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All Journal Jurnal Dedikasi Sosioinforma Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Muaddib : Studi Kependidikan dan Keislaman JTERA (Jurnal Teknologi Rekayasa) Prosiding Seminar Nasional Teknoka Indonesian Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Informatika Universitas Pamulang Sebatik JURIKOM (Jurnal Riset Komputer) Multitek Indonesia : Jurnal Ilmiah Legal Standing : Jurnal Ilmu Hukum KOMPUTEK J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Tekno Kompak International Journal of Industrial Optimization (IJIO) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Responsif : Riset Sains dan Informatika International Journal of Community Service EXPLORER Society: Jurnal Pengabdian Masyarakat International Journal Artificial Intelligent and Informatics Jurnal Komtekinfo Journal of Software Engineering and Information System (SEIS) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) AMMA : Jurnal Pengabdian Masyarakat Journal of Engineering and Technological Sciences Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika
Ida Widaningrum, Ida
Program Studi Teknik Informatika Universitas Muhammadiyah Ponorogo
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Implementation of The Certainty Factor Method in The Expert System For Early Diagnosis of Dyslexia in Childhood Ashidiqi, Ahmad Siroj; Widaningrum, Ida; Karaman, Jamilah
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 1 (2023): February 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i1.18433

Abstract

Dyslexia is a condition in which a person has difficulty (especially) in areas related to learning abilities such as reading, writing, and arithmetic or matters relating to numbers. This condition is not the skills expected of people with chronological age and normal intelligence abilities or IQ (quality of intelligence). This condition is sometimes not realized by parents and only consider their child slightly delayed, even though it is under standard (minimum) abilities at his age. Therefore, a platform using an expert system with the Certainty Factor method was created to help parents detect early whether their child has dyslexia or not and find out what type of dyslexia the child is experiencing. The types of dyslexia that will be included in this study include surface dyslexia, phonological dyslexia, rapid naming deficit, dysgraphia, and dyscalculia. The white box results found that the system was in line with expectations because it had a low level of risk.
Penggunaan Metode AHP (Analitycal Hierarchy Process) Untuk Menentukan Lokasi Wisata Yusuf, Moch Yasir; Karaman, Jamilah; Widaningrum, Ida; Astuti, Arin Yuli; Sucipto , Sucipto
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 7 No. 1 (2023): PROSIDING NSEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v7i1.3434

Abstract

Indonesia terkenal dengan berbagai tempat wisata yang menarik dan menjadi ikon dari daerah tersebut. Keunggulan dan kelebihan dari tempat wisata tersebut akan membingungkan orang yang akan melakukan perjalanan wisata. Biasanya pemilihan tempat wisata yang akan dikunjungi berdasarkan tema yang diinginkan, biaya yang dibutuhkan, fasilitas yang ditawarkan, jarak dan waktu yang diperlukan. Penelitian ini menawarkan sebuah sistem yang akan membantu menentukan lokasi wisata yang sesuai dengan keinginan calon wisatawan. Lokasi wisata fokus tempat wisata yang ada di Pulau Jawa saja. Metode yang digunakan dalam menentukan tempat wisata adalah AHP (Analitychac Hierachy Process). Metode AHP melakukan perbandingan berpasangan dalam perhitungannya, dan output-nya berupa rekomendasi alternatif berupa perangkingan.
Pengembangan Sistem Pendukung Keputusan Berbasis Machine Learning untuk Prediksi Kinerja Dosen Menggunakan Data Historis Evaluasi Pembelajaran Z, Ismail Abdurrozzaq; Widaningrum, Ida; Litanianda, Yovi
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9363

Abstract

Lecturer performance evaluation is a crucial component in efforts to improve the quality of higher education. However, traditional evaluation methods still face various challenges, such as subjective assessments, a lack of consistent standards, and lengthy decision-making processes. These conditions highlight the need for a more measurable, accurate, and data-driven evaluation mechanism, particularly in the context of ongoing digital transformation. This study aims to design and develop a lecturer performance prediction system using a machine learning (ML) approach within a Decision Support System (DSS) framework. The research approach involves processing historical lecturer data covering aspects of Teaching (including student evaluation scores, instructional innovation, and attendance levels), Research (number of publications, H-index, and participation in academic conferences), Community Service, and other administrative activities. Predictive models were developed and compared using several machine learning algorithms, namely Random Forest, Support Vector Machine (SVM), Multilayer Perceptron (MLP), and XGBoost. Experimental results show that Random Forest achieved an accuracy of 88.0%, SVM 85.0%, and MLP 87.0%, while XGBoost demonstrated the best performance with an accuracy of 92.0%, precision of 91.0%, recall of 90.0%, and an F1-score of 91.0%. Based on these results, XGBoost was selected as the primary model for the DSS. In addition, the system is equipped with a rule-based module that generates follow-up recommendations based on the model’s prediction results. All system components are implemented in an interactive dashboard using the Streamlit framework, enabling users to input data, monitor prediction outcomes, and obtain decision recommendations in a fast and data-driven manner.
Co-Authors ., Sugianti Abd. Rasyid Syamsuri abdurrouf Abdurrouf Adi Purwanto Adi Purwanto Agus Hening Triwasono Akzha Nabella Putra Arganata Al-Rizki, Muhammad Farid Iqbal Ali Selamat Ali Selamat Andy Triyanto Angga Prasetyo Ardio, Karisma Arief Budiono Arifin, Rizal Arifin, Rizal Ashidiqi, Ahmad Siroj Astuti, Arin Yuli Azizah, Hanifha Nur Bambang Widiyahseno Bambang Widiyahseno, Bambang Darminto . Deviardia Putri Nurmayasari Diah Ervin Arlindila DickiPrabowo, Reza Dinda Septyana Dita Puspitasari, Nita Dwiki Rian Pangestu Dyah Mustikasari Dyah Mustikasari Dyah Mustikasari Ega Feri Romawati Eka Arynda Ayu, Eka Arynda Eka Febriyanti, Nuraini Ekapti Wahjuni Djuwitaningsih Erika Diyah Cahyani Fauzan, Fahrul Alvin Fitri, Khoiru Nur Ghulam Asrofi Buntoro Gita Lely Endika Putri Hardi Prasetiyo Ika Nurjanah Indah Puji Astuti Indah Puji Astuti Indah Puji Astuti Isnandar, Aries Jamil, Salma Fauziyah Jamilah Karaman Johari, Norhasnidawani Karaman, Jamilah Khoiru Nur Fitri Khoiru Nurfitri Khoiru Nurfitri Kusnawan, Wawan Lee, Vannajan Sanghiran Lestari, Erma Puji Lestari, Riza Ayu Mohammad Bhanu Setyawan Muhammad Farid Iqbal Al-Rizki Muhammad Titan Rama Adi Wijaya Muthya Cahyani Putriabhimata Muzakki, Fikrun Najib Nadia Intan Pratiwi Neni Berlian, Munika Nurfitri, Khoiru Pratiwi, Nadia Intan Puji Astuti, Indah Rahmatika Az-Zahra, Rifqi Rendy Ahmadan Abdul Aziz, Maretha Rhesma Intan Vidyastari Rifqi Rahmatika Az-Zahra Rika Maya Sari Roziqin, Bahar Rudianto Karim Rudianto Rudianto Rudianto Rudianto Setya Ramadhani, Umi Sri Winiarti Sucipto , Sucipto Sucipto Sucipto Sugianti, Sugianti Tien Rubiyanti Tsaqila, Siti Lathifah Verian Dwi Saputra, Rezano Winardi, Yoyok Wunikaresti, Sari Yovi Litanianda, Yovi Yusuf, Moch Yasir Z, Ismail Abdurrozzaq Zulkarnain, Zulkarnain