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Priyono Tri Febrianto
Trunojoyo University
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Social Sciences Other

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The Enterprise School Readiness Prediction System (ESRPS) Uses Machine Learning to Assess Children's Readiness for Entering Elementary School Muhammad Choerul Umam; Cicilia Dyah Sulistyaningrum I.; Dydik Kurniawan; Priyono Tri Febrianto
Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Vol 10, No 4 (2024): December
Publisher : Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jk.v10i4.13488

Abstract

This study aims to develop and evaluate the Enterprise School Readiness Prediction System (ESRPS) to predict children's readiness for elementary school using machine learning algorithms.  This research employs the Research and Development (R&D) method using Borg and Gall’s model and Instruments include questionnaires, programming tools, performance evaluation metrics, and web/database development tools to ensure the system's validity, reliability, and practical applicability.The research analyzes data from 300 students in various Indonesian cities, focusing on attributes like age, gender, and parental education. The system implements four algorithms: Decision Tree, Random Forest, Naive Bayes, and SVM. Data preprocessing, model training, and hyperparameter tuning were conducted, followed by evaluation using metrics like accuracy and precision. A web-based application was developed for user interaction and deployment. The result showed that the Decision Tree and Naive Bayes algorithms achieved the highest accuracy at 55%, followed by SVM at 50%, and Random Forest at 45%. This suggests that simpler models may be more suitable for the dataset's characteristics. The system also demonstrated the feasibility of practical deployment for educational use. The study concludes that ESRPS effectively uses machine learning to assess school readiness, highlighting the value of data preprocessing and model tuning in enhancing accuracy. Despite moderate accuracy levels, the study confirms the system's potential for aiding educators and parents in supporting children's transition to school.
The Enterprise School Readiness Prediction System (ESRPS) Uses Machine Learning to Assess Children's Readiness for Entering Elementary School Umam, Muhammad Choerul; Sulistyaningrum I., Cicilia Dyah; Kurniawan, Dydik; Febrianto, Priyono Tri
Jurnal Kependidikan : Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran, dan Pembelajaran Vol. 10 No. 4 (2024): December
Publisher : LPPM Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jk.v10i4.13488

Abstract

This study aims to develop and evaluate the Enterprise School Readiness Prediction System (ESRPS) to predict children's readiness for elementary school using machine learning algorithms.  This research employs the Research and Development (R&D) method using Borg and Gall’s model and Instruments include questionnaires, programming tools, performance evaluation metrics, and web/database development tools to ensure the system's validity, reliability, and practical applicability.The research analyzes data from 300 students in various Indonesian cities, focusing on attributes like age, gender, and parental education. The system implements four algorithms: Decision Tree, Random Forest, Naive Bayes, and SVM. Data preprocessing, model training, and hyperparameter tuning were conducted, followed by evaluation using metrics like accuracy and precision. A web-based application was developed for user interaction and deployment. The result showed that the Decision Tree and Naive Bayes algorithms achieved the highest accuracy at 55%, followed by SVM at 50%, and Random Forest at 45%. This suggests that simpler models may be more suitable for the dataset's characteristics. The system also demonstrated the feasibility of practical deployment for educational use. The study concludes that ESRPS effectively uses machine learning to assess school readiness, highlighting the value of data preprocessing and model tuning in enhancing accuracy. Despite moderate accuracy levels, the study confirms the system's potential for aiding educators and parents in supporting children's transition to school.
Co-Authors 'Ayun, Dya Qurotul Ade Cyntia Pritasari Ade Cyntia Pritasari Ade Irma Damayanti Aditya Dyah Puspitasari Aditya Dyah Puspitasari Adji Setyorini, Devi Agustin, Putri Prihandini Agustina, Rufaydah Aidah Fatin, Rifka Ainia, Carryna Zalfa Ainur Rasikin, Muhammad Ainurramadhani, Imelda Eka Aisyah Noviyanti, Nur Ali Maksum Alya Agustina, Dea Anam Wijaya, Fahriz Andika Adinanda Siswoyo Andina, Aizza Naya Arum Budiastuti, Arum Budiastuti Arwinda, Vivi Prila Asbah Binti Razali Asbah Binti Razali Assayyidah, Jasmine Atika, Putri Aulia, Marsha Awalia , Tia Izzatul Ayu Puspita, Julia Ayu Ramanda Putri, Inessya Bachtiar Sjaiful Bachri BACHTIAR SYAIFUL BACHRI Bekiyatus Solehah Catharina Indah Kartika Cicilia Dyah Sulistyaningrum I. Desy Elvira Wulandari Dwi Elsa Romadhoni Dwi Rahmah, Alisyah Dwi Safitri Dwiyanto, Febri Dzofiroh, Amirotudz Eky Junnata Marianadya Sukadi Elsa Safila, Amanda Fadila, Anisa Nur Faizatul Hasanah Fara Medinna Oktavia Faradiba Rohadatul Aisy Fatimah Azzahra Fatiya Auliya Firdaus, Adella Tiara Bintara Firdausi Nurharini Firdausi Nurharini Firmansyah, Muhammad Bagus Hamim Mullah Wahyu Ramadhan Hana Naina Hanum Eka Pratiwi , Citra Helmia, Indi Hoiris Zuhro, Istihana Husnul Jannah Alfauzah Indahsari Indrayani, Vindy Indun Bi Wastuti Inggrid Adithalia Irena Yolanita Maureen Isna Aniqotun Nada Izmatul Mufidah Jasmine Assayyidah Jumiyati Kamilah , Mahsa Khoirunisa, Dinda Salsabila Khoirus Tsani, Mutiara Khusna, Mufidatul Khusna, Mufidatul Khusnah, Aprilia Nurul Khusnul Laili Mansuroh Kurniawan, Dydik LAMIJAN HADI SUSARNO Lina Anggraini Lola Viska Ardani Luluk Lailatul Mukarromah Lutfi Apreliana Megasari Lutfi Apreliana Megasari Lutfi Apreliana Megasari Lutfi Apreliana Megasari Mafrichatuz Zuhroh Maghfirli Islami, Sabrina Maharani, Putri Aulia Mas'udah, Siti Maulana, M. Nur Afifudin Dwi Mauliddiyah, Luluk Maulidiya, Zamrotun Mega Kalista, Zulfia Merlia Indah Prastiwi Merlia Indah Prastiwi Merlia Indah Prastiwi, Merlia Indah Mirza Mutiara Maulisa Insani Mochamad Nursalim Mohammad Edy Nurtamam Mohassin Mufidatul Khusna Muhamad Zakhi Ramadhan Muhammad Choerul Umam Muhammad Fahmi Amrullah Mustikasari , Sevia Dwi Nabila, Alifia Filza Nadia Putri Nanda Dwi Saharani, May Nilamsari Damayanti Fajrin Noverawati Syah Fitri Novia Safitri, Narulita Novianti Romadani Novita, Tri Nur Choyyina, Avin Nur Diana Firdaus Nur Rohmah, Eva Nurharini, Firdausi Nurul Fauziyah, Vita Nuudiya Anburika Puspita, Julia Ayu Putra, Moh Vikram Dwi Putri Faridatus Sholeha Putri Nabiella Fitri Rahmadhani Putri, Aqsha Maulidiyah Qodaria, Rizka Lailatul Rafiqa Dzurriyya Rahmadani, Arifatin Rosichah Ramadhani , Nanda Octavia Ramawati, Mei Ika Ramzi Albani Thariq Razali, Asbah Reftamey, Cinta Reva Amelia Ricca Aulia Rahma Rifatil Badri, Zafirah Rizky Dellentya Rizqillah, Ahmad Fajar Ridha Romadhon, Moh. Sulaiman Sabri Sulaiman Sahlya, Zulfatus Salsabila Damayanti Sandro Jadi Marulitua Nadeak Sari Devi, Kartika Saropah, Siti Sauqi, Iqbal Sayyidati Beta Masbaha Azzahroh Seftinengseh, Nurjihan Shinta Nuriah Shofiyati Fadilah Siti Chomsiyatul Ma'rifah Siti Masitoh Siti Salamah Solikhah, Makhfudhotus Sri Wilda Ningsih ST. Shafiyatul Hasanah Sudarso Sudarso Sudarso Sudarso SUKMAWATI, DWI Sulaiman Sulaiman Sulaiman Sulaiman Sulaiman, Sabri Sulistyaningrum I., Cicilia Dyah Syafrilla Faigha Utami Syafrilla Faigha Utami Syaifullah Alramadhani Tasya Permata Islami Tiara Bintara Firdaus, Adella Tri Nidia Kusumawardani Tsabitah, Ismi Tsabitah, Yasmin Mumtaz Uliatul Murtasidah Umam, Muhammad Choerul Umi Hanik Vero Stantika Wahyudi, Adisti Istivari Wahyuni, Esa Nur Warosatul Amalia Widayanti , Hesti Wahyu Yudha Aldetya Fanda Febriarta Zainur Rohman