There has been drastic growth in the microelectronics industry in the recent past. The performance of these materials is influenced by their structural, electrical, and optical properties among others, depending on their applications. Therefore, the need to conduct measurements of the semiconductor characteristics precisely, quickly, and conveniently cannot be overstated. Some of the desirable features of measurements include usability, accuracy, resolution, repeatability, and consistency which cannot be assured with manually operated systems. This study strived to design and interface an automated computer-aided four-point probe test equipment that characterizes materials to determine their electrical properties. A four-point probe head, an electromagnet, NI Keithley model 6220 Precision current source, model 7001 switch, model 2182A Nanovoltmeter, and model 7065 Hall Effect card instruments were interfaced with the NI LabVIEW program running in a computer through a GPIB hub to a PC USB for its full control. The four-probe head was utilized to probe the samples with a square symmetry that was adopted for the measurement of the semiconductor properties. Reliability tests were conducted on a standard P-type Germanium sample. The collected data was within 0.32% of the expected results. This work forms a basis for automating similar systems that were inherently designed to be operated manually. Keywords: Automated Hall Effect, manually operated systems, Hall angle, thin films, string manipulation routines.
{"title":"Development of an Automated Hall Effect Experimentation Method for the Electrical Characterization of Thin Films","authors":"A. M. Orega","doi":"10.53819/81018102t4208","DOIUrl":"https://doi.org/10.53819/81018102t4208","url":null,"abstract":"There has been drastic growth in the microelectronics industry in the recent past. The performance of these materials is influenced by their structural, electrical, and optical properties among others, depending on their applications. Therefore, the need to conduct measurements of the semiconductor characteristics precisely, quickly, and conveniently cannot be overstated. Some of the desirable features of measurements include usability, accuracy, resolution, repeatability, and consistency which cannot be assured with manually operated systems. This study strived to design and interface an automated computer-aided four-point probe test equipment that characterizes materials to determine their electrical properties. A four-point probe head, an electromagnet, NI Keithley model 6220 Precision current source, model 7001 switch, model 2182A Nanovoltmeter, and model 7065 Hall Effect card instruments were interfaced with the NI LabVIEW program running in a computer through a GPIB hub to a PC USB for its full control. The four-probe head was utilized to probe the samples with a square symmetry that was adopted for the measurement of the semiconductor properties. Reliability tests were conducted on a standard P-type Germanium sample. The collected data was within 0.32% of the expected results. This work forms a basis for automating similar systems that were inherently designed to be operated manually. Keywords: Automated Hall Effect, manually operated systems, Hall angle, thin films, string manipulation routines.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136103461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Regolinda Maneno, Budiman Baso, Patricia G. Manek, Kristoforus Fallo
Penelitian ini bertujuan untuk membangun sistem deteksi tingkat kematangan buah pinang dengan memanfaatkan pengolahan citra digital yang melibatkan fitur-fitur tekstur dan warna. Tahapan awal dalam penelitian adalah melakukan Pre-processing data citra agar dapat disiapkan untuk proses selanjutnya, yaitu ekstraksi fitur. Proses ekstraksi fitur tekstur dilakukan dengan menggunakan Gray Level Co-Occurrence Matrix (GLCM) untuk mengambil nilai Correlation, sementara ekstraksi fitur warna dilakukan dengan metode Color Moments dengan fokus pada nilai Mean. Klasifikasi dengan Support Vector Machine (SVM) dilakukan berdasarkan fitur yang telah diekstraksi sebelumnya, adapun parameter yang diujicobakan adalah jenis kernel yaitu Linear, Gaussian, Polynomial pada algoritma SVM. Dari hasil yang diperoleh menunjukan semua matrik performa dari kernel Polynomial mengungguli kernel yang lain dengan hasil Accuracy yang diperoleh sebesar 90,90%, Precision 90,90%, Recall 92,30% dan F1-Score mecapai 91,60% pada proses deteksi tingkat kematangan buah pinang.
{"title":"Deteksi Tingkat Kematangan Buah Pinang Menggunakan Metode Support Vector Machine Berdasarkan Warna Dan Tekstur","authors":"Regolinda Maneno, Budiman Baso, Patricia G. Manek, Kristoforus Fallo","doi":"10.32938/jitu.v3i2.5323","DOIUrl":"https://doi.org/10.32938/jitu.v3i2.5323","url":null,"abstract":"Penelitian ini bertujuan untuk membangun sistem deteksi tingkat kematangan buah pinang dengan memanfaatkan pengolahan citra digital yang melibatkan fitur-fitur tekstur dan warna. Tahapan awal dalam penelitian adalah melakukan Pre-processing data citra agar dapat disiapkan untuk proses selanjutnya, yaitu ekstraksi fitur. Proses ekstraksi fitur tekstur dilakukan dengan menggunakan Gray Level Co-Occurrence Matrix (GLCM) untuk mengambil nilai Correlation, sementara ekstraksi fitur warna dilakukan dengan metode Color Moments dengan fokus pada nilai Mean. Klasifikasi dengan Support Vector Machine (SVM) dilakukan berdasarkan fitur yang telah diekstraksi sebelumnya, adapun parameter yang diujicobakan adalah jenis kernel yaitu Linear, Gaussian, Polynomial pada algoritma SVM. Dari hasil yang diperoleh menunjukan semua matrik performa dari kernel Polynomial mengungguli kernel yang lain dengan hasil Accuracy yang diperoleh sebesar 90,90%, Precision 90,90%, Recall 92,30% dan F1-Score mecapai 91,60% pada proses deteksi tingkat kematangan buah pinang.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135081773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Smart Greenhouse adalah sistem yang menggunakan teknologi Internet of Things (IoT) untuk mengontrol dan memantau lingkungan pertumbuhan tanaman secara otomatis. Dalam melakukan analisis kinerja mikrokomputer Raspberry Pi dalam Smart Greenhouse berbasis IoT, dengan menerapkan algoritma Naive Bayes untuk menganalisis data dan membuat keputusan berdasarkan kondisi lingkungan tanaman. Hasil analisis terhadap mikrokomputer Raspberry Pi pada Smart Greenhouse menggunakan algoritma Naive Bayes dapat digunakan untuk memprediksi variabel lingkungan, seperti suhu dan kelembapan, sesuai data yang diperoleh dengan total data set adalah 500 baris menggunakan 4 variabel dengan mempunyai nilai evaluasi terhadap suhu udara dengan MSE (0.25) dan RMSE (0.50), kelembapan udara dengan MSE (0.07) dan RMSE (0.27), kelembapan tanah dengan MSE (0.00) dan RMSE (0.00) dan UV dengan nilai MSE (0.94) dan RMSE(0.97)
Smart Greenhouse adalah sistem yang menggunakan teknologi Internet of Things (IoT) untuk mengontrol dan memantau lingkungan pertumbuhan tanaman secara otomatis. Dalam melakukan analisis kinerja mikrokomputer Raspberry Pi dalam Smart Greenhouse berbasis IoT, dengan menerapkan algoritma Naive Bayes untuk menganalisis data dan membuat keputusan berdasarkan kondisi lingkungan tanaman. Hasil analisis terhadap mikrokomputer Raspberry Pi pada Smart Greenhouse menggunakan algoritma Naive Bayes dapat digunakan untuk memprediksi variabel lingkungan, seperti suhu dan kelembapan, sesuai data yang diperoleh dengan total data set adalah 500 baris menggunakan 4 variabel dengan mempunyai nilai evaluasi terhadap suhu udara dengan MSE (0.25) dan RMSE (0.50), kelembapan udara dengan MSE (0.07) dan RMSE (0.27), kelembapan tanah dengan MSE (0.00) dan RMSE (0.00) dan UV dengan nilai MSE (0.94) dan RMSE(0.97)
{"title":"Analisis Kinerja Mikrokomputer Raspberry Pi Pada Smart Greenhouse Berbasis Internet Of Things (IoT) Menggunakan Algoritma Naive Baye","authors":"Philipus Asten","doi":"10.32938/jitu.v3i2.5231","DOIUrl":"https://doi.org/10.32938/jitu.v3i2.5231","url":null,"abstract":"Smart Greenhouse adalah sistem yang menggunakan teknologi Internet of Things (IoT) untuk mengontrol dan memantau lingkungan pertumbuhan tanaman secara otomatis. Dalam melakukan analisis kinerja mikrokomputer Raspberry Pi dalam Smart Greenhouse berbasis IoT, dengan menerapkan algoritma Naive Bayes untuk menganalisis data dan membuat keputusan berdasarkan kondisi lingkungan tanaman. Hasil analisis terhadap mikrokomputer Raspberry Pi pada Smart Greenhouse menggunakan algoritma Naive Bayes dapat digunakan untuk memprediksi variabel lingkungan, seperti suhu dan kelembapan, sesuai data yang diperoleh dengan total data set adalah 500 baris menggunakan 4 variabel dengan mempunyai nilai evaluasi terhadap suhu udara dengan MSE (0.25) dan RMSE (0.50), kelembapan udara dengan MSE (0.07) dan RMSE (0.27), kelembapan tanah dengan MSE (0.00) dan RMSE (0.00) dan UV dengan nilai MSE (0.94) dan RMSE(0.97)
 
 Smart Greenhouse adalah sistem yang menggunakan teknologi Internet of Things (IoT) untuk mengontrol dan memantau lingkungan pertumbuhan tanaman secara otomatis. Dalam melakukan analisis kinerja mikrokomputer Raspberry Pi dalam Smart Greenhouse berbasis IoT, dengan menerapkan algoritma Naive Bayes untuk menganalisis data dan membuat keputusan berdasarkan kondisi lingkungan tanaman. Hasil analisis terhadap mikrokomputer Raspberry Pi pada Smart Greenhouse menggunakan algoritma Naive Bayes dapat digunakan untuk memprediksi variabel lingkungan, seperti suhu dan kelembapan, sesuai data yang diperoleh dengan total data set adalah 500 baris menggunakan 4 variabel dengan mempunyai nilai evaluasi terhadap suhu udara dengan MSE (0.25) dan RMSE (0.50), kelembapan udara dengan MSE (0.07) dan RMSE (0.27), kelembapan tanah dengan MSE (0.00) dan RMSE (0.00) dan UV dengan nilai MSE (0.94) dan RMSE(0.97)
","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136099849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to assist human work in knowing the decision support system for determining outstanding teachers using the topsis method using the Multi Attribute Decision Making (MADM) decision making method which is used to evaluate or select several alternatives as a decision support system using one method, namely the The trick for order preference by similarity to ideal solution (TOPSIS). This method is widely used to solve practical decision-making. This is because the concept is simple and easy to understand, computation is efficient, and has the ability to measure the relative performance of decision alternatives. There are 5 criteria used in determining outstanding teachers, namely pedagogic, personality, professional, social and innovation. From the results of calculations using the cicue for order preference by similarity to ideal solution (TOPSIS) method, the teacher who was selected as an outstanding teacher was Elisabeth Abi S.PD SD with a score of 0.825. Thecnicue for order preference by similarity to ideal solution (TOPSIS) method makes it easy to determine outstanding teachers at the youth and sports education office at TTU, this is web-based and uses the PHP programming language.
本研究旨在协助人类工作了解使用topsis方法确定优秀教师的决策支持系统，使用多属性决策(MADM)决策方法，该决策方法用于使用一种方法评估或选择多个备选方案作为决策支持系统，即topsis (order preference by similarity to ideal solution)。该方法被广泛用于解决实际决策问题。这是因为它的概念简单易懂，计算效率高，并且能够衡量决策备选方案的相对性能。优秀教师有5个标准，分别是教学、个性、专业、社会和创新。从TOPSIS法排序偏好曲线计算结果来看，入选优秀教师为Elisabeth Abi S.PD SD，得分为0.825。TOPSIS (order preference by similarity to ideal solution)方法使得TTU青年与体育教育办公室的优秀教师的评选变得容易，该方法是基于web的，使用PHP编程语言。
{"title":"SISTEM PENDUKUNG KEPUTUSAN PENENTUAN GURU BERPRESTASI MENGGUNAKAN METODE TOPSIS (STUDI KASUS: DINAS PPO KAB. TTU)","authors":"Jeri Aurelianus Sede, Yoseph P.K Kelen, Darsono Nababan","doi":"10.32938/jitu.v3i2.4083","DOIUrl":"https://doi.org/10.32938/jitu.v3i2.4083","url":null,"abstract":"This study aims to assist human work in knowing the decision support system for determining outstanding teachers using the topsis method using the Multi Attribute Decision Making (MADM) decision making method which is used to evaluate or select several alternatives as a decision support system using one method, namely the The trick for order preference by similarity to ideal solution (TOPSIS). This method is widely used to solve practical decision-making. This is because the concept is simple and easy to understand, computation is efficient, and has the ability to measure the relative performance of decision alternatives. There are 5 criteria used in determining outstanding teachers, namely pedagogic, personality, professional, social and innovation. From the results of calculations using the cicue for order preference by similarity to ideal solution (TOPSIS) method, the teacher who was selected as an outstanding teacher was Elisabeth Abi S.PD SD with a score of 0.825. Thecnicue for order preference by similarity to ideal solution (TOPSIS) method makes it easy to determine outstanding teachers at the youth and sports education office at TTU, this is web-based and uses the PHP programming language.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135303837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SIPLO is information system created and developed in order to manage academic activity scheduling data so that it can make it easier for users in intranet and internet campus academic activities. This study aims to determine the level of satisfaction of the Sistem Informasi Terpadu Program Studi (SIPLO) using the End User Computing Satisfaction (EUCS) model which includes 5 variables, namely content, accuracy, format, easy of use and timeliness. The results of the study showed that the satisfaction level of SIPLO users was 24% very satisfied, 52% satisfied, 21% quite satisfied, 2% dissatisfied and 1% very dissatisfied. The results of the hypothesis test showed that 5 variables had an effect on satisfaction and the hypothesis was accepted while the other 2 variables had no effect on satisfaction and the hypothesis was rejected.
{"title":"Analisis Kepuasan Pengguna Terhadap Penerapan Sistem Informasi Terpadu Layanan Prodi (SIPLO) Menggunakan End User Computing Satisfaction (EUCS)","authors":"Vina Zahrotun Kamila","doi":"10.32938/jitu.v3i2.4128","DOIUrl":"https://doi.org/10.32938/jitu.v3i2.4128","url":null,"abstract":"SIPLO is information system created and developed in order to manage academic activity scheduling data so that it can make it easier for users in intranet and internet campus academic activities. This study aims to determine the level of satisfaction of the Sistem Informasi Terpadu Program Studi (SIPLO) using the End User Computing Satisfaction (EUCS) model which includes 5 variables, namely content, accuracy, format, easy of use and timeliness. The results of the study showed that the satisfaction level of SIPLO users was 24% very satisfied, 52% satisfied, 21% quite satisfied, 2% dissatisfied and 1% very dissatisfied. The results of the hypothesis test showed that 5 variables had an effect on satisfaction and the hypothesis was accepted while the other 2 variables had no effect on satisfaction and the hypothesis was rejected.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135303839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Penelitian ini berfokus pada pengembangan Sistem Informasi Pariwisata daerah Kabupaten Malaka berbasis website. Kabupaten Malaka memiliki potensi pariwisata yang menarik, seperti Pantai Abudenok, Motadikin, Lao'odik, dan Pos Lintas Batas Negara (PLBM) Motamasin. Namun, informasi mengenai tempat-tempat pariwisata ini belum terpublikasi dengan baik karena beberapa lokasi berada di daerah pelosok.
Tujuan penelitian ini adalah merancang dan membuat sistem informasi pariwisata berbasis web untuk Kabupaten Malaka, serta menguji kualitas sistem yang telah dibuat. Dengan sistem informasi ini, diharapkan dapat meningkatkan promosi dan pengelolaan objek-objek wisata di Kabupaten Malaka. Penelitian ini menggunakan metode penelitian terapan dengan tahapan pengumpulan data, identifikasi masalah, perancangan sistem, pengujian, implementasi, dan pemeliharaan.
Analisis kebutuhan sistem dilakukan melalui observasi, wawancara, dan studi pustaka. Sistem ini memiliki fitur seperti tampilan informasi wisata, laporan data wisata, posting informasi, review data, dan fitur login untuk admin. Implementasi dilakukan dengan membuat antarmuka pengguna (UI) sesuai dengan perancangan yang telah dibuat.
Pengujian sistem dilakukan melalui uji coba dengan pengguna admin dan pengguna biasa (user). Hasil pengujian menunjukkan bahwa sistem berhasil memenuhi fungsionalitas yang diharapkan, seperti pengelolaan data wisata, posting informasi, dan review data.man Judul
{"title":"SISTEM INFORMASI PARIWISATA DAERAH KABUPATEN MALAKA BERBASIS WEB","authors":"Yanuarius Nahak","doi":"10.32938/jitu.v3i2.5122","DOIUrl":"https://doi.org/10.32938/jitu.v3i2.5122","url":null,"abstract":"Penelitian ini berfokus pada pengembangan Sistem Informasi Pariwisata daerah Kabupaten Malaka berbasis website. Kabupaten Malaka memiliki potensi pariwisata yang menarik, seperti Pantai Abudenok, Motadikin, Lao'odik, dan Pos Lintas Batas Negara (PLBM) Motamasin. Namun, informasi mengenai tempat-tempat pariwisata ini belum terpublikasi dengan baik karena beberapa lokasi berada di daerah pelosok.
 Tujuan penelitian ini adalah merancang dan membuat sistem informasi pariwisata berbasis web untuk Kabupaten Malaka, serta menguji kualitas sistem yang telah dibuat. Dengan sistem informasi ini, diharapkan dapat meningkatkan promosi dan pengelolaan objek-objek wisata di Kabupaten Malaka. Penelitian ini menggunakan metode penelitian terapan dengan tahapan pengumpulan data, identifikasi masalah, perancangan sistem, pengujian, implementasi, dan pemeliharaan.
 Analisis kebutuhan sistem dilakukan melalui observasi, wawancara, dan studi pustaka. Sistem ini memiliki fitur seperti tampilan informasi wisata, laporan data wisata, posting informasi, review data, dan fitur login untuk admin. Implementasi dilakukan dengan membuat antarmuka pengguna (UI) sesuai dengan perancangan yang telah dibuat.
 Pengujian sistem dilakukan melalui uji coba dengan pengguna admin dan pengguna biasa (user). Hasil pengujian menunjukkan bahwa sistem berhasil memenuhi fungsionalitas yang diharapkan, seperti pengelolaan data wisata, posting informasi, dan review data.man Judul","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135353798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Penyakit Covid 19 atau yang sering disebut dengan Virus Corona saat ini sedang menjadi perhatian dunia salah satunya di Indonesia. Dampak dari covid 19 di Indonesia merambat ke berbagai sektor terutama sektor pendidikan yang mengakibatkan perubahan besar dalam proses pembelajaran. Tingkat keefektifan serta tingkat kepuasan siswa terhadap proses pembelajaran sangat dipengaruhi oleh pembelajaran yang dilaksanakan secara daring, yang berdampak tidak hanya pada perubahan perilaku siswa tetapi juga pada cara mengajar. Sehingga terdapat ketidakpuasan serta tanggapan yang berbeda dalam proses belajar mengajar dari mahasiswa/i dikarenakan jaringan yang sering terganggu dan terbatasnya kouta internet. Tujuan dari penelitian ini yaitu mengukur tingkat kepuasaan mahasiswa/i terhadap proses belajar mengajar yang dilakukan secara daring, dengan menggunakan metode K-Means clustering berdasarkan perspektif mahasiswa/i. Penelitian ini melibatkan 1406 responden dari hasil pembagian kuisoner melalui google form, kemudian data yang diperoleh akan dianalisis menggunakan software phyton untuk membantu dalam proses analisis. Hasil penelitian ini menunjukan bahwa data yang diperoleh dari empat kategori tingkat kepuasan mahasiswa/i yaitu cluster 1 kategorinya baik persentase 39,5 %, cluster 2 kategorinya kurang baik persentase 16,1 %, cluster 3 kategorinya sangat baik persentase 15,9 %, dan cluster 4 kategorinya cukup baik persentase 28,4 %.
{"title":"Analisis Tingkat Kepuasan Mahasiswa Terhadap Perkuliahan Daring Di Era Covid 19 Menggunakan K-Means Clustering","authors":"Theresia Avila Babu, Darsono Nababan","doi":"10.32938/jitu.v3i2.5130","DOIUrl":"https://doi.org/10.32938/jitu.v3i2.5130","url":null,"abstract":"Penyakit Covid 19 atau yang sering disebut dengan Virus Corona saat ini sedang menjadi perhatian dunia salah satunya di Indonesia. Dampak dari covid 19 di Indonesia merambat ke berbagai sektor terutama sektor pendidikan yang mengakibatkan perubahan besar dalam proses pembelajaran. Tingkat keefektifan serta tingkat kepuasan siswa terhadap proses pembelajaran sangat dipengaruhi oleh pembelajaran yang dilaksanakan secara daring, yang berdampak tidak hanya pada perubahan perilaku siswa tetapi juga pada cara mengajar. Sehingga terdapat ketidakpuasan serta tanggapan yang berbeda dalam proses belajar mengajar dari mahasiswa/i dikarenakan jaringan yang sering terganggu dan terbatasnya kouta internet. Tujuan dari penelitian ini yaitu mengukur tingkat kepuasaan mahasiswa/i terhadap proses belajar mengajar yang dilakukan secara daring, dengan menggunakan metode K-Means clustering berdasarkan perspektif mahasiswa/i. Penelitian ini melibatkan 1406 responden dari hasil pembagian kuisoner melalui google form, kemudian data yang diperoleh akan dianalisis menggunakan software phyton untuk membantu dalam proses analisis. Hasil penelitian ini menunjukan bahwa data yang diperoleh dari empat kategori tingkat kepuasan mahasiswa/i yaitu cluster 1 kategorinya baik persentase 39,5 %, cluster 2 kategorinya kurang baik persentase 16,1 %, cluster 3 kategorinya sangat baik persentase 15,9 %, dan cluster 4 kategorinya cukup baik persentase 28,4 %.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135353801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-05DOI: 10.1108/ijilt-12-2022-0220
H. Utunen, Ranil Appuhamy, M. Attias, N. Ndiaye, R. George, E. Arabi, A. Tokar
PurposeOpenWHO is the World Health Organization's online learning platform that was launched in 2017. The COVID-19 pandemic led to massive growth in the number of courses, enrolments and reach of the platform. The platform is built on a stable and scalable basis that can host a large volume of learners. The authors aim to identify key factors that led to this growth.Design/methodology/approachIn this research paper, the authors examined OpenWHO metadata, end-of-course surveys and internal processes using a quantitative approach.FindingsOpenWHO metadata showed that the platform has hosted over 190 health courses in 65 languages and over seven million course enrolments. Since the onset of the pandemic, there have been more women, older people and people from middle income countries accessing courses than before. Following data analysis of the platform metadata and course production process, it was found that several key factors contributed to the growth of the platform. First, OpenWHO has a standardised course production pathway that ensures efficiency, consistency and quality. Further, providing courses in different languages increased its reach to a variety of populations throughout the world. For this, multi-language translation is achieved through a network of translators and an automated system to ensure the efficient translation of learning products. Lastly, it was found that access was promoted for learners with disabilities by optimising accessibility in course production. Data analysis of learner feedback surveys for selected courses showed that the courses were well received in that learners found it useful to complete courses that were self-paced and flexible. In addition, results indicated that preferred learning methods included videos, downloadable documents, slides, quizzes and learning exercises.Originality/valueLessons learnt from the WHO's learning response will help prepare researchers for the next health emergency to ensure timely, equitable access to quality health knowledge for everyone. Findings of this study will provide valuable insights for educators, policymakers and researchers in the field who intend to use online learning to optimise knowledge acquisition and performance.
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Pub Date : 2023-09-01DOI: 10.1108/ijilt-08-2022-0171
Yung-Ming Cheng
PurposeThe purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to test whether network externality, gamification and media richness as environmental feature antecedents to learners' learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs).Design/methodology/approachSample data for this study were collected from learners who had experience in taking the gamified MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 315 usable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study verified that learners' perceived network externality, gamification and media richness in MOOCs positively influenced their behavioral LE, emotional LE and social LE elicited by MOOCs, which collectively caused their continuance intention of MOOCs. The results support all proposed hypotheses, and the research model accounts for 75.6% of the variance in learners' continuance intention of MOOCs.Originality/valueThis study uses the S-O-R model as a theoretical groundwork to construct learners' continuance intention of MOOCs as a series of the internal process, which is influenced by network externality, gamification and media richness. Noteworthily, three psychological constructs, behavioral LE, emotional LE and social LE, are employed to represent learners' organisms of MOOCs usage. To date, the concepts of network externality, gamification and media richness are rarely together adopted as environmental stimuli, and psychological constructs as organisms have received lesser attention in prior MOOCs studies using the S-O-R model. Hence, this study's contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners' continuance intention of MOOCs is well documented.
{"title":"To continue or not to continue? Examining the antecedents of MOOCs continuance intention through the lens of the stimulus-organism-response model","authors":"Yung-Ming Cheng","doi":"10.1108/ijilt-08-2022-0171","DOIUrl":"https://doi.org/10.1108/ijilt-08-2022-0171","url":null,"abstract":"PurposeThe purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to test whether network externality, gamification and media richness as environmental feature antecedents to learners' learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs).Design/methodology/approachSample data for this study were collected from learners who had experience in taking the gamified MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 315 usable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study verified that learners' perceived network externality, gamification and media richness in MOOCs positively influenced their behavioral LE, emotional LE and social LE elicited by MOOCs, which collectively caused their continuance intention of MOOCs. The results support all proposed hypotheses, and the research model accounts for 75.6% of the variance in learners' continuance intention of MOOCs.Originality/valueThis study uses the S-O-R model as a theoretical groundwork to construct learners' continuance intention of MOOCs as a series of the internal process, which is influenced by network externality, gamification and media richness. Noteworthily, three psychological constructs, behavioral LE, emotional LE and social LE, are employed to represent learners' organisms of MOOCs usage. To date, the concepts of network externality, gamification and media richness are rarely together adopted as environmental stimuli, and psychological constructs as organisms have received lesser attention in prior MOOCs studies using the S-O-R model. Hence, this study's contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners' continuance intention of MOOCs is well documented.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44449095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-15DOI: 10.1108/ijilt-02-2023-0020
Martin Bean, Sheryl Grant, Glenn Hardaker, Rupert R. Ward
PurposeAlternative credentials are rapidly evolving. The purpose of this paper is to explore the challenges and opportunities arising from this evolution with particular reference to their role in education and employment.Design/methodology/approachThe paper explores the credential initiatives with a unique perspective from introducing alternative credential initiatives that have been influential in recent national policy developments. The paper is led by the experiences of the former General Manager of Microsoft's Education Products Group, former Vice-Chancellor of The Open University and the Royal Melbourne Institute of Technology University. His experiences and lessons learnt reflecting on alternative credential development during the last 30 years provides a unique insight in seeing the “signals” and moving beyond the “noise” of micro-credentials for successful integration into educational institutions.FindingsA number of key findings are identified in terms of current development challenges that impact on alternative credential use and identifying further developments. Relevant examples and references are provided throughout, with a particular focus on North America, Europe and Australasia where the most progress has been made in alternative credentials.Research limitations/implicationsImplications for those wishing to develop badging and microcredentialing solutions, especially in higher education, are identified for all seeking to maximise the success of alternative credential systems.Originality/valueMartin Bean has a unique perspective having explored credential initiatives whilst General Manager of Microsoft's Education Products Group and whilst Vice-Chancellor of The Open University and the Royal Melbourne Institute of Technology University. Martin Bean has also been influential in recent national policy developments in Australia. Martin Bean’s experiences and lessons learnt witnessing alternative credential development during the last 30 years across three continents, and within both public and private sectors, are summarised here to provide context for discussions of some of the key global concepts and related work.
{"title":"Signals and noise: communicating achievement through alternative credentials","authors":"Martin Bean, Sheryl Grant, Glenn Hardaker, Rupert R. Ward","doi":"10.1108/ijilt-02-2023-0020","DOIUrl":"https://doi.org/10.1108/ijilt-02-2023-0020","url":null,"abstract":"PurposeAlternative credentials are rapidly evolving. The purpose of this paper is to explore the challenges and opportunities arising from this evolution with particular reference to their role in education and employment.Design/methodology/approachThe paper explores the credential initiatives with a unique perspective from introducing alternative credential initiatives that have been influential in recent national policy developments. The paper is led by the experiences of the former General Manager of Microsoft's Education Products Group, former Vice-Chancellor of The Open University and the Royal Melbourne Institute of Technology University. His experiences and lessons learnt reflecting on alternative credential development during the last 30 years provides a unique insight in seeing the “signals” and moving beyond the “noise” of micro-credentials for successful integration into educational institutions.FindingsA number of key findings are identified in terms of current development challenges that impact on alternative credential use and identifying further developments. Relevant examples and references are provided throughout, with a particular focus on North America, Europe and Australasia where the most progress has been made in alternative credentials.Research limitations/implicationsImplications for those wishing to develop badging and microcredentialing solutions, especially in higher education, are identified for all seeking to maximise the success of alternative credential systems.Originality/valueMartin Bean has a unique perspective having explored credential initiatives whilst General Manager of Microsoft's Education Products Group and whilst Vice-Chancellor of The Open University and the Royal Melbourne Institute of Technology University. Martin Bean has also been influential in recent national policy developments in Australia. Martin Bean’s experiences and lessons learnt witnessing alternative credential development during the last 30 years across three continents, and within both public and private sectors, are summarised here to provide context for discussions of some of the key global concepts and related work.","PeriodicalId":51872,"journal":{"name":"International Journal of Information and Learning Technology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41245659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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