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Dahlan Abdullah

Universitas Malikussaleh

Author-ID : 217988

Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Transportation Other

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EDUCATIONAL ADVANCEMENTS IN THE DIGITAL EPOCH: A MULTIFACETED EXPLORATION OF THE STRATEGIC INCORPORATION OF TECHNOLOGY TO AMPLIFYEDUCATIONAL QUALITY AND LEARNING OUTCOMES IN PRIMARY EDUCATION ACROSS INDONESIA Iswan Riyadi; Sitti Nur Alam; Cut Ita Erliana; Dahlan Abdullah; Al-Amin
International Journal of Teaching and Learning Vol. 1 No. 1 (2023): International Journal of Teaching and Learning (INJOTEL)
Publisher : Adisam Publisher

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Amid the digital era, this research embarked on a comprehensive exploration of the strategic Integration of technology in primary education within the diverse educational landscape of Indonesia. The study delved into the multifaceted dynamics of technology's role in amplifying the quality of education and enhancing learning outcomes. The research unveiled a rich tapestry of findings, elucidating the promises and challenges associated with technology integration. It unearthed a positive correlation between technology integration and improved learning outcomes, where students in schools with higher technology integration consistently achieved better results in standardized assessments. However, the study also illuminated the striking disparities in technology integration, with urban schools benefiting from more advanced technological infrastructure than their rural counterparts. The implications of this research reverberate throughout the Indonesian educational landscape, emphasizing the imperative to bridge the digital divide and ensure equitable access to technology. As the digital epoch continues to reshape educational paradigms, this study stands as a testament to the transformative potential of technology when harnessed strategically and responsibly, with an unwavering focus on enhancing educational quality and empowering the next generation of learners.

SOCIOECONOMIC DISPARITIES IN EDUCATIONAL OUTCOMES ARISING FROM THE IMPLEMENTATION OF TECHNOLOGY-ENABLED LEARNING IN EARLY CHILDHOOD EDUCATION IN INDONESIA Al-Amin; Ika Rahayu Satyaninrum; Cut Ita Erliana; Dahlan Abdullah; Mohd Syahrin
International Journal of Teaching and Learning Vol. 1 No. 1 (2023): International Journal of Teaching and Learning (INJOTEL)
Publisher : Adisam Publisher

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The integration of technology in early childhood education has garnered significant attention worldwide. In 2021, Indonesia embarked on an ambitious journey to incorporate technology-enabled learning into its educational framework. This study retrospectively examines the socioeconomic disparities that emerged from this endeavor. Through extensive data analysis and assessments, it was observed that the introduction of technology in early childhood education had a mixed impact on the educational outcomes of children from various socioeconomic backgrounds. While children from affluent families exhibited enhanced digital literacy and cognitive development, those from economically disadvantaged households encountered disparities in access to technology and resources. The digital divide became more pronounced, leading to disparities in academic achievement. Furthermore, it was found that educators and policymakers encountered significant challenges in adapting the curriculum to address these disparities. The study also highlights the importance of addressing issues related to infrastructure and equity in technology access in early childhood education, ensuring that all children have an equal opportunity to thrive. These findings emphasize the necessity for a more inclusive and equitable approach to integrating technology in early childhood education, aiming to bridge the socioeconomic gaps and provide a level playing field for all children, thereby fostering a more equitable and promising educational landscape in Indonesia.

Traffic Accident Prediction Using Machine Learning Based on PT Jasa Raharja Data Utomo, Muhammad Fikri; Fikry, Muhammad; Hamdhana, Defry; Abdullah, Dahlan; Nurdin, Nurdin
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 21, No 1 (2026): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jim.v21i1.25392

Traffic accidents represent a critical issue that significantly affects public safety and generates substantial social and economic impacts, particularly within the operational area of PT. Jasa Raharja Lhokseumawe Branch. The lack of predictive information regarding accident occurrences often results in reactive policy making. This study aims to develop a machine learning–based forecasting model for traffic accident rates using a combination of K-Means Clustering and Recurrent Neural Network (RNN). The dataset consists of historical traffic accident records from 2022 to 2024, which were preprocessed and aggregated on a weekly basis at the district level. K-Means Clustering was employed to group districts according to weekly accident patterns, resulting in two optimal clusters based on silhouette score evaluation. Subsequently, separate RNN models were developed for each cluster to forecast weekly accident occurrences. Model performance was evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results indicate that the RNN model achieved higher prediction accuracy for clusters with more stable accident patterns compared to clusters exhibiting higher fluctuation. Overall, the proposed combination of clustering and RNN demonstrates strong potential in producing accurate traffic accident forecasts

Prediction Of Industrial Waste Using The Autoregressive Integrated Moving Average Method Roslaini, Roslaini; Abdullah, Dahlan; Suwanda, Rizki
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.624

This study presents the development of a web-based industrial waste prediction system using the Autoregressive Integrated Moving Average (ARIMA) method to forecast the volume of liquid and solid waste generated by PT Pupuk Iskandar Muda (PIM). The predictive model is built upon historical waste data collected between 2020 and 2023, serving as the foundation for the statistical analysis. The system is developed using the Flask web framework, offering an interactive and user-friendly interface, while SQLite3 is employed as a lightweight local database solution for efficient data handling. The ARIMA (1,1,1) model was selected based on stationarity testing and examining ACF and PACF patterns. The results suggest that the model can moderately capture prediction trends, although limitations in accuracy are evident. For 2024, liquid waste is projected to decrease from 30,600 tons in January to 29,400 tons in December. In contrast, solid waste displays a more stable trend, with an average monthly generation of approximately 23.2 tons. Model performance was evaluated using the Mean Absolute Percentage Error (MAPE) method, yielding high error rates—166.11% for liquid waste and 100% for solid waste, highlighting the significant impact of data quality and completeness on prediction accuracy. The system generates visual outputs through interactive graphs and tables accessible via a web browser, supporting data-driven decision-making. This research is a predictive tool for PT PIM and a reference for future development of technology-driven waste management systems to promote environmental sustainability.

Design of Electric Wheelchair Using Pulse Width Modulation (PWM) Method Nisa, Fidyatun; Abdullah, Dahlan; Akhyar, Daniel
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.638

An electric wheelchair is an essential mobility device for individuals with physical disabilities. Unlike traditional manual wheelchairs, which can be challenging for users to operate independently, an innovative PWM (Pulse Width Modulation) based electric wheelchair has been developed and tested. This wheelchair employs an Arduino Uno microcontroller, ultrasonic sensors, joystick input, and motor drivers to control speed and direction effectively. The system utilizes PWM to adjust the motor speed in proportion to the joystick input. Testing demonstrated that the wheelchair's motor responds efficiently to changes in PWM values. Additionally, the system successfully stops the motor when obstacles are detected within 80 centimeters. The ultrasonic sensors demonstrated an impressive measurement accuracy, with an average error of only 1%. Moreover, increasing the PWM values resulted in faster wheelchair speeds, showcasing the system’s ability for responsive speed control. This design provides an affordable and effective solution to improve mobility for users with disabilities.

Classification of Tourist Attractions in Central Aceh District using the C4.5 Decision Tree Algorithm Amny Yasira; Abdullah, Dahlan; Cut Agusniar
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.715

Central Aceh Regency is a region with rapidly growing tourism potential, characterized by lakes, mountains, and cultural sites typical of the Gayo people. Although the available tourist attractions are quite diverse, the presentation of unstructured information often makes it difficult for tourists to determine destinations that suit their needs and preferences. To address this problem, this study implemented the C4.5 decision tree algorithm to classify tourist attractions in Central Aceh Regency. The study used five main attributes: type of tourism, accessibility, facilities, ticket prices, and the Number of annual visitors. Data were obtained through field observations, interviews, and online reviews, with a total of 54 tourist attractions being sampled. The analysis process began with data preprocessing, entropy calculations, and information gain and gain ratio to construct a decision tree. The modelling results showed that the accessibility attribute produced the highest gain ratio and became the root node in the tree. Furthermore, the Number of visitors attributed became the dominant factor in the next branch, consistently distinguishing the classes. The classification system resulted in three recommendation categories: Highly Recommended, Recommended, and Not Recommended. Model evaluation using a confusion matrix showed 92% accuracy, 90% precision, and 90% recall, indicating that the C4.5 algorithm is effective at grouping tourist attractions based on their characteristics. This research contributes to a data-driven model that can help tourists obtain more systematic information, while also supporting local governments and tourism stakeholders in developing more targeted destination development strategies.

ANALYZING STRATEGIES FOR STRENGTHENING LITERACY COMPETENCE AT THE JUNIOR HIGH SCHOOL LEVEL AMONG SCHOOL TEAMS AT THE DISTRICT AND CITY LEVELS IN INDONESIA Deslana Roidja Hapsarini; Al-Amin; Cut Ita Erliana; Defi Irwansyah; Dahlan Abdullah
Indonesian Journal of Education (INJOE) Vol. 2 No. 3 (2023): Indonesian Journal of Education (INJOE)
Publisher : CV. ADIBA AISHA AMIRA

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This study delved into the intricate realm of enhancing literacy competence at the junior high school level among school teams operating at the district and city levels in Indonesia. With a focus on collaborative efforts, this research analyzed various strategies to bolster literacy skills, comprehensively exploring the multifaceted challenges and potential solutions. The study examined the historical background and significance of literacy competence in Indonesia's junior high schools to grasp the context. It addressed the pressing problem of inadequate literacy skills among students and identified vital contributing factors, such as limited access to resources, linguistic diversity, and disparities in socioeconomic conditions. The study set forth four primary research objectives: (1) to assess the current literacy competence levels in junior high schools, (2) to uncover the internal and external factors influencing literacy development, (3) to scrutinize effective strategies and best practices for strengthening literacy skills within school teams, and (4) to formulate targeted recommendations for district and city-level policymakers, educators, and stakeholders, through a comprehensive investigation encompassing public and private schools across diverse regions, the research aimed to shed light on the complex interplay of factors shaping literacy outcomes. This study, despite its limitations in terms of time and resource constraints and personal influences, seeks to provide valuable insights to guide collaborative efforts to boost among junior high school students in Indonesia.

Analysis of Informatics Engineering Students’ Dependency Level on the Use of ChatGPT Using the Support Vector Machine Method Aswita Indah Luthfiana Hasibuan; Dahlan Abdullah; Kurniawati Kurniawati
International Journal of Engineering, Science and Information Technology Vol 6, No 2 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i2.1813

This study aims to analyze the level of dependency among Informatics Engineering students on the use of ChatGPT in academic activities using the Support Vector Machine (SVM) method. The research data were collected through questionnaires distributed to students of the Informatics Engineering Study Program at Universitas Malikussaleh from the 2022–2025 cohorts, involving a total of 400 respondents. The research indicators included usage intensity, duration of use, purpose of use, perceived effectiveness, and dependency behavior toward ChatGPT. The collected data underwent several preprocessing stages. including missing value checking. label transformation. data normalization using Min-Max Scaling. and dataset splitting into 80% training data and 20% testing data. The classification process was performed using the Support Vector Machine (SVM) algorithm with a linear kernel. The experimental results showed that the proposed SVM model successfully classified student dependency levels into three categories, namely low, medium, and high, achieving an accuracy of 95%, which indicates excellent classification performance. The findings also revealed that usage frequency, duration of use, and the utilization of ChatGPT for academic assignments and programming activities were the most influential factors affecting student dependency. Furthermore, a web-based system was developed using Python Flask and SQLite to facilitate data processing, model training, and visualization of classification results. The system testing results demonstrated that all implemented features functioned properly according to the specified requirements.

Co-Authors - Hartono . Zulfan A. Z, Abdullah Abdul Wahab Achmad Harristhana Mauldfi Sastraatmadja Aditia, Donny Adli Zain, Razlan Affiza, Denhaz Pattra Afisman, Heri Juni Afriza, Muhammad Ridho Agil, Helvina Agus Sukoco Akbar, Abdul Hanif Akhyar, Daniel Al Kautsar Aidilof, Hafizh Al- Amin Al-Amin Ali Nasith Alimul Haq, Nur Ambas, Jamin Amny Yasira Amrina, Amrina Ananda Faridhatul Ulva Andik Bintoro ani, Muli Annisa Karima Ansyari, Taufik Habib Anuar Bahri, Khairil Ar Razi, Ar Razi Arifah, Mutia Arifin, Arifin Arnawan Hasibuan Aslam Aslam, Aslam Aswita Indah Luthfiana Hasibuan Aulia Barus, M Farhan Ayu Anggreni, Made Berkah Nadi, Muhammad Abi Chaizir, Muhammad Chaliza Nur, Wan Amalia Cindy Rahayu Cut Agusniar Cut Ita Erliana Cut Yusra Novita Darmawanta Sembiring Dedi Fariadi Defi Irwansyah Defi Irwansyah Deisye Supit Deslana Roidja Hapsarini Devin Mahendika Dita Amelia, Dita Eko Prastyo Elviwani Elviwani Elviwani Elviwani Elviwani, Elviwani Emy Yunita Rahma Pratiwi, Emy Yunita Rahma ER. UMMI KALSUM Erianto Ongko Erlina Erlina Erlina Erlina Fachry Abda El Rahman Fadlisyah Fadlisyah Fadlisyah Fajriana, Fajriana Fakhruddin Ahmad Nasution Farida Juliarta, Evie Fazil, M Fikri, Khusnul Firman Aziz Gamar Al Haddar Gio, Prana Ugiana Habib Muharry Yusdartono Haedir, Haedir Halim, Paisal Hamdhana, Defry Hapsarini, Deslana Roidja Haris Danial Hartono Hartono Hartono Hartono Hartono, Natalia Rumanti Hasanun Hasibuan, Abdurrozzaq Hasibuan, Fadilah Suryani Hasibuan, Muammar Faturrahman Heri Juni Afisman Herry Rachmat Widjaja Hery Budiyanto HS, Nurmadina I Ketut Sutapa I MADE MULIARTA . I P G. Adiatmika I Putu Agus Dharma Hita Ika Rahayu Satyaninrum IKhwanda Putra, Al Malikul Imanda, Nanda Imanullah, Imanullah Indah Sulistiani Indra Pilianti D Indra Tjahyadi Indrawati Indrawati Irdanil Kamal, Irdanil Irianto, Sugeng Irma Oktari Irwansyah, Defi Islam, Khoirul Iswan Riyadi Iswandi Iswandi Iswandi Iswandi Iylia Azlan, Rabiatul Juarni Siregar Judijanto, Loso Kamilah, Muna Kartika Kartika Kartini Rahayu Khairul Fuadi Khairullah Yusuf Komang Ayu Krisna Dewi Kosasih Kosasih , Kosasih Kurniawansyah, Kurniawansyah Kurniawati Kurniawati La Ode Muhammad Idrus Hamid B Lahap, Johanudin Lamsir, Seno Laros Tuhuteru Latif, Sarifudin Andi Lestari, Nana Citrawati Lestari, Veronika Nugraheni Sri Lidya Rosnita Limbong, Hendra Putranta Luana Sasabone Lubis, Fauzan Arbi Lubis, Muhammad Hanafi Sahar Luh Yusni Wiarti M Farhan Aulia Barus M Fauzan Maharani Asnur, Sardian Mahesa Reglisalo Manik, Aktina Marganda Simarmata Marlina Sari Maryana Maryana Maryana Maryana, Maryana Masriadi Maulana, Fatur Rahman Maulinda, Rerin Maya Savira Meilyana Meilyana Meutia Rahmi Mirna Dewi Misbahul Jannah Misbahul Jannah Miswar Miswar Miswar Mochamad Gilang A Mubarok Mohammad, Wily Mohd Said, Noraslinda Mohd Syahrin Muchlis ABD Muthalib Muhamad Stiadi Muhammad Daud Muhammad Fikry Muhammad Ichsan Muhammad Ihsan Dacholfany Muhammad Ikhsan Setiawan Muhammad Ikhsan Setiawan Muhammad Ikhwani Muhammad Khahfi Zuhanda Muhammad Khalis, Muhammad Muhammad Riansyah Muhammad Zarlis Muhammad Zarlis, Muhammad Muharam, Suhari muli ani Munirul Ula Muslem Muslem Muslem Muslem, Muslem Muthmainnah Muthmainnah Muzaffar Rigayatsyah Muzaffar Rigayatsyah N. Nazaruddin Nadia Karunia, Meutia Nashihin Nasution, Zainannur Nefo Preyandre Ni Ketut Dewi Irwanti Nisa, Fidyatun Noviany, Henny Nunsina, Nunsina Nurdin Nurdin Nurhasanah Nursyamsi SY Nuruddin Oksfriani Jufri Sumampouw Pasaribu, Hafni Maya Sari Pertiwi, Anggun Pikri, Faizal Poetri AL-Viany Maqfirah Puji, Ari Andriyas Putra, Arwin Putu Eka Wirawan Rafi’i, Rafi’i Rahma Fitria, Rahma Rahma, Hilmia Rahmat, Rezqiqah Aulia Ramlan, Rifqi Ramli, Rahmat Rasna, Rasna Razi, Ar Reskiawan, Bimas - Rezzy Eko Caraka Riansyah, Muhammad Richki Hardi Rifkial Iqwal Rini Meiyanti Risawandi, Risawandi Rizki Suwanda Rizki Wahyuri Rizky Putra Fhonna Roslaini, Roslaini S, Syarifuddin Sabriana, Riska Safwandi Safwandi Safwandi Safwandi, Safwandi Said Anshari Said Fadlan Anshari salamah salamah Salat, Junaidi Samsul A Rahman Sidik Hasibuan Sandya, Deasy Saputra, Nanda Saputra, Rizwan Sasabone, Luana Satria Pati Alam Sayed Fachrurrazi Selamat Meliala Setiawan, Muhammad Ikhsan Sima, Yenny Simarmata, Marganda Sitti Nur Alam Subhan, Roni Sulistyandari, Sulistyandari Surnihayati Surnihayati Susanti, Putu Herny Sutarna, Agus Syahputra, Wawan Syamsiah Badruddin Syarifuddin Syarifuddin Tahulending, Anneke A Tarigan, Tasya Amelia Taufiq Taufiq Taufiq Taufiq Teuku Mudi Hafli Touwe, Yohana S Touwe, Yohana S. Tri Suryowidiyanti Ulfa, Nur Saufani Ultra Prayogi Ulumul Haq, Bahrul Utomo, Muhammad Fikri Veronika Nugraheni Sri Lestari Victor E. D Palapessy Wa Ode Riniati Wahyu Pertiwi, Yuarini wandi, risa Wenny J, Syilvia Widiyani, Maya Yeni Risyani Yesy Afrillia Yuarini Wahyu Pertiwi Yuliah, Yuliah Yulisda, Desvina Yuniningsih Yuniningsih Yusra, Muhammad Zafera Adam, Jeanne d'Arc Zahratul Fitri, Zahratul Zainannur Nasution Zalfie Ardian Zara Yunizar Zega, Subhansah Zulfahmi Zulfahmi Zulfia , Anni

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