crucial stage in the process of detecting phenotypes using SNP data. In this study, we built a web-based application to carry out the SNP data quality control function. Raw SNP data in string type are filtered by calculating the missing rate, minor allele frequency, and Hardy-Weinberg Equilibrium values. The result is SNP data that has been filtered in numeric form, namely the value 1 represents dominant homozygous, 2 represents heterozygous and 3 represents homozygous recessive. SNP encoding in numerical form aims to make SNP data can be processed into machine learning for the further phenotype prediction step.
Bigdata Clustering using X-means method with Euclidean Distance
Authors: Zendrato N , Dhany H W , Siagian N A , Izhari F
Published: July 2020

Centroid is the central point of data in the grouping process, it is necessary to analyze the centroid in determining the initial value in the initial clustering process. So it is used as a cluster center point in the X-Means algorithm clustering process. Determine cluster center points or centroid, measure the performance of the X-Means algorithm with range cluster parameters by measuring distances between centroid for a fast and efficient way to group unstructured data, and to speed up the model construction process and divide several centroid in half to match the data as a test tool for the analysis of the X-Means method. From testing using the X-Means algorithm with the determination of the number of Centroid clusters carried out by modifying the X-Means method to do some determination of the centroid to get the results of 11 iterations. From the results of these tests produce good cluster members the level of similarity of data with other data and in determining the number of clusters, using the modification of the Euclidean distance method, get better results of the similarity level of each member compared to randomly determining the number of clusters with several iterations.
Embedded System for Detecting Cigarette Smoke Indoors using STM32 Microcontroller
Authors: Nasution T H , Zarlis M
Published: July 2020

In everyday life, smokers are often found around us. As we know, a lot of losses caused by cigarette smoke and cigarette smoke itself can also disturb the people around us. In order not to disturb the health of others, there are restrictions in certain rooms for smoking by giving a sign that smoking is prohibited. But some people sometimes ignore the ban. In this study, our system was embedded to give warnings to people who smoke in rooms that cannot smoke. The system will sound the siren if smoke is detected. This system is designed using a STM32 microcontroller and MQ-2 sensor to detect cigarette smoke. From the results of testing the system will work well by directly giving a signal when there is cigarette smoke.
Security of Image File with Tiny Encryption Algorithm And Modified Significant Bit Pseudo Random Number Generator
Authors: Hardi S M , Syah Ramadhani R , Muisa Zamzami E. , Tarigan JT , Jaya I
Published: July 2020

One of the negative impacts of the development of the era of digital technology on communication media today is the damage and loss of information data. Access to communication media is a means of delivering information that is vulnerable to manipulation. Therefore, cryptography is used to keep the information confidential. Cryptography is an art in encoding messages into other forms so that the message cannot be read by unauthorized parties. Tiny Encryption Algorithm (TEA) algorithm is a symmetric cryptographic algorithm in which the key is divided into four subsections and uses 128 key bits and operates 64 bits of data blocks and then divided into two blocks into 32 bits during the encryption process. In order to make the encryption stronger, it is combined with steganography where the steganography method used is Least Significant Bit (LSB) which has the function of inserting data into the last bit of other data. Linear Congruential Generator (LCG) is a random number generator in the LSB method where its function is as a flow of inputting data that has been encrypted randomly into another data as a cover so that the combination of these methods becomes Modified Least Significant Bit Pseudo Random Number Generator. The combination of cryptography and steganography is able to create a security in sending a confidential message to be safer.
Exploring the Pattern of Voters’ Characteristics: Partial Least Square Analysis
Authors: Lubis Muharman , Ridho Lubis Arif , Almaarif Ahmad
Published: July 2020

Understanding of characteristics can be assessed either by public decision-makers, who have been the primary concern of political actors or by voters themselves, who have participated directly in the process of election. Therefore, this study focused on the voters’ self-evaluation to look out on the voter decisions with survey questionnaire have been used as the tools to collect the data independently in relation to create formative measurement model. In addition, major influences to the public also involves the role of emotion, political socialization and tolerance to the diversity of media views. This study investigated gender-based patterns of 790 samples using PLS as a data analysis tool, which found interesting result, which suggested that Social Norm (SNorm) have strongest effect to both PCon and PBen with 0.179 and 0.066 respectively followed by Technology Solution (TSol) with 0.057 and 0.022 as well Legal Regulation (LReg) with 0.043 and 0.020 accordingly. Thus, in the developed model, the researcher recommend that social factors can lead to determination of demand and participation in the voting to have public confidence and good behaviour in the protective manner.
Chaos-based Cryptography: A Brief Look Into An Alternate Approach to Data Security
Authors: Sharif Amer , Intan Raihana Nur , Samsudin Azman
Published: July 2020

The present scale of computing inevitably demanded increased level of data security, which is the concern of cryptography. Security of the cipher depends on the strength of the key and the algorithm used to generate the keys. Many modern cryptographic algorithms are based on Number Theory, but in recent years an alternative approach has been studied which is based on Chaos Theory. Many properties of chaotic systems such as nonlinearity, randomness, and sensitivity to initial conditions bear resemblance to those required by cryptography such as diffusion and confusion. Implementations of chaos-based cryptosystems have been proposed by other researchers and yet the strength of these systems from a cryptographic point of view has not been thoroughly considered. This paper discusses the appeal of chaos-based cryptography, some of the researches already done, and the challenges that this approach faces to be established as a fully secure method for data security.
Relationship of Personal Data Protection towards the Electoral Measures: Partial Least Square Analysis
Authors: Lubis Muharman , Ridho Lubis Arif , Almaarif Ahmad , Amalia Nur Fajrillah Asti
Published: July 2020

The adoption of e-voting in several countries poses certain challenges, which are very similar when electronic means are applied to any activities, such as e-governance or e-commerce. Therefore, some people due to economics, politics or social reasons expect the e-voting use will facilitate and solve previous election’s problem. Unfortunately, the most complex and difficult practical implementation with distinct problems depends on the particular condition or culture. One of essential factor concerning the adoption related to privacy protection. Thus, this study examines the relationship of perceived benefit and privacy concern towards personal data protection by establishing model of formative measurement. For the generalization purposes, a survey questionnaire consists of 4 categories of 45 items was distributed offline and online to approximately 800 people with purposive sampling in selected multicultural cities in Indonesia. The result suggested that the Perceived Benefit (PBen) has the strongest predictive value of ƒ2 and Q2 compare to Privacy Concern (PCon) with 0.212 and 0.083 respectively.
Comparative Analysis of Inter-Centroid K-Means Performance using Euclidean Distance, Canberra Distance and Manhattan Distance
Authors: Faisal M , Zamzami E M , Sutarman
Published: July 2020

Clustering is a method needed to group data or objects based on the required level between data, K-means is one of the clustering methods used that can be used easily in its implementation, there are some additions to this method according to the data center and on the weighting of the distance between data, the weighting of the distance between data on K-Means traditionally can be done using Euclidean Distance, Canberra Distance and Manhattan Distance, making this an analysis of the accuracy generated from the method produced by a combination of the Z-score and Min-Max Normalization methods, and is carried out Cluster homogeneity test using the Silhouette Coefficient method. The results of this method show that the Canberra method is superior to Euclidean and Manhattan on Iris dataset and the Canberra combination method with Z-score and Min-Max can increase the value on the glass without using the Normalization Method 37. 44% to 67.46% use the Z-score and 56.52% use Min-Max and use an increase in the average value of the Silhouette Coefficient.
Exercising the Students Computational Thinking Ability using Bebras Challenge
Authors: Zamzami E M , Tarigan J T , Zendrato N , Muis A , Yoga A P , Faisal M
Published: July 2020

In this paper, we present our observation regarding the student’s computational thinking skill in the region of Sumatera Utara, Indonesia. The observation is based on the result of Bebras Indonesia 2019, a computer-based countrywide test on computational thinking aimed at students in primary school, middle school, and high school. We collected the data in a specific targeted region (the province of Sumatera Utara), collects additional data from the participant’s school, and analyse the data. Our objective is to find a pattern between the schools’ approach, if any, regarding topics related to computation thinking to the ability of students to actually solve the problem based on their score in the test.
End-to-end indonesian speech recognition with convolutional and gated recurrent units
Authors: Adiwidjaja Rifqi , Ivan Fanany M
Published: July 2020

Automatic Speech Recognition has penetrated deeply into our life. For well-resourced language, it can be considered as solved, but that’s not the case for under-resourced language like Bahasa. Although it’s the 7th most spoken language in the world, the research of speech recognition for Bahasa was still extremely limited, with setting still inconvenient for the real world and industry. This research is an attempt to make a speech recognition model that has applicability to the real world and industry, specifically that supports sentence level input with variable character length with end-to-end training. We built the model using the deep learning approach, specifically utilizing the residual networks and Bi-Directional Gated Recurrent Unit (Bi-GRU). To the best of our knowledge, this is the first Indonesian ASR model that can be trained in an end-to-end manner. Our model surpassed the baseline model on all metrics and achieve competitiveness with the current best result, which used the visual modal, for the dataset even with a more difficult and prone to noise modality like sound.
A Latent Semantic Analysis Method for Automatic Scoring System at Essay Test
Authors: Handayani L , Alika W O , Negara B S , Febiyanto
Published: July 2020

An essay test is the type of test that requires students’ skills to propose, arrange, and combine the ideas they have from the teaching-learning process conducted. The essay answers in the form of description cause the examination becomes more complicated compared to an objective multiple-choice test. Therefore, in this research, the scoring system is built for an essay test by Using Latent Semantic Analysis that can pay attention to the word synonym of the key answer on the students’ answer. The highest accuracy from the test that had been conducted at the essay scoring system by Using Latent Semantic Analysis was 84.35%, categorized into good.
Genetic Algorithm in Image Inserting with Modified Least Significant Bit Method to Find The Best MSE Value
Authors: Ramadhan S F , Sihombing P , Sutarman
Published: July 2020

Inserting data into digital media tends to change the large size of the media cover file, this is because the inserted pixel has a different size from the insertion value, i.e. with a larger or smaller value, for example a pixel value of 10 is inserted with larger or smaller data from the value 10. So that the pixel value is getting further from the value of 10, this causes the value of Mean Squared Error (MSE) of the media of the cover (cover) to become larger. In this study, the selection of pixels in the image is in accordance with the value of the insertion data as the insertion place with the Genetic algorithm (GA). Insertion of data on selected pixels using the GA algorithm is performed using the Modified Least Significant Bit (MLSB) algorithm at the position of the least significant bits. To find out the reliability of the proposed algorithm, the data insertion experiment was carried out by comparing the conventional LSB algorithm with the proposed algorithm where the results obtained a significant MSE value, i.e. the average MSE value of the LSB algorithm was 20.54 and the proposed algorithm was 7.12.
Optimization DataTransfer Using the Neural Network method Based on Signal Level
Authors: Zendrato Niskarto , Zarlis M. , Salim Sitompul Opim , Muisa Zamzami Elviawaty
Published: July 2020

The use of the internet that is very high at this time in all fields requires continuous development to improve the quality of data transfer. By improving the quality of data transfer, all activities that use the internet for transactions can run well. Good data transfer is influenced by speed, while speed is influenced by strength. There are several things that affect the data transfer process, but this research only focuses on speed and signal. Neural Network algorithm is used to determine the optimal point of the signal, where the optimal signal point is the maximum data transfer rate. This algorithm can be used to determine the optimal point with an accuracy rate of 10%
Performance Improvement of Clustering Affinity Propagation Method using Principal Component Analysis
Authors: Simanullang Jasael , Zarlis Muhammad , Muisa Zamzami Elviawaty
Published: July 2020

Affinity Propagation Method it is necessary to modify the algorithm by using Principal Component Analysis (PCA). PCA method is used to reduce the attributes or characteristics that are less influential on the data so that the most influential attributes are obtained to then be carried out the clustering process with Affinity Propagation. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when there are 8 optimal cluster clusters. While the performance of conventional clustering models produces an optimal number of clusters from 14 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Air Quality dataset because it produces an optimal number of clusters and iterations of 8 clusters. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when the optimal number of clusters is 5 clusters. While the performance of conventional clustering models produces a suboptimal number of 10 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Water Quality Status dataset because it produces an optimal number of clusters and 5 cluster repetitions.
Counter-propagation Neural Network for Brain Tumor Classification
Authors: Rahmat R F , Harahap Y T A , Rachmawati D
Published: July 2020

Brain tumor is a condition in which abnormal cells grow unnaturally in the brain. Depending on the size and type, the abnormal cells called tumors can be life-threatening if the patient does not take immediate treatment. The cause of tumor growth in the brain is the presence of risk factors such as family history and ionization radiation. Patients with brain tumors will experience several symptoms of a headache, nausea, memory loss, and changes in vision, speech, and hearing. Detection of brain tumors can be performed with the help of the medical device of Magnetic Resonance Imaging (MRI) Scan. Through the image of MRI Scan results, radiology specialists will interpret and analyze the brain condition. However, analysis and conclusions for this matter take a long period of time. Therefore, a method is required to classify the brain tumors through MRI images automatically. The method used in this research is Counter-propagation Neural Network. Prior to classification, the brain’s MRI image will be used as the input for the image pre-processing stage then go through the segmentation and feature extraction processes. Based on the test, it can be concluded that the proposed method can identify brain tumors with an accuracy of 92.5%.
Classification of Infection Type Based on Leukocytes Examination Results Using K-Nearest Neighbor
Authors: Suyanto S A N , Siregar B , Nababan E B , Fikri H A
Published: July 2020

Leukocytes are blood cells that contain nuclei, also called white blood cells. Leukocytes have a role in the cellular and humoral defiance of organisms against foreign substances. Laboratory tests of blood samples greatly influence the diagnosis of a disease. Manual blood tests do have a low price but still have some weaknesses such as the length of time needed will be longer, because health practitioners must examine them carefully to avoid misinformation. To help overcome these weaknesses, a classification of types of infections was carried out based on the results of leukocyte examination. Classification is a grouping of data where the data used has a label or target class. So that the algorithms for solving classification problems are categorized into supervised learning. The purpose of supervised learning is that label data or targets play a role as a ‘supervisor’ or ‘teacher’ who oversees the learning process in achieving a certain level of accuracy or precision. The algorithm used in this study is K-Nearest Neighbour. The data used in this study as many as 2,098 results of complete blood tests taken from one hospital in Medan. This study resulted in a classification accuracy of 92%.
Descriptions of reservoir basin subsurface structure in UNNES based on microgravity data
Authors: Supriyadi S , Khumaedi K , Setiawan F , Yani M , Mukromin T M
Published: July 2020

UNNES reservoir basin as a characteristic of the Conservation University is around 12 years old. This relatively long span of time has never been carried out a physical study of a subsurface structure. This study aims to describe the subsurface layer based on gravity data. The method used is to use gravity by calculating the elevation of each measuring point and by tidal correction and drift correction. Both of these corrections are to reduce the tidal and fatigue effects of the gravimeter. Measurements were done in July 2019 (dry season). The results of the study based on observational gravity data indicate that the value of a large gravity is in the north-south part and the smallest value is in the west part of the reservoir basin. The structure of the first layer which has an average density of 2.7 g/cm3 thick 75 m below the surface. The second layer is dominated by andesite rock with an average rock density of 2.8 g/cm3 thick 50 m below the first layer. While the lowest layer is a layer dominated by basalt rock with an average rock density of 3.1 g/cm3 thick more than 40 m below second layer.
Influence of annealing duration on structural, optical and electrical properties of AZO thin films grown on corning glass by dc magnetron sputtering
Authors: Sugianto S , Astuti B , Marwoto P , Firmahaya N A , Aryanto D , Isnaeni
Published: July 2020

Al doped ZnO (AZO) thin films were deposited using dc magnetron sputtering on corning glass substrate has successfully done. After deposition, the samples were annealed in vacuum ambient at temperature of 300 °C with variation in annealing duration of 0, 30, and 50 minutes, respectively. The structural, optical and electrical properties of these films have been investigated as a function of annealing duration. Thin films were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-Vis spectrometer and I-V measurements. AZO thin films without annealing treatment was showed amorphous structure. However, after annealed at 30 and 50 minutes, the films obtained were polycrystalline with a hexagonal wurtzite structure and preferred orientation in the (002) plane. Average optical transmittance of the AZO thin films was over 85%. In Addition, the electrical resistivity is reduced from 1.85 × 106 Ωcm to 1.93 × 102 Ωcm when applying annealing treatment. It’s can be concluded, the annealing treatment in vacuum ambient was improved the crystallinity and simultaneously improved optical and electrical properties of AZO films.
X-ray diffraction studies of ZnO:Cu thin films prepared using sol-gel method
Authors: Astuti B , Zhafirah A , Carieta V A , Hamid N , Marwoto P , Sugianto  , Nurbaiti U , Ratnasari F D , Putra N M D , Aryanto D
Published: July 2020

ZnO:Cu thin films were deposited on corning glass substrate using sol gel method with different concentration of Cu (0, 1, 3, and 5%) has been done. The effect of the different Cu concentration on the structural properties of these films was studied in detail. Based on the XRD result, the ZnO thin films undoped and doped Cu are polycrystalline with hexagonal wurtzite structure and has preferred orientation is c-axis. All peaks of ZnO thin films undoped and doped Cu shows that reflection peaks associated with (100),(002) and (110) planes. The film quality was improved with the increasing of the Cu concentration. The value of the lattice constant a and c was found to be increased with increases of the Cu concentration. Changes in the lattice constant affect the bond length of ZnO (L) and the volume of one hexagonal system unit (V). The lattice parameter also affects to the crystallite size. The crystallite size was increased with Increasing of the Cu concentration and the lattice parameter. Furthermore, the strain value of the film decreases with increases of the Cu concentration. Lattice strain that has decreased is due to the cavity around of the formed film. Cavities between atoms also affect the density of the dislocation. The larger cavity between atoms on the films that makes the dislocation density becomes smaller.
Identification of subsurface layer in UNNES reservoir basin
Authors: Supriyadi S , Khumaedi K , Mukromin T M , Yani M , Setiawan F
Published: July 2020

Reservoir basin is one of the important components in water conservation which is very supportive in Green Campus activities. The importance of information on the sub-surface layer surrounding the reservoir basin is the first step in managing and empowering the location. The purpose of this research is to identify the subsurface layers in the UNNES reservoir basin. The method used in this research is the resistivity geoelectric method with the Wenner configuration. Measured track totaling three which is located on the side of the UNNES reservoir basin with a track length of 75 m. The results of the identification of the subsurface layer get four layers, namely the layer of tuff sand/water with a value of 1.22 - 2.79 Ωm, a layer of clay with a value of 6.41 - 14.7 Ωm, a layer of sand / gravel with a value of 33, 7 - 77.3 Ωm and lava flow / breccia flow with a value of 77.4 - 177 Ωm.
Quantum oscillators model to derive an ideal gas in Bose-Einstein condensates under gravitation of earth
Authors: Prayitno T B
Published: July 2020

Considering a set of condensates as N indistinguishable noninteracting quantum oscillators and replacing an available volume with a harmonic volume, we derived an ideal gas model by applying the canonical partition function via the thermodynamic relation. In this case, we take a longitudinal part of the three-dimensional Gross-Pitaevskii equation in which the effect of gravitation of earth works. Since we used the time-independent perturbation theory, to include gravity effect, we must put the higher coefficient in the formulation of each energy state whose value is determined by the separated amplitude formula in each state. It will also be shown that even though the equation of state represents an ideal gas, the appropriate heat capacity approaches Einstein’s solid-like model if the certain conditions are employed.
Development of teaching materials for momentum assisted by scratch: building the pre-service teacher’s skills for 21st century and industry revolution
Authors: Rusilowati A , Subali B , Aji M P , Negoro R A
Published: July 2020

Learning physics problems still appear in many parts of the world. Along with this, the development of civilization demands the development of education to produce the skills that are the ultimate in every human being. 21st Century skills are skills that are relevant to the demands of the development of civilization. Pre-service Teacher needs to be prepared to overcome the problems of learning Physics by following with the times. This study aims to develop a skill-oriented Momentum teaching material of the 21st Century and the industrial revolution. This research is development research with stages: 1) Analysis of potential and problems, 2) Product design, 3) Design validation and design revision, 4) Product testing, 5) Analysis of trial results, and 6) final product assembly. The research instruments were in the form of observation sheets, tests, and questionnaires. The data analysis technique uses descriptive percentages. The results of the study in the form of scratch-assisted teaching materials that have characteristics provide opportunities for students to make momentum simulations independently. The percentage of the material validity score was 92.23% and the media validity was 88.64%. The results of the trial show that the acquisition of each skill score is more than 71, so it can be concluded that the materials teaching developed are practically used and effective to build 21st-century skills and industrial revolution 4.0.
Analysis of student’s learning achievement using PhET interactive simulation and laboratory kit of gas kinetic theory
Authors: Rustana C E , Andriana W , Serevina V , Junia D
Published: July 2020

This Quasi Experimental research aims to analyze the learning achievement of grade XI students of Public Senior High School in Bekasi, West Java-Indonesia. Two experiment science classes were selected as samples by using purposive random sampling. The 1st sample class was taught using laboratory kit activity; whirls the 2nd sample class was using PhET interactive simulation. The data was collected using written test to measure students’ achievement and then statistically analyzed using t-test to determine the hypothesis either be accepted or not. The normal distribution and homogeneity tests were also applied to know that the data was normally distributed, and all the variances were homogeneous with level of significant >0.05. The t test result indicated that the value of tcalculation (3,052) was greater than and tTable (1,667) that shown that there was a significant difference between the learning achievement of class 1 and 2 with mean value of 70.85 and 63.26, respectively. In conclusion that learning process using PhET interactive simulation provided higher students’ achievement compared to those class which apply laboratory kit activity of gas kinetic theory.
Investigation of the physics phenomena of weakly damped wave equations with forced force: theory and simulation
Authors: Jufriansah A , Hermanto A , Toifur M , Prasetyo E
Published: July 2020

The perturbation method is used to see changes in solutions that occur when attenuation is of little value, as in the phenomenon of waves with weak attenuation and which subjected to coercive force. Therefore this study aims to find solutions to solve the wave equations that experience weak attenuation and which subjected to coercive force. The method used is the study of literature and computation with MatLab. Based on the research results obtained that analytically non-homogeneous waveforms can not provide general solutions for differential resolution. Whereas computationally the results obtained are, the wave model with weak attenuation and the wave model with coercive force have amplitude values that change for time and for time wave models that subjected to coercive force has an amplitude value that increases compared to without coercive force.
Musa Acuminata Bract extraction for dye sensitized solar cell fabrication with Microwave Irradiation
Authors: Sutikno  , Ati L
Published: July 2020

One of the problems encountered in the making of dye-sensitized solar cell (DSSC) is the efficiency still relatively small compared to the conventional solar cells made from silicon. In this study, microwave irradiation was used in the process of coating Musa Accuminata Bract extract, with the aim that more anthocyanin pigments absorbed in the work electrode. This anthocyanin can make more sun energy absorbed and enhances efficiency. The resulting Musa Acuminata Bract extract was characterized using Ocean Optic Vis-Nir USB 4000 to determine its optical properties and produce maximum absorbance of 1.7353 at mass fraction of 0.45. The irradiation process was carried out using Electrolux Microwave Oven (EMM 2308X) at 140 W. After the DSSC sandwich is arranged, the sample is characterized using an El-Kahfi 100 I-V meter to determine its electrical properties. DSSC without microwave irradiation has an efficiency of 0.000345%, while with microwave irradiation, it could yield efficiency of 7.26%. This proves that microwave irradiation can improve DSSC performance.
Video tracker analysis: a strategy for measuring students communication and collaboration skills
Authors: Fianti  , Listiagfiroh W , Susilo
Published: July 2020

Students must have communication skills to communicate their ideas and thoughts. The communication skill of students plays a role in physics learning because it can change the learning situation in a better direction. In addition to communication skills, collaboration skills must also be owned by the students in the learning of physics, one of which is used to conduct observations in groups. The purpose of this research is to know the relationship between communication skills and students’ collaboration skills, especially in physics. This research is experimental and the sample was taken by purposive sampling technique. In the results, there is a very high relationship between communication skills and students’ collaboration. The score students’ communication skills was 0.876, indicating that there was a direct relationship between students’ communication and collaboration skills, where students’ communication skills increase with the increasing of collaboration skill. Additionally, learning used of video tracker software created new knowledge and skills.
Activity and selectivity of Ni/beta zeolite and Cu/beta zeolite catalysts on citronellal cyclization reaction from citronella oil
Authors: Utami Defi Nur , Cahyono Edy , Priatmoko Sigit
Published: July 2020

Isopulegol is an intermediate compound for synthesis some fine chemical and used in the pharmaceutical, soap and tooth paste industry. Conversion of citronellal to isopulegol in catalysed cyclization reaction has been investigated. Isopulegol can be produced by using cyclization reaction of citronellal with Ni/beta zeolite and Cu/beta zeolite catalysts. Citronellal has been isolated from citronella oil by fractional distillation under reduced pressure. The structure of product were analyzed by using GC, GC-MS and FTIR. The catalysts were prepared by using impregnation method and characrized by using XRD and SAA instruments. Citronellal cyclization was carried out at 180°C for 4 hour. Based on GC and GC-MS analysis, it was shown that concentration of isolated citronellal of 84.26%. XRD analysis of catalysts showed that the metals were impregnated with beta zeolite. Citronellal cyclization using Cu/beta zeolite catalyst produces 69.31% isopulegol and Ni/beta zeolite catalyst produce isopulegol at 29.68%. The Cu/beta zeolite catalyst has an activity of 90.20% and selectivity of 80.98%. The activity of Ni/beta zeolite catalyst of 42.53% with selectivity of 76.60%. These results indicate that Cu/beta zeolite catalyst is better than Ni/beta zeolite in citronellal cyclization.
The influence of polyethylene glycol on characteristic of Fe-N-TiO2 photocatalyst and its activity for water splitting
Authors: Priatmoko S , Sadewo R P , Harjito  , Rakainsa S K
Published: July 2020

Fe-N-TiO2 photocatalyst has been used in water splitting to produce hydrogen. Templating agent and dopant modification intends to determine the optimum composition with the best characterization and the highest production rate in visible light. Fe-N-TiO2 is synthesized using a sol-gel method with a various PEG and N weight percent. The variation of PEG is 2, 3, and 4% while N is 20, 25, and 30%w/w. Photocatalyst is characterized using DR-UV to find the band gap, XRD to see the crystallinity, and FTIR to know the functional group. Hydrogen gas from water splitting is analyzed using GC-TCD. Fe-N-TiO2 with 20wt% N can decrease up band gap to 2.56 eV. Photocatalyst with 4% PEG accelerates gelation time to 164.33 hours. The calculation of PEG anatase phase is 86.86% while the crystallite size is 44.26 nm. Synthesized Fe-N-TiO2 has major absorbtion at 520 cm-1 which is a region of Ti-O. From the activity test, Fe-N-TiO2 with 2% PEG and 20wt% N produces 0.076 μmol/hour hydrogen.
Bioethanol production from cassava-based industrial wastes using acid hydrolysis and simple fermentation
Authors: Heriyanti A P , Fibriana F , Tirtasari N L
Published: July 2020

Tapioca flour industry produces starchy wastes. Improper handling of this waste can cause environmental problems. The bioconversion of starchy waste to bioethanol has been widely performed. However, the utilization of solid waste from the tapioca flour industry for bioethanol production is still limited. This research is a preliminary investigation to determine the level of ethanol produced from cassava pulp and peel by the fermentation process. Cassava pulp and peel were prepared for the delignification process, hydrolysis process, fermentation process, and finally, the purification process. The fermentation process was carried out by varying fermentation periods, i.e., 2, 4, 6, 8, 10, 12, and 14 days. The highest ethanol concentration at 6.2% was obtained after eight days of fermentation.
Synthesis and characterization of bioactive compound from Cocoa fruit shell by pyrolysis process
Authors: Wijaya M , Wiharto M
Published: July 2020

Cocoa contain polyphenols and potential antioxidants. Polyphenols is beneficial to human health and used for cosmetic and food manufacturing. The production of cocoa and its derivative products resulted liquid smoke, tar and charcoal. Pyrolysis is able to overcome the accumulation of those production waste. In this study, pyrolysis was conducted at temperature 114-514°C. Analysis of cocoa shell content from Bulukumba district was lignin (42.28%), cellulose (44.55%), hemicellulose (10.02%). Analysis of cocoa shell content from Enrekang district was lignin (45.61%), cellulose (37.61%), hemicellulose (6.40%), and others (10.38%). GC-MS analysis for liquid smoke of cocoa shell from Bulukumba resulted acetic acid (18.39%), butyrolacton (6.27%), oxetane, 2-propyl (4.45%), 2,6-dimethyl-7-octen-3-ol (6.48%), and hexadecanoic acid (4.36%). GC-MS analysis for liquid smoke for cocoa shell Enrekang resulted acetic acid (25.78%), propane diamide (2.18%), acetamide N–methyl (4.0%), cyclopropyl carbinol (12.57%), 2-propanoic acid-2-methyl (7.83%), phenol 2,6-dimethoxy (2.72%), 1,6-anhydro-beta (5.83%), alpha-beta-D ribopyranose (1.76%). While XRD analysis for cocoa shell from Bulukumba and Enrekang showed that the degree crystallinity are 40.15% and 22.22%, respectively. The use of pyrolysis of cocoa shell can reduce carbon emission as environmental pollution and increase the economic value.
The application of liquid and solid organic fertilizer from Tilapia fish waste for conservation of Central Sulawesi superior Jackfruit plant from Tulo and Beka
Authors: Tiwow V M A , Adrianton  , Abram P H , Simatupang E A
Published: July 2020

In previous studies, there has been investigation about the levels of macro and microelements in liquid organic fertilizer and solid organic fertilizer made from Tilapia fish waste, indicated that the required standard of fertilizer could be met. Therefore, this research aims to study the application of Liquid Organic Fertilizer (LOF) and Solid Organic Fertilizer (SOF) from Tilapia fish waste to Central Sulawesi superior Jackfruit plants from Tulo and Beka areas. The factorial Block Random Design with two factors was used to analyze the growth of two kinds of Jackfruit plants and two kinds of fertilizer, with three times replications. The observation method was non-destructive measurement by using several parameters of growing plant standard. The result shows that all parameters measured among the combination of two kinds of Jackfruits, two kinds of fertilizers and three replications in terms of plant developing growth were no significant difference. The analyses of nutrient levels in the two kinds of fertilizers met the needs of Jackfruit plants.
Antioxidant activity and total phenolic content of three varieties of Ginger (Zingiber officinale) in decoction and infusion extraction method
Authors: Mahmudati N , Wahyono P , Djunaedi D
Published: July 2020

Ginger is one of the plants that is rich with phenolic compounds. This research was aimed at determination of the total phenolic content and antioxidant activity in the rhizome of ginger. However, there is only few information available about the comparison of phenolic compounds and antioxidant activity in the three varieties of ginger. This research employs a descriptive quantitative research using extracted dried gingers on two types of extraction processes, i.e. infusion and decoction. The phenolic compound analysis is conducted by using the Folin-C method, while antioxidant activity was conducted by using DPPH and measured by using Spectrophotometer. Based on ANOVA test result, the highest phenolic was red ginger 12.2533 mg GAE/g (infusion) and 22.9767 mg GAE/g (decoction) followed by emprit and elephant ginger. The highest antioxidant activity by infusion process was found in red ginger of 79.83 % followed by 70.43 % and 61.70% in emprit ginger and elephant ginger. Conversely, the highest antioxidant activity by decoction was found 78.76 % in emprit ginger, followed by 70.56 % and 60.93% for red ginger and elephant ginger. Ginger have sufficient antioxidant activity on extraction by infusion or decoction and the red ginger have a higher phenolic content.