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All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal INSYPRO (Information System and Processing) Jurnal Eksplora Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Soft Computing Exploration Jurnal Tika Online Learning in Educational Research Internet of Things and Artificial Intelligence Journal Teknovokasi : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Journal of Deep Learning, Computer Vision and Digital Image Processing Jurnal Sipakatau Jurnal MediaTIK Jurnal Media Informasi Teknologi Media of Computer Science
Adiba, Fhatiah
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Pelatihan Manajemen Waktu Untuk Meningkatkan Efektivitas Profesionalisme Mahasiswa Dalam Peran Mentoring Hasnining, Ayu; Nida Rifqi, Ainun; Febriansyah Ramadhan, Haekal; Baso, Fadhlirrahman; Adiba, Fhatiah
Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Volume 2 Issue No. 2: January 2025
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/kreativa.v2i2.20261

Abstract

Pengabdian ini bertujuan meningkatkan efektivitas pengelolaan waktu mahasiswa mentor melalui pelatihan berbasis analisis kebutuhan lapangan, mengintegrasikan pendekatan Eisenhower Matrix dan Teknik Pomodoro. Metode pelaksanaan meliputi survei awal, workshop interaktif, implementasi dalam skenario mentoring nyata, evaluasi kuantitatif dan kualitatif, serta pendampingan lanjutan. Temuan utama menunjukkan adanya peningkatan pemahaman konsep manajemen waktu dan kemampuan membedakan tugas penting-mendesak pasca-pelatihan. Meskipun demikian, masih ditemukan kesenjangan antara pemahaman dan konsistensi penerapan teknik dalam praktik sehari-hari, diperparah oleh tantangan mood dan beban organisasi. Pemanfaatan teknologi digital dalam manajemen waktu juga belum optimal. Pelatihan ini berkontribusi pada pemahaman bahwa efektivitas manajemen waktu tidak hanya bergantung pada pengetahuan teknis, tetapi juga pada kemampuan internalisasi dan adaptasi. Secara praktis, diperlukan pendampingan berkelanjutan untuk membentuk kebiasaan. Secara teoretis, hasil ini mendukung pembelajaran berbasis pengalaman. Disarankan untuk pengabdian selanjutnya adalah mentoring the mentors dan evaluasi dampak jangka panjang untuk memperkuat keberlanjutan praktik.  
Learning Motivation Mediates Growth Mindset, Self-Efficacy, and AI Usefulness Impact on Programming Problem-Solving Skills Fardan, Muhammad; Fathahillah, Fathahillah; Fakhri, M. Miftach; Sanatang, Sanatang; Adiba, Fhatiah; Soeharto, Soeharto; Amukune, Stephen
Tadris: Jurnal Keguruan dan Ilmu Tarbiyah Vol 10 No 1 (2025): Tadris: Jurnal Keguruan dan Ilmu Tarbiyah
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/tadris.v10i1.23743

Abstract

Artificial Intelligence has rapidly developed, especially in education and programming, providing advantages in improving learning efficiency and personalizing educational content. This study examines the relationships between learning motivation and problem-solving skills, as well as factors influencing learning motivation, namely growth mindset, self-efficacy, and perceived usefulness of Artificial Intelligence. Data collected from 276 students were analyzed using Partial Least Squares Structural Equation Modeling. The results show that growth mindset, self-efficacy, and perceived usefulness significantly influence learning motivation. Additionally, learning motivation strongly predicts problem-solving skills in programming tasks. These findings emphasize the critical role of psychological factors in fostering learning motivation and improving problem-solving abilities within Artificial Intelligence-enhanced programming environments. This research offers valuable insights for educators and instructional designers to develop effective strategies that integrate psychological support and Artificial Intelligence tools, ultimately enhancing student learning outcomes.
AI Literacy Meets Ethics: Critical Appraisal's Mediating Role in Shaping Ethical Awareness in Higher Education Syukur, Pramudya Asoka; Fakhri, M. Miftach; Firdaus, Firdaus; Putra, Kurnia Prima; Adiba, Fhatiah; Arifiyanti, Fitria
Online Learning In Educational Research (OLER) Vol 5, No 1 (2025): Online Learning in Educational Research
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/oler.v5i1.508

Abstract

As artificial intelligence increasingly permeates higher education systems worldwide, developing students' ethical awareness has become essential for responsible AI implementation. This study seeks to examine the connections between technical understanding, applied knowledge, and critical appraisal in shaping ethical awareness within the context of AI literacy. The study utilizes a quantitative method, applying Partial Least Squares Structural Equation Modeling (PLS-SEM) to data gathered from 322 university students. The findings indicate that technical understanding has a direct favorable influence of 0.180 on ethical awareness, while applied knowledge demonstrates a stronger impact of 0.467. Critical appraisal serves as a significant complementary partial mediator, with indirect path coefficients of 0.083 for technical understanding and 0.155 for applied knowledge, strengthening their relationships with ethical awareness. This study concludes that AI literacy educational programs should not only emphasize technical and applied knowledge but also foster critical appraisal skills to promote ethical AI usage.
Recommendation of Assistant Lecturer for Advanced Programming Course using Fuzzy Tahani Amaliah, Annisa Shela; Sulmadani, Fitriah; Khaida, Fatihah; Adiba, Fhatiah; Nasrullah, Asmaul Husna; Munawir, Munawir
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.224

Abstract

The recruitment of teaching assistants for certain courses is a regular activity conducted during specific periods to meet the needs of teaching and learning both inside and outside the classroom. The main objective of the recruitment is to obtain the best teaching assistants who can perform their duties optimally. However, selecting teaching assistants based solely on grades and GPA without considering other criteria is ineffective and subjective. This research proposes the use of the Fuzzy Tahani method in a recommendation system to select teaching assistants for the Advanced Programming course. The aim is to develop a recommendation system for selecting teaching assistants using the Fuzzy Tahani method and to improve objectivity and accuracy in the decision-making process for selecting teaching assistants by considering four criteria: grades, recommendations, availability, and students' GPA. This recommendation system approach is necessary to minimize subjectivity and ensure that the selected teaching assistants can effectively carry out their duties. The result obtained is a recommendation system for selecting teaching assistants, where there is a high level of accuracy between the system's results and the calculation results in Excel, with a difference of 0.00 between them.
A Decision Support Model for Scholarship Recipient Selection Based on Tsukamoto Fuzzy Logic Muhtadi; Aksa, Muhammad; Naoval, Ahmad; Adiba, Fhatiah; Nasurllah, Asmaul Husna
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.225

Abstract

This study proposes a decision support model for scholarship recipient selection based on the Tsukamoto fuzzy logic method to overcome the inefficiencies and subjectivity inherent in manual selection processes. The model incorporates three key criteria: Grade Point Average (GPA), parents’ income, and number of dependents. Experiments were conducted using a dataset of 25 students obtained from a public Kaggle repository. The model employs fuzzification, rule formulation, and defuzzification to compute a final decision score for each applicant. The experimental results demonstrate that the proposed model achieves an accuracy rate of 92%, indicating its effectiveness in supporting objective and efficient scholarship selection decisions.
Sistem Penentuan Mahasiswa Berprestasi menggunakan metode Analytic Hierarchy Process (Studi Kasus : Fakultas Teknik UNM) Jariah, Rezki Nurul; Fadiah, Nur; Surianto, Dewi Fatmarani; Parenreng, Jumadi M; Adiba, Fhatiah
Eksplora Informatika Vol 14 No 1 (2024): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i1.1096

Abstract

Penentuan mahasiswa berprestasi merupakan langkah krusial dalam meningkatkan mutu pendidikan, namun menentukan kriteria yang sesuai dan mengukur kinerja mahasiswa secara adil dan efektif merupakan suatu tantangan. Oleh karena itu, penelitian ini bertujuan untuk mengeksplorasi serta mengimplementasikan sistem pendukung keputusan berbasis Analytical Hierarchy Process (AHP) dalam menentukan mahasiswa berprestasi di lingkungan akademik, berdasarkan empat kriteria utama yaitu nilai IPK, jumlah prestasi yang dicapai, partisipasi dalam organisasi, dan total SKS yang telah dilulusi. Hasil penelitian ini menunjukkan bahwa sistem yang dibangun mampu menentukan mahasiswa berprestasi dengan menggunakan bobot standar. Bobot tersebut dihitung berdasarkan nilai IPK minimal 3.5, jumlah prestasi minimal 2, jumlah organisasi minimal 1, dan jumlah SKS yang dilulusi minimal 85. Hasil pengujian diperoleh bahwa Metode AHP dapat diimplementasikan dalam penentuan mahasiswa berprestasi dengan tingkat usabilitas mencapai 91,63% yakni pada kategori sangat layak. Dengan demikian, penelitian ini tidak hanya mengidentifikasi masalah dalam penentuan mahasiswa berprestasi, tetapi juga memberikan solusi konkret melalui penggunaan AHP, membuktikan efektivitasnya dalam meningkatkan keakuratan dalam seleksi mahasiswa berprestasi di lingkungan akademik.
Optimasi Pemilihan Mahasiswa Berprestasi Menggunakn Metode Wp (Weighted Product) Berbasis Web Dalam Sistem Pendukung Keputusan Sumardi, Andi Mawaddah; Wadjidi, Abdul Rifai; Adiba, Fhatiah
Jurnal Tika Vol 9 No 2 (2024): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

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

Abstract

Students as learning agents and seekers of knowledge need to be encouraged to explore their potential, including in aspects of hard skills and soft skills. This research focuses on building a Decision Support System (SPK) with the Weighted Product (WP) method to determine the best students. Improving students' future existence depends not only on the excellence of hard skills, but also the balance of soft skills. The research involved four journals related to SPK student selection, and WP was chosen as an evaluation method. The research process begins with literature collection and system design, including design procedures, system usage, relationships between tables, use case diagrams, and WP method flowcharts. The implementation of the system includes a login page, input of criteria and alternative values, and the process of calculating student rankings. WP gives an accurate ranking, with Alternative 9 (Rifai) as the best student. Testing shows a high degree of accuracy between manual results and system results. This DSS provides an objective evaluation of student achievement, with the potential for further development related to data integration with academic systems and user interface improvement. The conclusion of this study is that SPK with the WP method can provide student rankings efficiently and accurately, helping to support decision making related to the selection of the best students. Further development suggestions involve feature enhancements, data maintenance, and further integration with academic systems to improve system reliability.
Optimasi Pemilihan Mahasiswa Berprestasi Menggunakan Metode Wp (Weighted Product) Berbasis Web Dalam Sistem Pendukung Keputusanoptimasi Adiba, Fhatiah; Wadjidi, Abdul Rifai; Sumardi, Andi Mawaddah
Jurnal Tika Vol 9 No 1 (2024): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v9i1.2353

Abstract

Students as learning agents and seekers of knowledge need to be encouraged to explore their potential, including in aspects of hard skills and soft skills. This research focuses on building a Decision Support System (SPK) with the Weighted Product (WP) method to determine the best students. Improving students' future existence depends not only on the excellence of hard skills, but also the balance of soft skills. The research involved four journals related to SPK student selection, and WP was chosen as an evaluation method. The research process begins with literature collection and system design, including design procedures, system usage, relationships between tables, use case diagrams, and WP method flowcharts. The implementation of the system includes a login page, input of criteria and alternative values, and the process of calculating student rankings. WP gives an accurate ranking, with Alternative 9 (Rifai) as the best student. Testing shows a high degree of accuracy between manual results and system results. This DSS provides an objective evaluation of student achievement, with the potential for further development related to data integration with academic systems and user interface improvement. The conclusion of this study is that SPK with the WP method can provide student rankings efficiently and accurately, helping to support decision making related to the selection of the best students. Further development suggestions involve feature enhancements, data maintenance, and further integration with academic systems to improve system reliability.
Pemanfaatan Aplikasi berbasis Artificial Intelligence untuk Pengembangan Bahan Ajar Guru di SMP Negeri 2 Kahu Kaswar, Andi Baso; Adiba, Fhatiah; Andayani, Dyah Darma; Nurjannah, Nurjannah; Risal, Andi Akram Nur
Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Volume 2 Issue No. 1: July 2024
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/kreativa.v2i1.20243

Abstract

Media pembelajaran memainkan peran penting dalam meningkatkan pengalaman belajar peserta didik di sekolah. Salah satu unsur terpenting  yang menentukan kualitas dalam desain media pembelajaran adalah bahan ajar.  diperoleh. Faktanya, proses penyusunan bahan ajar yang efektif dengan cara konvensional membutuhkan perencanaan yang matang, waktu yang lama, pemahaman yang mendalam tentang kurikulum, serta kemampuan untuk menyajikan materi dengan pendekatan yang inovatif.  Namun, upaya-upaya peningkatan kompetensi guru dalam pengembangan bahan ajar berdasarkan kegiatan yang telah banyak dilakukan sebelumnya hanya berfokus pada pengembangan bahan ajar dalam konteks pemanfaatan media digital dan konteks materi bahan ajar. Dengan banyaknya kesibukan administrasi dan pengajaran di kelas, guru semakin kesulitan untuk mengembangkan bahan ajar dengan efektif dan efisien jika menggunakan cara-cara konvensional. Permasalahan ini juga terjadi pada sebagian Guru SMP Negeri 2 Kahu Kabupaten Bone Sulawesi Selatan yang merupakan mitra dalam kegiatan pengabdian kepada masyarakat ini. Oleh karena itu pada kegiatan program kemitraan masyarakat ini dilaksanakan pelatihan pemanfaatan aplikasi berbasis Artificial Intelligence (AI) untuk pengembangan bahan ajar guru. Kegiatan ini terbagi ke dalam 3 tahapan yaitu tahap persiapan, pelaksanaan kegiatan dan tahap evaluasi. Dimana materi inti yang disampaikan adalah berkaitan dengan teknik penggunaan prompt Google Gemini dalam mendukung dan membantu guru untuk penyusunan dan pengembangan bahan ajar.  Hasil pelatihan menunjukkan bahwa terjadi peningkatan yang signifikan pada para peserta terkait pengetahuan dan kompetensi peserta dalam pengembangan bahan ajar dengan memanfaatkan aplikasi berbasis AI.
Integrasi Metode Weighted Product (WP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk Pendukung Keputusan Penentuan Asisten Dosen Muthmainnah, Aindri Rizky; Pamput, Jessicha Putrianingsih; Adiba, Fhatiah; Surianto, Dewi Fatmarani; Nasrullah, Asmaul Husnah; Budiarti, Nur Azizah Eka
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 2 (2025): September
Publisher : Universitas Wahid Hasyim

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

Abstract

The selection of teaching assistants requires an objective and effective decision-making system. This study designs a decision support system for selecting assistants in the Algorithm and Basic Programming course at JTIK, Universitas Negeri Makassar, by integrating the Weighted Product (WP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. WP assigns weights to evaluation criteria, while TOPSIS identifies the best candidates based on positive and negative ideal distances. The criteria include academic performance, communication, subject mastery, and teaching experience. Testing results show that the system produces consistent selections, aligned with manual calculations and recruitment outcomes, proving its validity and effectiveness in supporting the selection process.
Co-Authors Abdul Wahid Afdhaliyah, Mukhlishah Aglaia, Alifya Nuraisyar Akbar, Muh. Aksa, Muhammad Amaliah, Annisa Shela Amukune, Stephen Anastasia, Tezza Andani, Andi Ferry Adlian Tri Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Arifiyanti, Fitria Asmaul Husnah Nasrullah Awaluddin, Muh. Ghazali Ayu Hasnining Azis, Putri Alysia Baso, Fadhlirrahman Bittara, Andi Ghizzania Sirih DARMATASIA, DARMATASIA Dewi Fatmarani Surianto Edy, Marwan Ramdhany FADIAH, NUR Fajar, Andi Muhammad Fardan, Muhammad Farghina, Syakira Ayma Fathahillah Fathahillah Febriansyah Ramadhan, Haekal Firdaus Firdaus Husna Nasrullah, Asmaul Jannah, Ghina Raodatul Jariah, Rezki Nurul Jumadi Mabe Parenreng Kartika, A.Amalia Khaida, Fatihah Kurnia Prima Putra Lapendy, Jessica Crisfin Lia, Resky Amalia Liku, Antika Diana M. Miftach Fakhri Makmur, Haerunnisya Maolani, Muh. Alfi Muhammad Fajar B Muhammad Yahya Muhtadi Muliadi Munawir Munawir Mustapa, Mahmud Muthmainnah, Aindri Rizky Naoval, Ahmad Nasrullah, Asmaul Husna Nasrullah, Asmaul Husnah Nasurllah, Asmaul Husna Nasurullah, Asmaul Husna NFH, Alifya Nida Rifqi, Ainun Nurfitri, Andi Aisyah Nurjannah Nurjannah Pamput, Jessicha Putrianingsih Parenreng, Jumadi M. Prasetya, Muhammad Fahril Qadri, Zul Rahmat, Nuzulul Ramli, Abdur Rahman Resky, Andi Aulia Cahyana Rivai, Andi Tenri Ola Salsabila, Azizah Sanatang Soeharto Soeharto Sulmadani, Fitriah Sumardi, Andi Mawaddah Syahbani, Dimas Syair, Andi Irfandiari Syair Syukur, Pramudya Asoka Tahir, Muhlis Taufiq, Muhammad Aqsha Tenriola, Andi Udin, Alvin Mas Wadjidi, Abdul Rifai Wahyuni , Maya Sari Wardani, Ayu Tri Wardani, Ayu Tri Wardani WULANDARI