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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Pengajaran MIPA TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmu Komputer (JIK) Indonesian Journal of Disability Studies Journal of Engineering and Technological Sciences ELINVO (Electronics, Informatics, and Vocational Education) Jurnal Penelitian dan Pembelajaran IPA Indonesian Journal of Science and Technology QUANTUM: Jurnal Inovasi Pendidikan Sains JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Knowledge Engineering and Data Science Jurnal Penelitian Pendidikan IPA (JPPIPA) Momentum: Physics Education Journal MUST: Journal of Mathematics Education, Science and Technology Journal of Natural Science and Integration JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI Journal of Education Technology Jurnal Tekno Insentif Jurnal Sains Dirgantara Education and Human Development Journal Jurnal Paedagogy Cendikia : Media Jurnal Ilmiah Pendidikan Journal Evaluation in Education (JEE) Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) Journal of Coaching and Sports Science IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan Bulletin of Social Informatics Theory and Application Jurnal Guru Komputer Jurnal Pendidikan Teknologi Informasi dan Komunikasi Jurnal Ilmiah Sistem Informasi Journal of Computers for Society Cadika Journal.
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Journal : Indonesian Journal of Science and Technology

Determining Trending Topics in Twitter with a Data-Streaming Method in R Mediayani, Melani; Wibisono, Yudi; Riza, Lala Septem; Pérez, Alejandro Rosales
Indonesian Journal of Science and Technology Vol 4, No 1 (2019): IJOST: VOLUME 4, ISSUE 1, 2019
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v4i1.15807

Abstract

Trending topics in Twitter is a collection of certain topics that are widely discussed by users. This study aims to design a model and strategy for finding trending topics from data streams on Twitter. The research approach was carried out in four stages, namely twitter data collection, preprocessing data, data analysis with sequential K-Means clustering and information processing. Sequential K-Means is used because it can receive input data sequentially and the cluster center can be updated. Testing of the model is carried out in three scenarios where each scenario is distinguished between the amount of data, time and parameter values. After that, evaluation of the results of clustering will be done using the Dunn Index method. Trending topics twitter application were created using the R language and produce output in the form of histograms. There are five topics being the trending topics in New York before the new year. The topic of "Times" relates to the presence of a new year's celebration night concert in Times Square. The "Hours" topic deals with the calculation of time and seconds towards 2017. "Eve" and "Party" topics relate to celebrations and the topic "Resolution" relating to hope and change for New Yorkers in in 2017.
Question Generator System of Sentence Completion in TOEFL Using NLP and K-Nearest Neighbor Riza, Lala Septem; Pertiwi, Anita Dyah; Rahman, Eka Fitrajaya; Munir, Munir; Abdullah, Cep Ubad
Indonesian Journal of Science and Technology Vol 4, No 2 (2019): IJOST: VOLUME 4, ISSUE 2, 2019
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v4i2.18202

Abstract

Test of English as a Foreign Language (TOEFL) is one of learning evaluation forms that requires excellent quality of questions. Preparing TOEFL questions using a conventional way certainly spends a lot of time. Computer technology can be used to solve the problem. Therefore, this research was conducted in order to solve the problem of making TOEFL questions with sentence completion type. The built system consists of several stages: (1) input data collection from foreign media news sites with excellent English grammar quality; (2) preprocessing with Natural Language Processing (NLP); (3) Part of Speech (POS) tagging; (4) question feature extraction; (5) separation and selection of news sentences; (6) determination and value collection of seven features; (7) conversion of categorical data value; (8) target classification of blank position word with K-Nearest Neighbor (KNN); (9) heuristic determination of rules from human experts; and (10) options selection or distraction based on heuristic rules. After conducting the experiment on 10 news, it is obtained that 20 questions based on the results of the evaluation showed that the generated questions had a very good quality with percentage of 81.93% (after the assessment by the human expert), and 70% was the same blank position from the historical data of TOEFL questions. So, it can be concluded that the generated question has the following characteristics: the quality of the result follows the data training from the historical TOEFL questions, and the quality of the distraction is very good because it is derived from the heuristics of human experts.
Multiplatform Application Technology – Based Heutagogy on Learning Batik: A Curriculum Development Framework Widiaty, Isma; Riza, Lala Septem; Abdullah, Ade Gafar; Mubaroq, Sugeng Rifqi
Indonesian Journal of Science and Technology Vol 5, No 1 (2020): IJOST: VOLUME 5, ISSUE 1, 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v5i1.18754

Abstract

This  study  aimed  to  design  a  batik  learning  medium  for vocational high school students in based on multiplatform. The application  made was expected  to support heutagogy approach – based learning and to deal with the development of  science  and  technology  integrated  in  the  curriculum  of vocational high schools. The application developed, namely e-botik,  was  an  integration  of  several  previously-designed applications using Code ignitor (CI) framework. The database used was My-SQL. It is commonly known that Code igniter is an open source web application framework utilized to create dynamic PHP applications. In this study, e-botik consisted of three main  components  including interface, database,  and application  programming  interface  (API).  Some  of  the applications combined were ARtikon_joyful (Android-based), Video Kasumedangan Batik (movie player), Nalungtik  Batik (desktop-based),  Digi_Learnik  (web-based),  Batik  UPI (manual),  Batik  Cireundeu  (manual),  and  Lembar  Balik (manual). The combination proceeded web-based so that it was  compatible  with  various  operating  systems.  The application (e-botik) was designed and then tested. The test was  performed  through  whitebox  testing  and  blackbox testing. The results of the test showed that it ran well and was able to be used a batik learning media. It is expected that students  can  utilize  e-botik  in  selecting  topics  of  learning batik in accordance with their competences and needs. This condition enables e-botik to support learning batik through heutagogical approach. In addition, the application was also validated in terms of both system and usage aspects. 
Working Volume and Milling Time on the Product Size/Morphology, Product Yield, and Electricity Consumption in the Ball-Milling Process of Organic Material Asep Bayu Dani Nandiyanto; Riezqa Andika; Muhammad Aziz; Lala Septem Riza
Indonesian Journal of Science and Technology Vol 3, No 2 (2018): IJoST: VOLUME 3, ISSUE 2, September 2018
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v3i2.12752

Abstract

Analysis of ball-milling process under various conditions (i.e. working volume, milling time, and material load) on the material properties (i.e. chemical composition, as well as particle size and morphology), product yield, and electricity consumption was investigated. Turmeric (curcuma longa) was used as a model of size-reduced organic material due to its thermally and chemically stability, and fragile. Thus, clear examination on the size-reduction phenomenon during the milling process can be done without considering any reaction as well as time-consuming process. Results showed that working volume is prospective to control the characteristics of product. Working volume manages the shear stress and the collision phenomena during the process. Specifically, the lower working volume led to the production of particles with blunt-edged morphology and sizes of several micrometers. Although working volume is potentially used for managing the final particle size, this parameter has a direct impact to the product yield and electricity consumption. Adjustment of the milling time is also important due to its relation to breaking material and electrical consumption.
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.
Co-Authors Abdullah, Cep Ubad Abu Samah, Khyrina Airin Fariza Achmad Samsudin Ade Gafar Abdullah, Ade Gafar Ade Rohayati Ade Sobandi, Ade Adedokun-Shittu, Nafisat Afolake Adi Rahmat Ahmad Zainal Abidin Akbar, Anthonio Al Husaeni, Dwi Fitria Al Husaeni, Dwi Novia Aldi Zainafif Alejandro Rosales Pérez Alejandro Rosales-Pérez Alfitri, Latifahny Aridia Aliyya, Farrel Rahma Amay Suherman Amirah Misdan, Nur Farhanah Anisyah, Ani anne Hafina, anne Aqhbar Habib Arianti, Andini Setya Asep Bayu Dani Nandiyanto Asep Wahyudin Asep Wahyudin Asri, Novri Atqiya, Muhammad Azka AZ Pranata Basallamah, Muhammad Alam Budiana, Dian Budiman Budiman Cep Ubad Abdullah Dadang Lukman Hakim Destian, Rangga Dewini Dewini Didin Wahyudin, Didin Edy Soewono Edy Soewono Eka Fitrajaya Rahman Eki Nugraha Eliyawati Eliyawati Enjang Ali Nurdin Erlangga, E. Erna Piantari Erry Fuadillah Faisal Syaiful Anwar Farhan Dhiyaa Pratama Farizi, Syahandhika Naufal Fathimah, Nusuki Syari'ati Fatimah, Nusuki Syariati Ferry Mukharradi Simatupang Fidela Zhafirah Firdaus, Pipin Gerraldi, Alief Gintara, Andre Rangga Gunarso Hamzah, Raseeda Hasanah , Lilik Nur Hasrol Jono, Mohd Nor Hajar Hayati , Nurlaila Herbert Siregar Homdijah, Oom Siti Huda, Kirana Syafa Husni Firmansyah Ida Kaniawati ISKANDAR, AYSHA ALIA Isma Widiaty Jaja Kustija Judhistira Aria Utama Junaeti, Enjun Kafilli, Muhammad Fikri Kenny David Kenny David Kesuma, Muhammad Salman Khyrina Airin Fariza Abu Samah Kuntjoro Adji Sidarto Kuntjoro Adji Sidarto Liliasari M. FURQON Mahmoud Fahsi Masnur Ali Mediayani, Melani Mohd Nor Hajar Hasrol Jono Muhammad Afif Auliya Muhammad Aziz Muhammad Bahrul Ulum Muhammad Hazmi Zuhdi Muhammad Irfan Firmansyah Muhammad Ramdan Pamungkas Muhammad Syafri Syamsudin Mumu Komaro Munir Munir Munir Munir, Munir N. Nurjanah Nanang Dwi Ardi Naufal Rabah Wahidin Nazir, Shah Nor Aiza Moketar Novi Sofia Fitriasari Novitasari , Eka Fitri Nur Maisarah Nor Azharludin Nuraulia, Anti Nurhayati, Ai Siti Nurqueen Sayang Dinnie Wirakarnain Nursalman, Muhammad Nusratullo, Samialloi Olyan, Warzuqni Parlindungan Sinaga Pérez, Alejandro Rosales Pertiwi, Anita Dyah Piantari, Erna Prabawa, Harsa Wara Prasetyaningsih Prasetyaningsih, Prasetyaningsih Prasetyaningsih, Prasetyaningsih Pudjo Sukarno Pudjo Sukarno Putri , Ananda Hafizhah Putri , Liandha Arieska Putri Amelia Solihah Putri, Iffa Ichwani Qobus, Muhammad Shofwan Rahman, M Ammar Fadhlur Rambari Apandi, Anjar Rani Megasari Raseeda Hamzah Rasim, Rasim Rena Zaen Rendi Adistya Rosdiyana Riandi Riandi Riezqa Andika Rika Rafikah Agustin Rizky Rachman Judie Rooseno Rahman Dewanto Rosa, Elisa Rosi Oktiani Rosyda, Miftahurrahma Safitri, Fibriyana Sahidin, M. Zaenal Iskandar Samah, Khyrina Airin Fariza Abu Sapiruddin, Sapiruddin Selvi Marcellia Shah Nazir Shah Nazir Sigit Nugroho Siregar, Herbert Siregar, Nofi Marlina Solihat, Syifa Sonjaya, Rebina Putri Sugeng Rifqi Mubaroq Suratno Susilawati, Susilawati Tarpin Juandi Taufiq Hidayat Topik Hidayat Tutuka Ariadji Tyas Farrah Dhiba Wahyudin Wahyudin - Wahyudin Wahyudin Sanusi Rosada Wahyudin Wahyudin Wahyudin, W. Wawan Setiawan Wibisono, Yudi Wihardi, Yaya Yudi Prasetyo Zain, Muhammad Iqbal Zainab Othman Zsalzsa Puspa Alivia