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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Pekommas Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Jurnal Teknologi Informasi dan Komunikasi Sistemasi: Jurnal Sistem Informasi Jurnal Teknik Komputer AMIK BSI Ilmu Budaya: Jurnal Bahasa, Sastra, Seni, dan Budaya Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Eksplora Informatika Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi J I M P - Jurnal Informatika Merdeka Pasuruan JURNAL PENDIDIKAN TAMBUSAI JKM (Jurnal Kebidanan Malahayati) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Informatika Global Jurnal Tekno Kompak MULTINETICS Journal of Information Systems and Informatics Babali Nursing Research Indonesia Berdaya MAHESA : Malahayati Health Student Journal JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Al-MIKRAJ: Jurnal studi Islam dan Humaniora Jurnal PADAMU NEGERI (Pengabdian pada Masyarakat Bidang Eksakta) Jurnal Pendidikan Matematika Malikussaleh Jurnal Pengabdian Masyarakat Bhinneka INCOME: Indonesian Journal of Community Service and Engagement Jurnal Informatika: Jurnal Pengembangan IT CSRID Jurnal Pengabdian Masyarakat (JURDIMAS) DIPANEGARA KOMPUTER TEKNOLOGI INFORMATIKA (DIPAKOMTI) DIPANEGARA KOMPUTER SISTEM INFORMASI (DIPAKOMSI) Al-Ijtimā: Jurnal Pengabdian Kepada Masyarakat JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of Information Technology and its Utilization
Rismayani Rismayani
Universitas Dipa Makassar
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Journal : Journal of Information Technology and its Utilization

 1 
Model-View-Controller Design System of Motorcycle Damage Detection Using Forward Chaining Method Rismayani Rismayani; Muhammad Wahinuddin Tahir; Muhammad Darwis; Nurani Nurani; Martina Pineng
Journal of Information Technology and Its Utilization Vol 6 No 2 (2023): December 2023
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.6.2.5230

Abstract

This study aims to design a motorbike damage detection system using the forward chaining method with a view controller model that can be run on a mobile-based system. Dealers and motorbike service providers receive and fulfil customer requests for motorbike service services. Mechanics who service vehicles still use conventional methods to check vehicle damage by scanning the paper (form). There is a list ofvehicle damage. This method takes quite a long time, and it is not sure that the problem will be resolved quickly. The research method used is forward chaining, and the model used is the Model View Controller, which separates data from the display by processing it. The result of this research is that with a motorbike damage detection system, mechanics from dealers and service areas do not have to carry out initial checks manually but instead use a system with a view controller model and initial check results. Detection can also be determined by applying the forward chaining method. Based on functional testing of the system using a black box, valid results were found; then, for logic testing using the forward chaining method, the results were free from logical errors.
Learning Difficulty Levels Prediction of Elementary School Student Mathematics Using Machine Learning Model Rismayani, Rismayani; Sambo Layuk, Novita; Patasik, Madyana; Endang, Andi Hutami
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.5906

Abstract

Difficulty learning mathematics in elementary school students is a significant problem and requires serious attention. This study aims to predict the difficulty level in elementary school students learning mathematics using a machine learning model, namely KNN. Exam scores, assignments, quizzes, and characteristics of students' difficulty level in learning mathematics were used as data in this study. A study used the KNN model to divide students into three categories of difficulty in learning mathematics: easy, moderate, and challenging. The results showed that the KNN model can accurately predict student’s difficulty levels in mathematics. Thus, applying this model can help teachers provide appropriate and effective interventions to students experiencing difficulties. Using machine learning technology, especially the KNN model, we found an accuracy of 95%. In addition, we can still accurately predict the difficulty level of elementary school students' mathematics learning. This study uses anonymous student data, the distribution of assignments, quizzes, and exam score ranges, and characteristics of mathematics learning difficulty levels. There are three prediction classes: high, medium, and low.
Co-Authors Abidin, Nur Awalia Syukri Zainal Ahmad Ramadhan Ahyuna Ahyuna, Ahyuna Aklimawati Aklimawati, Aklimawati Al Farizi, Muhammad Alam, Samsul Aldi Susanto Alfandy, Andi Faiz Andi Hutami Endang, Andi Hutami Andi Irmayana Annah Annah, Annah Ardimansyah Ardimansyah Arief Setyanto Arifin, Ismail Arlenti, Lety Arnold Listanto Pratama Arudji Hermatyar Asmanurhidayani, Asmanurhidayani Asrul Syam Asrul Syam Asti Rahayu Arjuni Aswar TC. Koswara Avila, Rizna Dwi Chandreekha Ummareng Cucut Susanto Edi Susilo Elcindy Putri Mangadi Elvina, Ade Ema Utami Entan Afriannisyah Erdianza, Noor Fadhilah, Meirah Fadhlullah, Muhammad Alief Fahmi Satriawan Taslim Febrianti, Anggi Ferdiansyah Noor Alief Gosari, Nero Caesar Hani, Siti Umi Harlina, Sitti Hartana Wali Hasibuan, Riza Sakhbani Hasriani Hasriani Hasyrif SY Hasyrif SY Hasyrif SY Heltiani, Nofri Hendayani, Veli Sifa Hendri Bustamam Herlinda Herlinda, Herlinda Hermatyar, Arudji Imran, Irfina Astria Indo Intan Irma Suryani Irsan Mansyur Iskandar Iskandar Jasman, Taufik Zulhaq Keziah Julia Siow Layuk, Novita Sambo Linshia, Linshia Lubis, Hilda Zahra M. Syabur Feryson Pilat Madyana Patasik Mahaputri, Amanda Ulayyah Mahrim, Andes Saparila Maria Yustina Tuga Martina Pineng Maulana, Andi Ikram Maulani, Nurul Mawarni Mawarni Mirfan Mirfan muh Rinalwi Muh Yusuf Zahir Muhammad Agus Muljanto Muhammad Alief Fadhlullah Muhammad Alim Rahmat Muhammad Ardiansyah Muhammad Darwis Muhammad Kasrun Muhammad sabiq Muhammad said Muhammad Syukri Mustafa Muhammad Wahinuddin Tahir Muliana, Muliana Mursalim Mursalim Muthahharah Muthahharah MZ, St. Naziha Nasif Nababan, Lolli Nabia, Wasiatul Nadia Ananda Nasution, Dinil Arifah Natasya Putri Rantelino Ni Kadek Marselina Novita Sambo Layuk Nurani Nurani Nurani Nurani Nurani Nurani Nurcahyani Syamsu Nurdiansah Nurdin Nurdin Nurhaeni F Nurilmi Amalia Marda Nurisnaini, Gianti Nurlindasari Tamsir Oktavia, Rara Parwito Parwito, Parwito Petronilia Palinggik Allorerung Piu, Sriwahyuningsih Poppy Siska Putri Pratama, Arnold Listanto PURWANTI PURWANTI Putri, Ayilzi R, Agum Wiranto Rahmaliza, Rahmaliza Rambe, Aisyah Putri Reski Ariani Reza Afandi Rima Aprilia Riska Anita Rahayu Rita, Wismalinda Rizky Amalia Rizna Dwi Avila Rudyanto Salam Safaat, Syahrial Sandy, Wilson Siti Aisa Siti Aisyah Sri Rahayu N Sitti Asnany Sri Marliani Sri Wahyuni ST. Aminah Dinayati Ghani Suhardi Aras Sutanto, Nur Hamid Sutri Yani Syafitasari, Juanda Tahir, Muhammad Wahinuddin Tandiar, Brayens Taufik Zulhaq Jasman Tiwi Nurhidayatullah Tommy Darwansyah Tulwahdah, Farida Usman, SE., M.Kom Usman, SE., M.Kom Vitha Aulia Nurwardhani Yunus Wal Ikram Widyaa, Syahruni Widyaningsih, Sari Wiwik Handayani Yudi Heriadi Yusdarly, Yusdarly