Tahani model of fuzzy database for an adaptive metacognitive scaffolding in Hypermedia Learning Environment (Case: Algorithm and structure data course)

Nurlayli, Akhsin; Adji, Teguh Bharata; Permanasari, Adhistya Erna; Hidayah, Indriana

doi:10.1109/siet.2017.8304164

Cited by 5 publications

(5 citation statements)

References 30 publications

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“…Berdasarkan hasil pengembangan sistem, masih terdapat kekurangan, seperti sistem yang dibangun tidak adaptif mengikuti tingkat kognisi pengguna [16]. Sistem lain yang telah dikembangkan adalah self-regulated learning system with rule-based learning diagnostic scheme (SRLS-RLDS) [17] dan Adaptif HLE [18], [19]. Kedua sistem yang dikembangkan telah mengusung konsep adaptif menggunakan scaffolding.…”

Section: Pendahuluanunclassified

“…Dalam SRLS-RLDS [17], digunakan algoritme inferensi berbasis aturan untuk menentukan scaffolding pada setiap proses belajar mahasiswa dengan SRL. Penilaian kemampuan awal mahasiswa didasarkan pada evaluasi yang diperoleh guru sehingga diperoleh rule set yang telah ditentukan, sedangkan sistem adaptif HLE [18], [19] membuat scaffolding adaptif berdasarkan kategorisasi kemampuan metakognisi mahasiswa dan aktivasi pengetahuan sebelumnya (PKA). Keterampilan metakognisi diperoleh dari pengisian angket metacognitive awareness inventory (MAI) dan nilai PKA pada awal mahasiswa menggunakan sistem.…”

Section: Pendahuluanunclassified

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Pengembangan Hypermedia Learning Environment (HLE) untuk Meningkatkan Self-Regulated Learning Berdasarkan Kemampuan Self-Monitoring

Sakkinah

Hartanto

Permanasari

2022

JNTETI

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Penggunaan media pembelajaran saat ini telah berkembang pesat. Dewasa ini banyak penelitian yang menggunakan komputer sebagai media pembelajaran yang adaptif bagi mahasiswa; salah satu contohnya adalah hypermedia learning environment (HLE). Media HLE dikembangkan untuk membantu mahasiswa dalam belajar, misalnya pada situasi pandemi COVID-19 saat ini, yang mengharuskan semua aktivitas pembelajaran dilakukan secara daring (online). Salah satu bidang yang terkena dampak pandemi ini adalah bidang pendidikan, yaitu semua kegiatan pembelajaran dialihkan menjadi daring. Oleh karena itu, pembelajaran berbasis web HLE dapat membantu mahasiswa untuk tetap belajar dari rumah. HLE saat ini sedang dikembangkan untuk meningkatkan kemampuan mahasiswa dalam proses self-regulated learning (SRL). Ada komponen penting di dalam SRL, yakni self-monitoring. Namun, dalam perkembangannya, HLE yang dikembangkan tidak berbasis self-monitoring. Dalam penelitian ini, HLE adaptif dikembangkan berdasarkan kemampuan self-monitoring mahasiswa. Dalam pengembangannya, sistem HLE menggunakan metode pengembangan agile, yaitu Scrum. Pengumpulan data awal untuk klasifikasi mahasiswa dilakukan menggunakan self-regulatory inventory (SRI). SRI merupakan instrumen yang digunakan untuk mengukur kemampuan self-monitoring mahasiswa. Data kemudian diolah hingga dapat mengklasifikasikan siswa menjadi tiga kelas, yaitu high, medium, dan low. Hasil klasifikasi kemampuan siswa kemudian digunakan untuk mengembangkan bantuan pembelajaran pada HLE. Pengembangan bantuan yang disediakan adalah dalam bentuk teks dan video yang disesuaikan dengan tingkat self-monitoring mahasiswa. Dari hasil pengembangan, didapatkan bahwa semua fungsi HLE dapat berjalan dengan baik. Sistem diuji coba kepada dua belas mahasiswa untuk mengetahui tingkat usability dengan menggunakan system usability scale (SUS). Hasil menunjukkan kategori good, dengan skor 72,92. Untuk penelitian selanjutnya, dapat dilakukan implementasi pada mahasiswa dan mengukur keefektifan sistem yang telah dikembangkan.

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Section: Pendahuluanunclassified

Pengembangan Hypermedia Learning Environment (HLE) untuk Meningkatkan Self-Regulated Learning Berdasarkan Kemampuan Self-Monitoring

Sakkinah

Hartanto

Permanasari

2022

JNTETI

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“…Penelitian berikutnya dalam memilih susu yang paling sesuai berdasarkan nilainilai nutrisi yang dikandung susu tersebut [5]. Pengambilan keputusan secara adaptif bagi mahasiswa jurusan computer menggunakan fuzzy tahini [6].…”

Section: Pendahuluanunclassified

Sistem Rekomendasi Pembelian Sepeda Motor Bekas Menggunakan Metode Fuzzy Tahani

Murdianingsih¹,

Sitiumayah²

2020

JICT

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A used motorcycle is an option in the quest to buy a motorcycle, reliability is one factor. Accessibility means the size and the sum of the installment. Affordability is very important given the Covid-19 pandemic and economic recession, particularly in an environment of economic downturn. This research aims to establish a used motorcycle purchase recommendation system using the year's criteria for the manufacture of used motorcycles, prices,Â and installments in the purchase of used motorcycles, as well as to assess how high the reliability of the used motorcycle purchase recommendation system is. Firstly, twenty used motor data were obtained which were used to analyze recommendations, secondly to determine the domain size, thirdly to determine the function and degree of membership for each parameter, fourth to measure fire intensity and fifth to determine recommendations for the purchase of used motorbikes. Testing device reliability using the MAE tool. The framework was implemented using the interface MySQL DBMS and PHP. Using the Fuzzy Tahani method, the search for used motorbikes can be carried out, with the benefit of providing the installment quantity parameter and fifty-eight percent of the device reliability for buying used motorcycles. Â

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“…Previously, an MTS which is aimed to support students in learning algorithm and data structure was developed. The developed MTS provides some different learning strategies, namely drawing, summarizing, and controlling video to be used by students according to their individual preference (Nurlayli, Adji, Permanasari, & Hidayah, 2017). The first learning strategy, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, students are encouraged to identify the best strategy for each of them. However, it is found in the testing phase that students need a learning strategy recommendation system to further support their learning (Nurlayli, Adji, Permanasari, & Hidayah, 2017). It is expected that the system can provide insight of the most appropriate strategy for each student in practicing metacognition and self-regulated skills in the learning process.…”

Section: Introductionmentioning

confidence: 99%

Development of Learning Strategy Recommendation System to Train Metacognition and Self-Regulated Learning in Algorithm and Data Structure Course

Indriana

Setio

Rahmawati³

et al. 2019

ICEAP Proceeding 2019

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Metacognitive training system (MTS) which is developed for Algorithm and Data Structure course facilitates students to choose, use, and evaluate different learning strategies. Therefore, students are encouraged to be self-regulated. However, the system is also expected to know the best learning strategies of students to generate recommendation that will help students to better understand their self. The recommendation is generated by using various parameters such as post-test scores, learning strategy evaluation values, learning strategy access time, number of clicks and number of summary words to determine the best level of metacognition and learning strategies for students. The learning strategy recommendation system developed using Simple Additive Fuzzy Weighting Algorithm. This method adds the weight of each criterion in each learning strategy. The system's functionality is tested using Black Box method as well as validated by experts. A user acceptance test (UAT) is also carried out to prove that the system is accepted by users and requirements have been met. The UAT resulted in an average of 82.5% which is considered as very good.

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Tahani model of fuzzy database for an adaptive metacognitive scaffolding in Hypermedia Learning Environment (Case: Algorithm and structure data course)

Cited by 5 publications

References 30 publications

Pengembangan Hypermedia Learning Environment (HLE) untuk Meningkatkan Self-Regulated Learning Berdasarkan Kemampuan Self-Monitoring

Pengembangan Hypermedia Learning Environment (HLE) untuk Meningkatkan Self-Regulated Learning Berdasarkan Kemampuan Self-Monitoring

Sistem Rekomendasi Pembelian Sepeda Motor Bekas Menggunakan Metode Fuzzy Tahani

Development of Learning Strategy Recommendation System to Train Metacognition and Self-Regulated Learning in Algorithm and Data Structure Course

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