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Dahlan Abdullah

Universitas Malikussaleh

Author-ID : 217988

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Performance of K-Nearest Neighbor Algorithm and C4.5 Algorithm in Classifying Citizens Eligible to Receive Direct Cash Assistance in Bandar Mahligai Village Chaliza Nur, Wan Amalia; Abdullah, Dahlan; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.752

Direct Cash Assistance, commonly called BLT, is one of the many programs the Indonesian government held to reduce the poverty rate of the Indonesian population. This study compares the KNN and C4.5 methods to determine the eligibility of residents eligible to receive Direct Cash Assistance in Bandar Mahligai Village. This study began with collecting resident data from the Bandar Mahligai village office. Then, the data obtained was taken into several attributes to be used in the classification process, namely the name of the head of the family, KK number, NIK, number of dependents, occupation, income, and monthly expenses. After the data is collected, the data will be classified using the KNN and C4.5 algorithms. There is a significant difference between the two algorithms in the classification process; the KNN algorithm by looking for the nearest neighbor data value, in this study, the K value = 9, while the C4.5 algorithm by building a decision tree from the attribute values taken based on resident data used as training data. The classification results of the two methods will be compared using a confusion matrix to obtain a higher accuracy technique. The results of testing using a confusion matrix for both algorithms are the accuracy produced by the KNN and C4.5 algorithms in classifying residents eligible for Direct Cash Assistance (BLT) of 90% in the system that has been built. The results of comparing the KNN and C4.5 algorithms for this study show that the KNN algorithm is better because the accuracy level reaches 90% in manual and system calculations. While the C4.5 method only gets 85% for the accuracy of its manual calculations, it receives an accuracy level of 90% in the system that has been built.

Web-based Rabies Disease Diagnosis Expert System with Forward Chaining and Dempster Shafer Methods Salat, Junaidi; Rasna, Rasna; Ichsan, Muhammad; Abdullah, Dahlan; Lamsir, Seno
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.801

Rabies is a hazardous zoonotic disease that poses a significant threat to both animals and humans, as it can result in death. The disease is caused by a single-stranded RNA virus commonly found in infected animals' saliva, which can be transmitted to humans through bites. Although many people keep animals as pets, many lack adequate knowledge about the potential risks of rabies transmission. In Indonesia, most cases of rabies transmission to humans are caused by bites from infected dogs, followed by bites from monkeys and cats. The absence of an effective treatment for Rabies makes prevention and early diagnosis extremely important. One approach that could help manage the disease is creating an expert system for rabies diagnosis. The Rabies Disease Expert System is developed based on a needs analysis conducted through interviews with veterinarians to understand the classification of symptoms and the diagnostic process for Rabies. It's important to note that while the system is a valuable tool, it does have limitations and should not replace the role of a veterinarian. The system employs two critical methodologies: the Forward Chaining and Dempster-Shafer algorithms. These algorithms allow the system to trace the progression of symptoms and calculate the probability of a rabies infection. The system is an interactive platform where users—such as animal owners or medical professionals—can input observed symptoms in either animals or humans. Based on these inputs, the system provides a probable diagnosis. For example, the expert system might determine that a dog is in the 'Excitation Stage' of Rabies with a 54% confidence level. The integration of Forward Chaining and Dempster-Shafer methods ensures that the system continuously refines its diagnostic accuracy, aiming for a confidence level close to 100%. This expert system offers a promising tool to aid in the early detection and management of Rabies, potentially reducing the risk of widespread transmission.

The Decision Support System for Feasibility Testing of Healthy Canteens at Universitas Malikussaleh Using the Multi-Attribute Utility Theory Method Ulfa, Nur Saufani; Abdullah, Dahlan; Agusniar, Cut
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.815

This research aims to develop a decision support system based on the Multi-Attribute Utility Theory (MAUT) method to evaluate the feasibility of healthy canteens at Malikussaleh University. The system is designed to assess the feasibility of canteens based on six main criteria: Selection of Raw Materials, Storage of Food Ingredients, Food Processing, Food Storage, Food Transportation, and Food Serving. This study evaluated 20 canteens on campus, with feasibility values calculated based on the weights assigned to each Criterion. The results showed that the canteen with the alternative code A11 (Kopita BI) received the highest score of 0.956, followed by A6 (Umi), with a score of 0.798, and A10 (Alisha), with a score of 0.620. Out of the 20 canteens evaluated, only three canteens were categorized as "Feasible," 3 as "Sufficiently Feasible," and the remaining 14 were deemed "Not Feasible." These findings highlight the urgent need to improve the quality of most canteens. The criteria for Selection of Raw Materials and Food Processing had the highest weights, emphasizing the importance of these two aspects in maintaining food quality and health standards. Implementing this system simplifies data management and analysis and provides clear recommendations for canteen managers to improve service and health standards. Thus, this system is expected to promote healthier and higher-quality campus canteens. This research enhances canteen service quality in university environments and can serve as a reference model for other educational institutions in evaluating and improving their canteen facilities.

Data Mining Analysis of Commodity Distribution in Central Aceh Through an Integrated Auction Market System Using the Android-Based Association Rule Mining Method Amelia, Dita; Abdullah, Dahlan; Fitri, Zahratul
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.834

Commodity distribution in Central Aceh faces inefficiencies due to lengthy distribution chains and limited price control, which often leads to higher costs for consumers and lower profits for farmers. To address these issues, this study develops an integrated auction market system based on Android, utilizing the Association Rule Mining (ARM) method to optimize the distribution and pricing of commodities. ARM is a data mining technique that uncovers high-frequency patterns in transaction data. By applying ARM with the apriori algorithm, the system identifies key associations among commodities, allowing for more efficient and targeted price recommendations. The system calculates the highest bid for each commodity and recommends optimal pricing strategies to sellers based on frequent pattern analysis, improving transparency and reducing distribution inefficiencies. Testing and implementation of this system indicate that it successfully reduces distribution costs while increasing the effectiveness and speed of the auction process. Overall, the Android-based auction market system shows promise as a tool for enhancing distribution efficiency, optimizing bid values, and supporting local economies in Central Aceh through more equitable commodity pricing. The final result of this process resulted in four association rules based on predefined parameters, namely a minimum support of 20% and a minimum confidence of 50%. These rules indicate that 60% of the transactions in the Integrated Auction Market system that include Cassava also include Carrots. In other words, a bidder who buys Cassava has a 60% probability of also buying Carrots. This rule is significant as it shows that 20% of all transactions recorded in the system contain both items. This analysis provides important insights into the relationship patterns between items that can be used to provide item recommendations based on purchasing patterns.

Performance Efficiency of Muhammadiyah University Sumatera Area Using Data Envelopment Analysis (DEA) Sulistyandari, Sulistyandari; Fikri, Khusnul; Puji, Ari Andriyas; Abdullah, Dahlan
International Journal of Applied Management and Business Vol. 1 No. 2 (2023)
Publisher : ADPEBI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/ijamb.v1i2.695

Purpose – This paper seeks to examine the efficacy of predicting turnover for employees and entrepreneurs from Estonia, Latvia, and Lithuania using attitudes towards benefits, pay satisfaction, pay, gender, and age across a four-year time frame. Methodology/approach – A survey that included information on attitudes towards benefits and pay satisfaction was used to collect data from 153 Estonian, 157 Latvian, and 146 Lithuanian employees and 243 Latvian, 103 Estonian, and 109 Lithuanian entrepreneurs. Findings – It was found that . Attitudes towards benefits were generally significant predictors of turnover for employees and entrepreneurs over a four-year time period while satisfaction with pay was typically significant for employees but not for entrepreneurs. Novelty/value – As employee retention has been an important factor in the Baltic region over the last two decades it is vital to understand how to retain employees. Keywords Employee turnover, Entrepreneurs, Pay, Estonia, Latvia, Lithuania.

SISTEM PENDETEKSI POLA TAJWID AL- QURAN HUKUM IDGHAM MUTAQARIBAIN PADA AL-QURAN MENGGUNAKAN METODE GOWER & LEGENDRE Abdullah, Dahlan
Jurnal Teknologi Terapan and Sains 4.0 Vol 1 No 2 (2020): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v1i2.3260

Seluruh umat muslim di dunia ini memiliki landasan hukum yaitu Al-Quran dan Al-Hadist. Setiap muslim tentu menyadari bahwa Al-Qur'an adalah kitab suci yang merupakan pedoman hidup dan dasar setiap langkah hidup. Al-Quranul Karim adalah Kalamullah, Kitab suci yang agung umat Islam dan Al-Quran ditulis dalam bahasa Arab. Hampir semua Muslim di seluruh dunia mengetahui bagaimana cara membaca Al-Quran, tetapi tidak semuanya dapat membaca Al-Quran dengan benar berdasarkan makhraj dan Tajwidnya. Oleh karena itu, sistem pendeteksi Tajwid diperlukan untuk membantu pengguna menemukan hukum-hukum Tajwid di dalam Al-Quran. Dalam penelitian ini, metode Gower & Legendre digunakan untuk menghitung jarak keakuratan pola Tajwid pada citra Al-Quran. Hasil pengujian menunjukan bahwa keakuratan sistem ini sebesar 70% hingga 90%. Persentase detection rate tersebut menunjukkan bahwa metode Gower & Legendre dapat digunakan sebagai salah satu pendekatan untuk pendeteksian pola Tajwid pada citra Al-Quran. Kata kunci : Pengolahan Citra, Al-Quran, Tajwid, Gower & Legendre, Big Theta

Analysis of Boarding House Feasibility and Satisfaction Using Data Mining with the C4.5 Algorithm Based on Service Quality and Facilities Manik, Aktina; Abdullah, Dahlan; Ar Razi, Ar Razi
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.896

This research develops a boarding house eligibility classification system using the C4.5 algorithm based on service quality and available facilities. The system evaluates boarding house eligibility by considering various factors such as management services, cleanliness, security, room facilities, public facilities, internet access, comfort, and price. Each of these factors is given a specific weight based on its importance to the tenants, and they are used to classify boarding houses as luxury, standard, and economical. The classification results show that 43% of luxury boarding houses were deemed eligible, while 57% were not. In the standard boarding house category, 21% were classified as eligible, and 79% as ineligible, while in the economical category, 23% were eligible and 77% were ineligible. Using the Confusion Matrix and Classification Report, model evaluation revealed precision ranging from 0.4 to 1.0, recall from 0.67 to 1.0, and F1-scores from 0.5 to 0.91, demonstrating a reasonably high overall accuracy. Additionally, feature importance analysis revealed that price, water and electricity availability, and room facilities are the most influential factors in determining boarding house eligibility. The system's performance was tested against a dataset of real-world boarding houses, and the results suggest that it can accurately classify boarding houses based on key factors that affect tenant satisfaction. The system has the potential to serve as a valuable decision-making tool for boarding house owners, helping them improve service quality and for prospective tenants, enabling them to make more informed housing choices based on their preferences and needs.

Classification of Stunting Status Using the Naive Bayes Classifier Algorithm with Backward Elimination Feature Selection Pasaribu, Hafni Maya Sari; Abdullah, Dahlan; Rosnita, Lidya
JINAV: Journal of Information and Visualization Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav4100

Stunting is one of the major health issues affecting toddlers that can influence their physical growth and developmental progress, ultimately impacting their quality of life. It is characterized by a child’s height being below the standard for their age. To address this issue, a method is needed to classify the stunting status in toddlers. This study aims to classify stunting status in toddlers using the Naive Bayes Classifier algorithm, with feature selection performed using the Backward Elimination method to improve classification accuracy.The dataset used in this research was collected in 2023 from the Lueng Daneun Public Health Center, located in Peusangan Simblah Krueng Subdistrict, Bireun District. The dataset includes several features such as age, gender, family income, height, weight, sanitation, clean water access, and formula milk consumption. The application of the backward elimination feature selection method is intended to identify the most significant and relevant features for the target variable. The Naive Bayes Classifier was implemented using the Python programming language. The analysis results indicated that the remaining feature, namely the sanitation condition, had a significant contribution to the classification process. The dataset consisted of 244 entries, divided into 195 training data and 49 testing data with an 80:20 ratio. The initial classification results showed an accuracy of 77.55%, a precision of 60.00%, a recall of 64.29%, and an F1-score of 62.07%. After feature selection, the accuracy increased to 81.63%, precision to 63.16%, recall to 85.71%, and the F1-score slightly improved to 72.73%. These results indicate that feature selection in the Naive Bayes model demonstrates good performance.

Klasterisasi Kualitas Biji Kopi Berdasarkan Taraf Penyusutan Menggunakan Metode K-Harmonic Means dengan Validasi Silhouette Index dan C-index Putra, Arwin; Abdullah, Dahlan; Daud, Muhammad
Jurnal Janitra Informatika dan Sistem Informasi Vol. 4 No. 2 (2024): Oktober - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/f1jg3b72

Kopi merupakan salah satu hasil perkebunan masyarakat Indonesia yang memiliki nilai jual yang tinggi. di Indonesia ada beberapa daerah penghasil kopi, salah satunya adalah Kabupaten Bener Meriah dengan luas lahan 48.95 ribu ha dan jumlah produksi 4.75 ribu ton. Setiap desa nya memiliki jumlah produktifitas kopi asalan yang berbeda-beda, walaupun dengan luas lahan yang sama, hal ini terjadi karena adanya proses penyusutan. Oleh karena itu perlu adanya pengelompokan desa dengan kualitas biji kopi berdasarkan taraf penyusutan. Penelitian ini bertujuan untuk mengelompokkan desa-desa dan mengetahui cluster kualitas biji kopi berdasarkan proses pengolahan.Metode yang digunakan dalam pengelompokan (Clustering) ini menggunakan metode K-Harmonic Means yang merupakan pengembangan dari metode K-Means. Jumlah data yang digunakan dalam penelitian ini yaitu sebanyak 34 desa dengan 6 atribut yaitu nama desa, luas lahan, jumlah gelondong, gabah, labu dan asalan . pengujian klaster dilakukan dengan jumlah klaster k = 2, 3 dan 4 serta menguji klaster yang dihasilkan dengan menggunakan metode validasi silhouette index dan C-Index. Berdasarkan hasil analisis penelitian ini didapatkan klastering yang terbaik pada k = 2 dengan metode Silhouette Index dengan nilai SI = 0,59822 sedangkan c-index diperoleh klaster yang terbaik pada k = 4 dengan nilai CI = 0,03436. Adapun hasil profilisasi k = 2 yaitu 9 desa dengan kualitas kopi sangat baik dan 25 desa dengan kualitas kopi baik. dan profilisasi k = 4 yaitu 5 desa dengan kualitas kopi sangat baik, 13 desa dengan kualitas kopi baik, 10 desa dengan kualitas kopi cukup dan 6 desa dengan kualitas kurang. Dari kedua metode ini yang paling optimal yaitu menggunakan 4 klaster pada c-index yang memiliki nilai rasio Sw dan Sb terkecil yaitu 0,0734.

Analisis Assesment Vulnerability pada Website dan Aplikasi Publik di Dinas Komunikasi Informatika dan Statistik Kota Banda Aceh Saputra, Rizwan; Abdullah, Dahlan; Daud, Muhammad; Maulana, Fatur Rahman
Jurnal Janitra Informatika dan Sistem Informasi Vol. 4 No. 2 (2024): Oktober - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/q6jdk177

Penelitian ini bertujuan untuk melakukan analisis asesmen kerentanan pada website dan aplikasi publik yang dikelola oleh Dinas Komunikasi, Informatika, dan Statistik (Diskominfotik) Kota Banda Aceh. Kerentanan dalam sistem informasi dapat membuka peluang bagi serangan siber yang dapat merugikan integritas dan kerahasiaan data, serta ketersediaan layanan. Oleh karena itu, penelitian ini fokus pada identifikasi, evaluasi, dan mitigasi potensi kerentanan yang dapat muncul pada infrastruktur digital tersebut. Metode penelitian melibatkan analisis keamanan yang holistik, mencakup uji penetrasi, analisis kode, dan pemeriksaan konfigurasi sistem. Data yang diperoleh dari asesmen ini akan membantu Diskominfotik dalam meningkatkan keamanan sistem mereka dan melindungi informasi yang dikelola. Hasil penelitian diharapkan dapat memberikan wawasan mendalam tentang tingkat kerentanan yang ada, serta rekomendasi konkret untuk memperbaiki kelemahan yang teridentifikasi. Dengan demikian, Diskominfotik Kota Banda Aceh dapat mengambil langkah-langkah proaktif untuk mengamankan website dan aplikasi publik mereka, meningkatkan kepercayaan pengguna, dan memastikan kelangsungan operasional layanan digital.

Co-Authors - Hartono . Zulfan Abdul Wahab Achmad Harristhana Mauldfi Sastraatmadja Aditia, Donny Adli Zain, Razlan Affiza, Denhaz Pattra Afisman, Heri Juni Afriza, Muhammad Ridho Agus Sukoco Akbar, Abdul Hanif Akhyar, Daniel Al- Amin Ali Nasith Alimul Haq, Nur Ambas, Jamin Amrina, Amrina Ananda Faridhatul Ulva Andi Latif, Sarifudin Andik Bintoro ani, Muli Ansyari, Taufik Habib Anuar Bahri, Khairil Ar Razi, Ar Razi Arifah, Mutia Arifin, Arifin Aslam Aslam, Aslam Aulia Barus, M Farhan Ayu Anggreni, Made Berkah Nadi, Muhammad Abi Chaliza Nur, Wan Amalia Cindy Rahayu Cut Agusniar Cut Ita Erliana Cut Yusra Novita Darmawanta Sembiring Defi Irwansyah Deisye Supit Devin Mahendika Dita Amelia, Dita Eko Prastyo Elviwani Elviwani Elviwani Elviwani Elviwani, Elviwani Emy Yunita Rahma Pratiwi ER. UMMI KALSUM Erianto Ongko Erlina Erlina Erlina Erlina Fadlisyah Fadlisyah Fadlisyah Farida Juliarta, Evie Fazil, M Fidyatun Nisa Fikri, Khusnul Firman Aziz Gamar Al Haddar Gio, Prana Ugiana Haedir, Haedir 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 Putu Agus Dharma Hita I Putu Gede Adiatmika Ika Rahayu Satyaninrum IKhwanda Putra, Al Malikul Imanullah, Imanullah 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 Kamilah, Muna Kartika Kartika Kartini Rahayu Khairullah Yusuf Komang Ayu Krisna Dewi Kosasih , Kosasih Kurniawansyah, Kurniawansyah La Ode Muhammad Idrus Hamid B Lahap, Johanudin Lamsir, Seno Laros Tuhuteru Lestari, Veronika Nugraheni Sri Lidya Rosnita Limbong, Hendra Putranta Lubis, Fauzan Arbi M Farhan Aulia Barus M FAUZAN Maharani Asnur, Sardian 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 Miswar Miswar Mohammad, Wily Mohd Said, Noraslinda Mohd Syahrin 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 Muslem Muslem Muslem Muslem, Muslem Muthmainnah Muthmainnah Muzaffar Rigayatsyah Muzaffar Rigayatsyah N. Nazaruddin Nadia Karunia, Meutia Nana Citrawati Lestari Nasution, Zainannur Ni Ketut Dewi Irwanti Noviany, Henny Nunsina, Nunsina Nurdin Nurdin Nurhaedah Nurhaedah Nurhasanah Nursyamsi SY Oksfriani Jufri Sumampouw Paisal Halim Pasaribu, Hafni Maya Sari Pertiwi, Anggun Pikri, Faizal Poetri AL-Viany Maqfirah Puji, Ari Andriyas Putra, Arwin Rahmat, Rezqiqah Aulia Ramli, Rahmat Rasna, Rasna Reskiawan, Bimas - Rezzy Eko Caraka Riansyah, Muhammad Richki Hardi Rini Meiyanti Risawandi, Risawandi Rizki Suwanda Rizki Wahyuri Roslaini, Roslaini S, Syarifuddin Sabriana, Riska Safwandi Safwandi Safwandi Safwandi, Safwandi 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 Sutarna, Agus Syamsiah Badruddin Tahulending, Anneke A Teuku Mudi Hafli Touwe, Yohana S Touwe, Yohana S. Tri Suryowidiyanti Ulfa, Nur Saufani Ultra Prayogi Ulumul Haq, Bahrul 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 Yuliah, Yuliah Yuniningsih Yuniningsih Yusra, Muhammad Zafera Adam, Jeanne d'Arc Zahratul Fitri, Zahratul Zainannur Nasution Zara Yunizar Zega, Subhansah Zulfahmi Zulfahmi

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