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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi DINAMIKA DOTCOM Prosiding SNATIKA Vol 01 (2011) POSITIF Jurnal Kajian Pembelajaran Matematika JMPM: Jurnal Matematika dan Pendidikan Matematika Jurnal Manajemen Informatika Building of Informatics, Technology and Science Jurnal Karinov Scientific Journal of Informatics International Journal of Insights for Mathematics Teaching (IJOIMT) Indonesian Values and Character Education Journal Jurnal Pengabdian Masyarakat Asia Jikom: Jurnal Informatika dan Komputer Jurnal Sistem Komputer Asia Jurnal ilmiah teknologi informasi Asia
Puji Subekti
Institut Teknologi Dan Bisnis Asia Malang
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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Enhancing Literacy and Numeracy through Inquiry-Based Learning: The Impact of E-Lens as an Innovative Board Game Subekti, Puji; Rahayu, Widya Adhariyanty
Indonesian Values and Character Education Journal Vol. 7 No. 2 (2024): October
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ivcej.v7i2.83964

Abstract

The problem faced is the low literacy and numeracy skills of students, which pose a challenge for conventional teaching methods. This study aims to analyze the effectiveness of the inquiry-based learning game, E-Lens, in improving students' literacy and numeracy. The study employs a quasi-experimental design with pre-test and post-test methods, involving two groups: the experimental group using E-Lens and the control group using conventional teaching methods. The instruments used include literacy and numeracy tests, questionnaires, and classroom observations. Data were analyzed using statistical analysis, including ANCOVA, to compare the results between the two groups. The findings show that the use of E-Lens significantly improves students' literacy and numeracy compared to the control group. Statistical analysis also reveals a strong negative correlation between pre-test scores and post-test improvements, with students who initially scored lower showing greater gains. Teacher evaluations indicate that E-Lens is easy to implement and enhances student engagement. The conclusion of this study is that E-Lens has been proven effective in improving students' literacy and numeracy and can serve as an innovative solution to enhance the quality of education in Indonesia.
Pemanfaatan Metode Based Collaborative Filtering Untuk Rekomendasi Wisata Di Kabupaten Malang Mufidatul Islamiyah; Puji Subekti; Titania Dwi Andini
Jurnal Ilmiah Teknologi Informasi Asia Vol 13 No 2 (2019): Volume 13 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v13i2.70

Abstract

Tourist information in Malang district has not been widely spread on the internet, making it difficult for tourists to determine tourist destination in Malang district that will be visited. Therefore, this recommendation system was built to provide information about tourism in Malang district using the item based collaborative filtering method. The item based collaborative filtering method has the advantage of being able to increase the accuracy of the resulting object recommendations. Results from the questionnaire test that has been done, it is obtained that the tourism recommendation system is useful with the benefit level reaching 86.35% and in the item based collaborative filtering method test using the manual method in Excel and in the system produces the same predictive value namely prediction 1 with a value of 3.562, prediction 2 with a value of 3.287, and prediction 3 with a value of 1.896.
Perbandingan Metode Best Subset Dan Stepwise Untuk Mengetahui Pengaruh Tingkat Pendidikan Terhadap Pengangguran Di Jawa Timur Puji Subekti
Jurnal Ilmiah Teknologi Informasi Asia Vol 9 No 2 (2015): Volume 9 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pengangguran adalah salah satu permasalahan ekonomi yang banyak terjadi di Jawa Timur. Dewasa ini tidak sedikit dari penduduk di Jawa Timur dalam usia angkatan kerja yang tidak bekerja seperti pada umumnya. Jumlah penduduk kian hari semakin meningkat namun lapangan pekerjaan yang tersedia semakin sedikit. Data yang digunakan dalam laporan PKL ini adalah data persentase pengangguran serta persentase tingkat pendidikan terakhir di Propinsi Jawa Timur yang dirinci Menurut Kabupaten/Kotamadya. Berdasarkan hasil Analisis Regresi Linier Berganda menggunakan minitab menghasilkan hubungan yang dinyatakan dalam persamaan : Y = 11,1 - 0,0538 X1 - 0,224 X2 - 0,0003 X3 - 0,17 X4 + 0,167 X5 + 0,006 X6 dengan S= 1,73963 R-Sq = 71,1 % R-Sq (adj) = 65,5 % Dari hasil tersebut ternyata terjadi multikolinieritas. Selanjutnya akan digunakan metode Regresi Stepwise dan Best Subset untuk mengatasi kasus multikolinieritas tersebut. Dari hasil Best Subset kita peroleh persamaan baru terpilih yaitu :Y = 6,99 - 0,198 X2 + 0,164 X5, dengan R-Sq= 69,2%, R-Sq(adj)=67,5%, C-p=1,0 dan S=1,6892. Sedangkan dari hasil Stepwise kita peroleh persamaan baru terpilih yaitu : Y = 6,991 + 0,164X5 - 0,198X2 , dengan R-Sq = 69,25%, R-Sq(adj) = 67,49%, S = 1,69 dan Cp = 1,0. Pada hasil analisis proses menggunakan kedua metode diatas dapat diketahui bahwa Tingkat pendidikan SMA dan SD lebih mempengaruhi pengangguran. Sehingga diharapkan tiap-tiap sekolah khususnya di tingkat SMA/Sederajat serta SD lebih dapat meningkatkan kualitas pembelajaranya
Penentuan Model Hubungan Kepadatan Penduduk dan Faktornya Menggunakan Metode Forward Selection Subekti, Puji; Islamiyah, Mufidatul
JMPM: Jurnal Matematika dan Pendidikan Matematika Vol 2 No 1: Maret
Publisher : Prodi Pendidikan Matematika Universitas Pesantren Tinggi Darul Ulum Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/jmpm.v2i1.826

Abstract

Kepadatan penduduk adalah perbandingan antara jumlah penduduk yang tinggal di wilayah tertentu dengan luas wilayahnya. Kota Blitar adalah salah satu Kota di Jawa Timur dengan kepadatan penduduk tinggi. Banyak faktor yang mempengaruhi kepadatan penduduk suatu daerah. Dalam penelitian ini menggunakan metode Forward Selection untuk menentukan model hubungan kepadatan penduduk Kota Blitar dan faktornya.Data sekunder yang digunakan adalah data jumlah penduduk datang, penduduk pindah, penduduk mati, penduduk lahir, dan luas wilayah.Hasil pengolahan data kepadatan penduduk dan faktor-faktor yang mempengaruhinya mengalami kasus multikolinieritas. Diperoleh model persamaan regresi yang terbaik yaitu
Analisis Faktor-Faktor yang Mempengaruhi Minat Belajar Statistik Mahasiswa STMIK Asia dalam Penerapan Strategi Problem Based Learning Subekti, Puji; Hakim, Lukman; Habibi, Azwar Riza
JMPM: Jurnal Matematika dan Pendidikan Matematika Vol 3 No 2: September 2018 - February 2019
Publisher : Prodi Pendidikan Matematika Universitas Pesantren Tinggi Darul Ulum Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/jmpm.v3i2.1032

Abstract

Peneltian ini dilakukan dengan langkah-langkah penelitian eksperimental dengan tujuan untuk mengetahui faktor-faktor yang mempengaruhi minat belajar statistik mahasiswa di STMIK Asia. Dalam penelitian ini terdapat tujuh variabel bebas yang dianalisis dengan metode stepwise. Sehingga diperoleh tiga variabel bebas yang berpengaruh secara simultan diantaranya jenis kelamin, rata-rata pendapatan orang tua dan jumlah saudara, dengan model persamaan regresi berganda sebagai berikut Y= -1,260 +0,425X7 +0,511X2 + 0,417X5. Strategi yang dapat diambil dalam penerapan problem based learning adalah dengan memilih mahasiswa dalam setiap kelompok. Dengan aturan terdapat minimal satu mahasiswa laki-laki yang menjadi ketua kelompok, terdapat minimal satu mahasiswa dengan latar belakang pendapatan orang tua di atas rata-rata dan minimal satu mahasiswa yang bukan merupakan anak tunggal atau mempunyai saudara lebih dari satu.
Implementasi Metode Simple Additive Weighting untuk Menentukan Kriteria Guru Terbaik Di Smak St. Albertus Malang Subekti, Puji; Henry, Rivaldo
JURNAL SISTEM KOMPUTER ASIA Vol 2 No 1 (2024): JISKOMSIA - Volume 2, Nomor 1, Tahun 2024
Publisher : Institut Tekonologi dan Binisi Asia Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jiskomsia.v2i01.43

Abstract

Indonesia's education continues to experience commendable ranking improvements. Nevertheless, societal demands for educational quality in schools are increasingly pressuring institutions to compete in producing the best graduates. Generating high-achieving students requires high-quality educators. Therefore, a system capable of precise calculation with weighting and top priorities is necessary. One technique that can be utilized is the Simple Additive Weighting. The Simple Additive Weighting method is appropriate for addressing this issue because it enhances the accuracy of calculations by multiplying the weights of different criteria. The initial input consists of raw scores of teachers across various criteria in the school. Subsequently, Simple Additive Weighting calculates the overall assessment and displays the ranking of teachers in the school.
ObeCheck Sebagai Platform Penerapan Metode K-Nearest Neighbors untuk Klasifikasi Obesitas Berbasis Website Farihah, Lailatul; Subekti, Puji
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6726

Abstract

The increase in obesity has become one of the major challenges in the healthcare sector, requiring quick and effective solutions for early classification and diagnosis. This study aims to develop a web-based system using the K-Nearest Neighbors (KNN) method to classify obesity based on user data, thereby assisting the public in early detection of obesity. The dataset used in this research comprises 2,111 records and 17 attributes, covering various factors related to obesity, such as weight, height, age, gender, genetic factors, and lifestyle, including dietary habits and physical activity. This dataset was obtained from the UCI Repository website. The data is processed using the K-Nearest Neighbors (KNN) method to generate an accurate and relevant obesity classification model. To evaluate the performance of the K-Nearest Neighbors (KNN) model, the dataset was split into training and testing data with a ratio of 80:20 and evaluated using a Confusion Matrix, resulting in an accuracy of 89%. Since the model demonstrates good performance in classifying test data, it can be implemented as a web-based system to test new data. This system will produce weight classification results, including categories such as "Underweight," "Normal Weight," "Overweight," and "Obesity." Thus, the public can easily and accurately classify obesity using this system.
Co-Authors Adriani Kalalembang Agus Purnomo Sidi Anjaningrum, Widiya Dewi Azwar Riza Habibi, Azwar Riza Fadhli Almu’iini Ahda Farihah, Lailatul Hanif, Rifki Henry, Rivaldo Hironimus Hari Kurniawan Jaenal Arifin Justita Dura Laksono Trisnantoro Layli Dwi Rohmatunnisa Lilis Widayanti Lukman Hakim Lukman Hakim Mufidatul Islamiyah Mufidatul Islamiyah Mufidatul Islamiyah Mufidatul Islamiyah Mufidatul Islamiyah, Mufidatul mulyaningtyas, mulyaningtyas Nur Lailatul Aqromi Puspa Dewi, Mariana Setyorini Setyorini Siti Nurul Afiyah Suastika Yulia Riska Titania Dwi Andini Wa Ode Irma Sari Widya Adhariyanty Rahayu Yogatama, Ahmad Nizar