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INDONESIA
Indonesian Journal of Science and Technology
Published by Universitas Pendidikan Indonesia
ISSN : 25278045     EISSN : 25281410     DOI : -
Core Subject : Science, Social,
Computer Science & IT Environmental Science
Arjuna Subject : -
Articles 220 Documents
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Combining Chatbot and Social Media: Enhancing Personal Learning Environment (PLE) in Language Learning Nuria Haristiani; Mumu Muhamad Rifa’i
Indonesian Journal of Science and Technology Vol 5, No 3 (2020): IJOST: VOLUME 5, ISSUE 3, 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v5i3.28687

Abstract

Transformation of the global learning landscape in twenty-first century is shaped by the uptake of digital technology and social network applications, along with students’ alteration of characteristics, needs, and demands. As an attempt to integrate digital technology and social network application, this study aimed to develop a chatbot-based application integrated with social media LINE to enhance language learning, specifically for learning Japanese grammar. The application, namely Gengobot, is a chatbot-based grammar application, consisting of Japanese Language Proficiency Test Level 5 and Level 4 (N5 and N4) grammar materials in three language: Indonesian, English, and Japanese. This study applied design-based research method with Waterfall application development procedure, and a questionnaire to gather feedbacks from fifty-three students regarding Gengobot features and contents. Gengobot application was successfully developed using code igniter framework, MySQL database, and webhook to integrate Gengobot application with LINE messaging API. Application testing confirmed that Gengobot is successfully developed and operated properly. The students agreed that Gengobot materials and features considered to be adequate, useful, user friendly, and suitable to support language learning. Gengobot is also highly accessible since it is integrated to social media LINE, allowing students to adjust its use to their own learning preference and needs, which is suitable to enhance students’ personal learning environment.
Pyrolysis-GC/MS Analysis of Fast Growing Wood Macaranga Species R.R. Dirgarini J.N. Subagyono; Ying Qi; Alan L. Chaffee; Rudianto Amirta; Marc Marshall
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31917

Abstract

Py-GC/MS analysis of six different species of fast growing Macaranga wood has been studied. Flash pyrolysis was conducted at different temperatures (250-850 oC) under a flow of helium followed by GC/MS analysis of the products. The total pyrolysis yields of the six different species of Macaranga were mostly between 40 and 90% within the range of pyrolysis temperature applied.  Pyrolysis of the woody biomass produced compounds which are mostly derived from thermal degradation or volatilization of lignin and cellulose/hemicellulose, the original major constituents of the biomass. The Py-GC/MS technique indicated that M. gigantea was the most potential species for biofuel production and the optimum pyrolysis temperature to produce high yields of bio-oil was 450 oC.
CDIO Initiative: A Guarantee for Successful Accreditation of Engineering Programmes Abdulkareem Sh. Mahdi Al-Obaidi
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31521

Abstract

The accreditation bodies and engineering councils set a number of qualifying requirements and accreditation criteria to ensure the quality of engineering graduates and programmes. One of these requirements is the engineering curriculum. Some institutions using the traditional engineering curriculum often face difficulties and burden to meet the accreditation minimum academic requirements as their curriculum lacks the innovation and the integration of graduate attributes such as personal, interpersonal, teamwork, entrepreneurship, development of life skills and emotional wellbeing, among many. This eventually leads to deferred or even declined accreditation. To overcome these difficulties, the CDIO initiative is an ideal tool for successful accreditation. The CDIO standards, syllabus, engineering curriculum, and learning outcomes are not only meeting what accreditation bodies require, but they offer innovative curriculum more on high-level cognitive skills set in the context of the product-system lifecycle; Conceiving-Designing-Operating-Implementing metaphases. This paper shares a successful engineering education experience of the School of Engineering/Taylor’s University and how the CDIO initiative contributed not only to a successful accreditation but also to have a new innovative engineering curriculum. The adopted new curriculum is innovative, hands-on and project-based in order to achieve integrated learning where acquiring discipline-specific knowledge and CDIO skills take place simultaneously
Hybrid Vector Autoregression Feedforward Neural Network with Genetic Algorithm Model for Forecasting Space-Time Pollution Data Rezzy Eko Caraka; Rung Ching Chen; Hasbi Yasin; Suhartono Suhartono; Youngjo Lee; Bens Pardamean
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.32732

Abstract

The exposure rate to air pollution in most urban cities is really a major concern because it results to a life-threatening consequence for human health and wellbeing. Furthermore, the accurate estimation and continuous forecasting of pollution levels is a very complicated task.  In this paper, one of the space-temporal models, a vector autoregressive (VAR) with neural network (NN) and genetic algorithm (GA) was proposed and enhanced. The VAR could tackle the issue of multivariate time series, NN for nonlinearity, and GA for parameter estimation determination. Therefore, the model could be used to make predictions, such as the information of series and location data. The applied methods were on the pollution data, including NOX, PM2.5, PM10, and SO2 in Taipei, Hsinchu, Taichung, and Kaohsiung. The metaheuristics genetic algorithm was used to enhance the proposed methods during the experiments. In conclusion, the VAR-NN-GA gives a good accuracy when metric evaluation is used. Furthermore, the methods can be used to determine the phenomena of 10 years air pollution in Taiwan.
Unlimited Energy Source: A Review of Ocean Wave Energy Utilization and Its Impact on the Environment Muhammad Satriawan; L Liliasari; Wawan Setiawan; Ade Gafar Abdullah
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31473

Abstract

This paper aims to review the potential of wave energy in several countries, the wave energy converter technology that has been developed, and the impact of the installation of wave energy converter technology devices on the environment. In addition, it discusses the theoretical formulations and challenges in the development of energy converter technology in the future. Based on the detail analysis, the potential of ocean wave energy for alternative energy is very large but cannot be used optimally because the technology of wave energy converter that has been developed is still on a prototype scale. In addition, the impact of the use of ocean wave converters on the environment is insignificant compared with conventional energy. Finally, this study informs and recommends the government and the private sector to start investing in the ocean wave energy industry optimally in order to achieve a sustainable future.
Computational Analysis of Different Turbulence Models in a Vane Pump Simulation Daniel Alberto Beleño Molina; Rafael Ramírez Restrepo; Jorge Eliecer Duarte Forero; Andrés David Rodríguez Toscano
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31918

Abstract

The study presents a computational analysis of a vane pump using two different turbulence models namely κ-ε and κ-ω. The geometry characteristics of the vane pump were obtained by disassembly and further measurements. The CAD model for the computational domain was developed in SOLIDWORKS®. The CFD modeling was powered by ANSYS®, which allowed the evaluation of different mesh types and turbulence models. A total set of six simulations were performed to obtain comparison schemes for turbulence model evaluation. Specifically, the angular velocity and excentricity were varied within the simulations. Both turbulence models were carefully validated using the manufacturer´s dataset as validation criteria, obtaining a relative error of less than 5%. The κ-ω experienced the best performance when describing the flow variables, excepting the pressure gradient. Specifically, the κ-ω presented an accurate prediction of edge effects, energy losses in the walls, and turbulent viscosity. Notably, the CFD modeling showed that density and velocity variations are not significant. Overall, CFD modeling demonstrated to be a robust tool to gain insight understanding of the flow interactions in vane pump operation. 
The K-Means Algorithm for Generating Sets of Items in Educational Assessment Lala Septem Riza; Rendi Adistya Rosdiyana; Alejandro Rosales Pérez; Asep Wahyudin
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31523

Abstract

In a national-scale educational assessment system, such as the National Examination, the need for several sets of questions that have the same level of difficulty is very required to avoid cheating by students. Therefore, the objective, which is to make a set of questions with the same level of difficulty automatically, is done in this research. It used a machine learning approach, namely K-Means. To achieve this goal, several following procedures need to be implemented. Firstly, we need to create banks of questions to be assigned to students. Then, we build training data by determining the value of each question based on Bloom's Taxonomy, item characters/types, and other parameters. Then, with utilizing K-Means, several cluster centers are obtained to represent the uniformity of the questions in the cluster members. By using several heuristics criteria defined previously, several sets or packages of questions that have the same characteristics and difficulty levels are obtained. From the experiments conducted, the analysis with descriptive (i.e., mean, standard deviation, and data visualization) and inference (i.e., ANOVA) statistics of results are presented showing that questions of each sets have the same characteristics to ensure the fairness of examinations. Moreover, by using this system, the contents of the questions in the generated set do not need to be the same, the package of questions can be generated automatically quickly, and the level of the difficulties can be measured and guaranteed.
How to Read and Interpret 1H-NMR and 13C-NMR Spectrums Ramdhan Gunawan; Asep Bayu Dani Nandiyanto
Indonesian Journal of Science and Technology Vol 6, No 2 (2021): IJOST: VOLUME 6, ISSUE 2, September 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i2.34189

Abstract

Nuclear magnetic resonance spectroscopy or NMR is a chemical instrument that can be used to evaluate the structure of a chemical compound other than FTIR, GC-MS, and HPLC. NMR spectroscopy commonly used for compound analysis is 1H-NMR and 13C-NMR. Techniques can be used to determine the structure conformation, the number of protons, and the number of carbons in the structure of a chemical compound. So far, there have been many publications related to the use of this spectroscopic technique. However, the steps in reading and interpreting the spectra of both 1H-NMR and 13C-NMR are not described in detail. Thus, in this paper, we described the steps in reading and interpreting the 1H-NMR and 13C-NMR spectra based on the level of difficulties: (1) simple compounds, (2) fairly complex compounds, (3) more complex compounds, and (4) very complex compounds.
The Comparison of Electrodialysis and Nanofiltration in Nitrate Removal from Groundwater J Touir; S Kitanou; M Zait; S Belhamidi; M Belfaquir; M Tahaikt; M Taky; A Elmidaoui
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31477

Abstract

Nitrate groundwater contamination is of major interest all over the world. This problem arises in agricultural regions across Morocco. An excess amount of nitrate causes a serious problem in urban water networks and human health. Because of these health risks, considerable attention has been paid to find effective treatment processes to reduce nitrate concentrations to safe levels. The World Health Organization has set an acceptable level for nitrate in drinking water at 50 mg/L. The aim of this study is to reduce the nitrate concentration from groundwater using two membrane processes: Electrodialysis (ED) and Nanofiltration (NF). Efficiencies of these two technologies are compared in respect to nitrate ions removal, cost process and final quality of water. The results of technologies show that, for electrodialysis standards level can be achieved for a demineralization rate of 15% and the physico-chemical quality of the produced water is satisfactory. For nanofiltration we obtain a nitrate removal of 90% but the produced water is very de-mineralized and must be remineralized.
Decay of Entanglement of Correlated Qubits Through Bosonic Fields Deniz Türkpençe
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.31921

Abstract

Distribution of entangled parties with the longest time possible is of importance to quantum communication. Therefore, analyzing the decay character of entanglement of correlated qubits in the presence of reservoir effects is of significance to the quantum-based technologies. This study covers the analysis of the temporal entanglement decay of two maximally entangled qubits against different reservoir types and system parameters. It is shown how varying the coupling type of the system to the environment affects the lifetime of entanglement. In the presence of quantum interaction between entangled qubits, it is possible to enlarge the entanglement lifetime depending on the initialization of entanglement.  Model parameters used in the numerical calculations and the results are general enough to be applied in any specific quantum-based experimental task.

Page 14 of 22 | Total Record : 220

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