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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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Food Security Optimization Forecasting Fertilizer Production With Method Weighted Moving Average (WMA) Rifkial Iqwal; Dahlan Abdullah; Nunsina
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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This research focuses on optimizing food security through the application of fertilizer production forecasting method at PT Pupuk Iskandar Muda (PIM) using Weighted Moving Average (WMA). Effective food security relies heavily on stable and adequate fertilizer availability, which in turn requires accurate production predictions to ensure efficiency. In this study, historical data of urea and ammonia fertilizer production from January 2019 to December 2023 is used to build a forecasting model that can provide an overview of future production trends. The WMA method was chosen due to its adaptive nature, where greater weight is given to the most recent data, allowing the model to be more responsive to changes and emerging trends. The results showed that for urea production, WMA produced a MAPE value of 1773.8% and MAD of 13,223.2, while for ammonia production, the MAPE was recorded at 3085.5% with MAD of 7,538.5. Total production showed a MAPE of 69.7% with a MAD of 20,568.9, indicating significant fluctuations in production during the period under study. Nevertheless, the WMA method still provides a fairly good prediction and can be used as a reference in future production planning. In addition, the results of this study also provide valuable insights into the production dynamics at PIM, which is critical in supporting the national food security strategy. This research recommends further exploration of other more advanced forecasting methods, such as ARIMA or machine learning techniques, to improve prediction accuracy and better anticipate changes in production patterns. Keywords: Food security, Weighted Moving Average, Fertilizer Production Forecasting, MAPE, MAD.

Application of the Naïve Bayes Method in Optimizing Marketing Performance at PT. Semen Indonesia Mahesa Reglisalo; Dahlan Abdullah; Yesy Afrillia
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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This study examines the application of the Naïve Bayes method to improve marketing performance at PT. Semen Indonesia. In an increasingly competitive business environment, effective data management is crucial for strategic decision-making. Currently, PT. Semen Indonesia utilizes the SAP system to manage sales and financial data, but it lacks an automated system to analyze marketing performance. This research aims to develop a Naïve Bayes-based classification system to monitor marketing performance, considering attributes such as profit, market share, sales volume, and customer satisfaction. The Naïve Bayes method was chosen for its accuracy in handling large-scale data and its ability to provide fast and efficient predictions. Marketing performance data is processed using this method to categorize marketing performance as “good” or “poor.” The analysis results show that the developed system achieves a classification accuracy of 43.75% for the “good” category and 56.25% for the “poor” category. This system assists management in designing more effective marketing strategies by leveraging historical data to predict trends and market needs. Keywords: Naïve Bayes, marketing performance, PT. Semen Indonesia, data analysis, classification system, profit, market share

Prediction of Trash in Aceh Province Using the Autoregressive Integrated Moving Average (ARIMA) Method Nefo Preyandre; Dahlan Abdullah; Said Anshari
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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The increase in trash production in Aceh Province presents challenges for trash management, particularly in planning adequate infrastructure. This study applies the Autoregressive Integrated Moving Average (ARIMA) model to predict trash volume in Aceh. The data utilized originates from the National Trash Management Information System (SIPSN) and the Central Bureau of Statistics (BPS) from 2020 to 2023. The prediction results indicate that ARIMA can capture the primary trends in trash volume but has limitations in accounting for seasonal fluctuations in certain trash categories. Accuracy evaluation using the Mean Absolute Percentage Error (MAPE) shows varying accuracy levels across trash types, with some categories requiring additional models to enhance accuracy. These findings are expected to support planning and policy for trash management in Aceh.

Pilgrimage and Cultural Heritage: Understanding Tourist Motivations at the Tomb and Sunan Drajat Museum at Lamongan East Java-Indonesia Nuruddin; Wirawan, Putu Eka; Susanti, Putu Herny; Nashihin; Wiarti, Luh Yusni; Abdullah, Dahlan
Pusaka : Journal of Tourism, Hospitality, Travel and Business Event Vol. 8 No. 1 (2026): Vol. 8 No. 1 (2026): February-July
Publisher : Politeknik Pariwisata Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33649/pusaka.v6i2.598

Motivation is a key factor in tourists’ decision-making, including visits to historical sites related to the development of religion. This study aims to analyze the motivation of tourists visiting historical sites such as the tombs of saints and museums preserving their legacy. A qualitative method with a thematic and interpretive approach was used. Data were collected through interviews, field observations, and literature review. The findings reveal two main motivational perspectives: religious and cultural. Religious motivation includes the pursuit of blessings, spiritual merit, and inner peace, while cultural motivation involves interest in history, architecture, and cultural heritage. This study offers both theoretical and practical contributions to the development of tourism based on local and spiritual values. Its uniqueness lies in combining religious and cultural motivations in the context of visits to the Tomb and Museum of Sunan Drajat Lamongan—a site that has received little scholarly attention. Unlike previous studies that tend to separate the two aspects, this research integrates spiritual and historical dimensions to better understand tourist behavior.

Analysis of the Efficiency and Performance Effectiveness of Srikandi Application Using the UTAUT Model and Delone & Mclean Syahputra, Wawan; Abdullah, Dahlan; Nurdin, Nurdin; Daud, Muhammad; Taufiq, Taufiq
International Journal of Engineering, Science and Information Technology Vol 6, No 1 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i1.1806

The development of information technology has encouraged the government to carry out digital transformation in administrative governance, one of which is through the implementation of the SRIKANDI Application (Integrated Dynamic Archive Information System). This application is designed to support the management of electronic archives and correspondence integrated across government agencies. This study aims to analyze the efficiency and effectiveness of the SRIKANDI Application in supporting government administration, focusing on service speed, documentation accuracy, and resource efficiency. The method used in this study is a mixed methods approach with a sequential explanatory design. Quantitative data were collected by distributing questionnaires to employees who used the application to assess perceptions of efficiency and effectiveness. Furthermore, qualitative data were obtained through in-depth interviews and document analysis to delve into the quantitative findings and explore contextual factors that influence application implementation. Data analysis is carried out in stages, starting with descriptive and inferential statistical analyses for quantitative data and with thematic analysis for qualitative data. This research is expected to contribute to the development of an electronic government system and serve as a reference for evaluation and policymaking related to bureaucratic digitalization. In addition, the results of this study are also expected to strengthen the literature on the effectiveness of government information systems and provide an empirical picture of the practice of implementing the SRIKANDI Application in government agencies.

Comparison of Logistic Regression and Random Forest Methods in Predicting Vehicle Tax Payment Compliance Khairul Fuadi; Taufiq Taufiq; Arnawan Hasibuan; Dahlan Abdullah; Nurdin Nurdin
Jurnal Informatika Vol. 13 No. 1 (2026): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/informatika.v13i1.11944

Motor vehicle tax is a major source of Regional Original Income (PAD). However, the level of motor vehicle tax payment compliance in North Aceh Regency is still suboptimal, particularly related to late payments. A data-driven approach is needed to predict and understand taxpayer compliance patterns more accurately. This study aims to compare the performance of the Logistic Regression and Random Forest methods in predicting motor vehicle tax payment compliance, as well as to identify factors that influence taxpayer compliance behavior at the North Aceh Samsat (Sat). This study uses secondary data in the form of motor vehicle tax payment transactions at the North Aceh Samsat for the 2022–2024 period, totaling 100,000 observations. The response variable is the tax payment compliance status (compliant and non-compliant), while the predictor variables include vehicle age, type of ownership, vehicle type, and vehicle brand. The data is divided into 70% training data and 30% testing data. The performance evaluation model is conducted using accuracy, precision, recall, and Area Under Curve (AUC) metrics. The analysis results show that Random Forest has better predictive performance than Logistic Regression, with higher accuracy and AUC values. Vehicle age and type of ownership are the most influential variables in predicting tax payment compliance, while vehicle brand has a relatively smaller influence. Logistic Regression provides a clear interpretation of the variable relationship, but has lower discrimination ability than Random Forest. Random Forest has proven to be more effective as a prediction model for motor vehicle tax payment compliance at the North Aceh Samsat. The application of machine learning-based predictive models has the potential to support more targeted policy making in an effort to improve motor vehicle tax payment compliance, especially in reducing late payments.

Prediction Of Unemployment Rate Using The Fuzzy Time Series Chen Model Method Annisa Karima; Dahlan Abdullah; Muchlis ABD Muthalib; Nurdin Nurdin; Muhammad Daud
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7310

Unemployment is a significant socio-economic problem in Lhokseumawe City that requires serious attention from policymakers. The unemployment rate fluctuates from year to year, making accurate forecasting an important aspect in formulating effective strategies and policies to reduce unemployment. One method that can be used to analyze and forecast time series data with uncertainty is the Fuzzy Time Series (FTS) method, which applies fuzzy logic concepts to handle vague and imprecise data patterns. In this study, the Fuzzy Time Series method is applied to predict the number of unemployed people in Lhokseumawe City. The data used are historical unemployment data over a period of 10 years, from 2013 to 2022. The research process begins with defining the universe of discourse (U), determining the number and length of interval classes, defining fuzzy sets on U, and fuzzifying the unemployment data. Furthermore, Fuzzy Logical Relationships (FLR) are identified and grouped into Fuzzy Logical Relationship Groups (FLRG). The defuzzification process is then carried out to obtain crisp values, followed by forecasting calculations.The analysis was conducted using the RStudio application. The forecasting results show that the predicted number of unemployed people in 2023 is 10,514.125, which is rounded to 10,514 people. The accuracy of the forecasting model is evaluated using Mean Absolute Percentage Error (MAPE) and Average Forecasting Error Rate (AFER), both of which yield values of 6.70%. Since the MAPE and AFER values are less than 10%, the forecasting results can be categorized as very good and reliable for decision-making purposes.

ETHICAL DILEMMAS IN NEUROMARKETING: NAVIGATING PERSUASION, CONSUMER AUTONOMY, AND EMERGING TECHNOLOGIES Muhamad Stiadi; Luana Sasabone; Deisye Supit; Cut Ita Erliana; Dahlan Abdullah
International Journal Of Humanities, Social Sciences And Business (INJOSS) Vol. 3 No. 1 (2024): INTERNATIONAL JOURNAL OF HUMANITIES, SOCIAL SCIENCES AND BUSINESS (INJOSS)
Publisher : ADISAM Publisher

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Neuromarketing is a rapidly growing field that uses neuroscience to understand consumer behavior and improve marketing effectiveness. This article explores the complex ethical implications of neuromarketing practices, especially regarding persuasive influence on consumer autonomy and the use of emerging technologies. First, we investigate advances in neurotechnology, such as fMRI, EEG, and brain-computer interfaces (BCIs), that enable a deeper understanding of consumer preferences. The challenge is enforcing this technology's ethical use and protecting individual privacy. Second, we discuss "neuro hacking," exploiting neurological vulnerabilities to influence consumer decisions. This raises ethical questions about mental safety and individual autonomy. Third, algorithms and artificial intelligence in Neuromarketing create highly personalized marketing experiences. This raises questions about how to protect privacy, obtain consent, and maintain individual agency. Fourth, we explore cultural issues in Neuromarketing, exploring how cultural values must be respected in marketing practices. Fifth, we discuss security and data protection issues in using neuromarketing technology. Sixth, we investigate the role of government and regulatory agencies in regulating neuromarketing practices and protecting consumer rights. Finally, we highlight the importance of education about neuroethics in educating marketers, researchers, and consumers about the ethical aspects of Neuromarketing. This article encourages critical reflection on the ethical dilemmas businesses, researchers, and policymakers face in the rapidly evolving world of Neuromarketing.

CULTIVATING SUSTAINABLE EMPLOYEE ENGAGEMENT AND WELL-BEING INITIATIVES IN INDONESIAN ORGANIZATIONS: A MULTIFACETED EXAMINATIONOF STRATEGIES, CHALLENGES, AND IMPACT ON ORGANIZATIONAL PERFORMANCE Kosasih Kosasih; Yuarini Wahyu Pertiwi; Cut Ita Erliana; Defi Irwansyah; Dahlan Abdullah
International Journal Of Humanities, Social Sciences And Business (INJOSS) Vol. 3 No. 1 (2024): INTERNATIONAL JOURNAL OF HUMANITIES, SOCIAL SCIENCES AND BUSINESS (INJOSS)
Publisher : ADISAM Publisher

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We provide an overview of the research on cultivating sustainable employee engagement and well-being initiatives in Indonesian organizations. The study aimed to comprehensively examine the strategies employed, the challenges faced, and the impact of these initiatives on organizational performance in the Indonesian context. The research was rooted in a mixed-methods approach, combining qualitative and quantitative methods to understand the subject matter better. Data was collected from surveys, interviews, and organizational records. Stratified random sampling was employed for surveys, while purposive sampling was used for interviews, ensuring a diverse and representative dataset. Our analysis incorporated descriptive statistics and inferential statistical methods, such as regression analysis, for quantitative data. Qualitative data underwent thematic analysis, allowing for the identification of patterns and themes. Integrating both data types enabled triangulation and a more profound insight into the research questions. Ethical considerations were paramount throughout the research, with data treated confidentially and participant identities protected. Informed consent was obtained from all participants, and potential biases or conflicts of interest were transparently addressed. While the mixed- methods approach enriched our understanding, it did pose resource and time constraints. While valuable within the Indonesian context, the findings may not be universally applicable. Additionally, challenges related to data collection, such as participant availability and the completeness of organizational records, were acknowledged. This research contributes to the existing body of knowledge by offering insights into the strategies and impact of sustainable employee engagement and well-being initiatives in Indonesian organizations while shedding light on the challenges faced in implementing such programs.

EXPLORING THE INTEGRATION OF QUANTUM MACHINE LEARNING ALGORITHMS IN HIGHER EDUCATION TO ENHANCE CURRICULUM DEVELOPMENT ANDCYBERSECURITY PROGRAMS Muhammad Ihsan Dacholfany; Miswar; Cut Ita Erliana; Dahlan Abdullah; Indrawati
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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This research delved into a dynamic landscape in exploring the integration of Quantum Machine Learning (QML) algorithms in higher education for curriculum development and cybersecurity programs. The study aimed to investigate the potential impact of QML on higher education and the security domain, addressing the evolving educational needs and the ever-pressing cybersecurity challenges. Through comprehensive analysis, this research unveiled the transformative capacity of QML technology and its implications for the academic and security sectors. Research findings disclosed significant gaps in current curricula and the need for a comprehensive approach to QML integration. Faculty and student perceptions illustrated the challenges and opportunities surrounding QML, with the former emphasizing the necessity for professional development and the latter expressing enthusiasm and the desire for more hands-on experiences. Insights from cybersecurity experts highlighted QML's potential in fortifying security measures, underlining the importance of collaboration between quantum computing and cybersecurity communities. This research contributes by providing a multifaceted understanding of QML integration in higher education and its ability to reshape learning and security paradigms. However, it acknowledges certain limitations, such as sample diversity and the evolving nature of quantum technology. Despite these limitations, this exploration lays the groundwork for future adaptations and advancements in education and cybersecurity in the quantum age

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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