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All Journal Techno.Com: Jurnal Teknologi Informasi JURNAL PENGABDIAN KEPADA MASYARAKAT Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika MODELING: Jurnal Program Studi PGMI IT JOURNAL RESEARCH AND DEVELOPMENT PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Teknik Informatika UNIKA Santo Thomas INTECOMS: Journal of Information Technology and Computer Science Zero : Jurnal Sains, Matematika, dan Terapan ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) AXIOM : Jurnal Pendidikan dan Matematika Jurnal Teknologi Sistem Informasi dan Aplikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Kurawal - Jurnal Teknologi, Informasi dan Industri Jurnal Riset Informatika AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Jurnal Review Pendidikan dan Pengajaran (JRPP) Progresif: Jurnal Ilmiah Komputer Jurnal Informatika dan Rekayasa Elektronik JSR : Jaringan Sistem Informasi Robotik Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Teknik Informatika C.I.T. Medicom G-Tech : Jurnal Teknologi Terapan Science Midwifery JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) INFOKUM Community Development Journal: Jurnal Pengabdian Masyarakat U-NET Jurnal Teknik Informatika Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) MEANS (Media Informasi Analisa dan Sistem) Journal of Computer Networks, Architecture and High Performance Computing JiTEKH (Jurnal Ilmiah Teknologi Harapan) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Journal La Multiapp Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Armada Informatika Journal of Information Systems and Technology Research Jurnal Sains dan Teknologi JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Innovative: Journal Of Social Science Research Jurnal Komputer Antartika Scientica: Jurnal Ilmiah Sains dan Teknologi Jurnal Pengabdian Masyarakat Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Ilmiah Nusantara Modem : Jurnal Informatika dan Sains Teknologi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Teknologi : Jurnal Ilmiah Sistem Informasi
Abdul Halim Hasugian
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Sistem Pendukung Keputusan Untuk Menentukan Kelayakan Penerima Bantuan Langsung Tunai Menggunakan Metode AHP-Topsis Simatupang, Aidil Akbar; Hasugian, Abdul Halim
JURIKOM (Jurnal Riset Komputer) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8833

Abstract

Social inequality and inaccuracy in aid distribution are still challenges in the Direct Cash Assistance (BLT) program, especially at the village level such as Bandar Selamat Village, North Labuhan Batu Regency. The process of determining BLT recipients which is still manual and subjective poses a risk of injustice and inefficiency. This study formulates the problem: how to develop an objective and targeted decision support system (DSS) for the selection of BLT recipients. The purpose of this study is to design and implement a DSS based on the Analytical Hierarchy Process (AHP) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) which can increase the accuracy and efficiency of aid recipient selection. The method used is Research and Development (R&D), with data collection techniques through interviews and observations, as well as comprehensive system testing. The results show that from 110 household head data, the system is able to identify 69 families eligible to receive assistance with a preference value ? 0.6. Employment and home conditions are the dominant criteria in determining eligibility. The system is proven to be consistent (CR = 0.0298 <0.1) and is able to simplify the decision-making process. This research provides real benefits in improving transparency, accountability, and effectiveness of social assistance distribution at the village level through a data and technology-based approach.
Sistem Rekomendasi TV Series Berdasarkan Genre Menggunakan Algoritma KNN Deni Fahrizal; Abdul Halim Hasugian
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.6225

Abstract

The problem of choice overload on TV series streaming platforms often makes it difficult for users to find content that suits their preferences. To address this challenge, this study develops a Content-Based Filtering-based recommendation system by applying the K-Nearest Neighbor (KNN) algorithm and the Jaccard Similarity metric. The designed system analyzes users' genre preferences, such as Drama, Sci-Fi, and Comedy, while integrating rating, popularity, and release year factors to generate more personalized recommendations. Evaluation of 500 TV series titles from the TMDB API shows a high level of accuracy, with Precision and Recall reaching 1.0 for specific genre preferences, as well as stable performance with an F1-Score of 0.67 for cross-genre preferences. These findings prove that the proposed model is effective in reducing choice overload and significantly improving the user experience in exploring content on streaming platforms. Furthermore, this approach has the potential to be further developed by integrating sentiment analysis and real-time audience behavior data to generate increasingly adaptive and relevant recommendations.
Sentiment Analysis on the Planned Nickel Mining Development in Raja Ampat Using the Random Forest Algorithm Rajani, Attila; Hasugian , Abdul Halim
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1565

Abstract

The planned nickel mining development on Kawe and Manuran Islands in Raja Ampat has sparked various public reactions, especially on social media platforms. Raja Ampat is known for having one of the highest levels of marine biodiversity in the world, raising concerns about the potential ecological and social impacts of such development. This study aims to analyze public sentiment regarding the nickel mining plan in Raja Ampat by utilizing social media comments. The method used is the Random Forest algorithm, which is recognized for its high performance in classifying complex text data. A total of 2,010 comments were collected, and after the preprocessing stage, 1,658 clean data entries remained for analysis. The preprocessing steps included text cleaning, case folding, normalization, tokenization, stopword removal, and stemming. The results show that 57.85% of the comments expressed positive sentiment, while 42.15% showed negative sentiment. The Random Forest model was able to classify the sentiments with an accuracy of 80.1%, using three decision trees as the basis for majority voting. Furthermore, n-gram analysis and word cloud visualization provided insight into the dominant words in public opinion, offering a deeper understanding of the issues being discussed. This research is expected to serve as a consideration in development policy-making that prioritizes environmental sustainability and the well-being of local communities.
PREDIKSI PENJUALAN SEMBAKO MENGGUNAKAN METODE REGRESI LINIER SEDERHANA Dea Amallia; Hasugian , Abdul Halim
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1573

Abstract

Penelitian ini berfokus pada prediksi penjualan sembako di Toko Gento dengan menggunakan regresi linier sederhana. Metode ini dipilih karena kesederhanaannya dalam memodelkan hubungan antara waktu dan volume penjualan. Penelitian ini mengikuti lima tahap dalam siklus data mining, yaitu pemahaman bisnis, pemahaman data, persiapan data, pemodelan, evaluasi. Data yang digunakan mencakup penjualan dari Januari hingga Juni. Hasil penelitian menunjukkan bahwa regresi linier sederhana dapat memberikan prediksi tren penjualan yang cukup akurat, terutama untuk produk dengan pola penjualan linier. Model ini diharapkan dapat membantu toko dalam membuat keputusan terkait pengelolaan stok dan perencanaan penjualan.
Identifying Dominant Factors of Divorce in Marbau Selatan Village Using K-Means Clustering Anggraini, Sindi; Hasugian, Abdul Halim
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 2 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i2.26447

Abstract

The increasing rate of divorce in Marbau Selatan Village reflects a broader trend in Indonesia and highlights an urgent social issue that threatens family resilience. This study applied the K-Means Clustering algorithm to analyze and classify divorce cases based on demographic and social characteristics. Data were collected from 85 divorce records registered between 2021 and 2025, focusing on key variables such as age, gender, case type, and cause of divorce. The clustering process generated three distinct groups, namely: conflicts and repeated disputes, abandonment by one party, and economic hardship. The results demonstrated that persistent conflicts represented the most dominant factor, followed by abandonment and financial problems. These findings suggest that K-Means is effective for revealing hidden patterns in divorce data, providing valuable insights for local stakeholders. The study contributes to data-driven policy recommendations, such as premarital counseling, family economic empowerment, and community-based mediation, to reduce divorce rates and improve household harmony in rural areas.
Data Mining of Rural Digital Technology Adoption Factors Using Apriori Algorithm Windary, Wanda; Hasugian, Abdul Halim
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1324

Abstract

Digital technology adoption in rural communities remains a major challenge due to limited infrastructure, weak internet connectivity, and low levels of digital literacy, which contribute to persistent gaps in digital inclusion. This study aims to analyze the socio-economic factors that influence technology adoption in Kuta Baru Village by applying data mining techniques with the Apriori algorithm within the Knowledge Discovery in Database (KDD) framework. A survey was conducted on 50 respondents selected using purposive sampling, and variables such as education, income, occupation, and internet access were encoded into binary items for analysis. The Apriori algorithm was executed with a minimum support threshold of 15% and a minimum confidence threshold of 60% to extract association rules. Results show that the strongest rule was “Low Internet Access ⇒ Weak Signal” with 100% confidence and 30% support, highlighting infrastructure as the most critical barrier. Another key finding revealed that respondents with education levels above high school had an 85% confidence of using the internet, while those with monthly incomes greater than IDR 3 million demonstrated a 78% confidence of adopting digital technologies. Furthermore, formal sector occupations were associated with consistent internet usage at 72% confidence. These findings suggest that improving infrastructure must be complemented by strengthening socio-economic conditions, particularly education and income, to accelerate rural digital transformation. The study provides empirical evidence and practical implications that can inform policymakers in designing targeted programs to bridge the rural digital divide.
Web-Based Decision Support System for Superior Corn Seed Selection Using FMADM and AHP Algorithms Putra, Donny Dwi; Hasugian, Abdul Halim
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1331

Abstract

Indonesia as an agricultural country still faces challenges in meeting national corn demand due to dependency on imports. One critical issue is the inaccurate selection of superior seeds that suit local conditions. This study aims to develop a web-based decision support system (DSS) for superior corn seed selection using the Fuzzy Multi-Attribute Decision Making (FMADM) algorithm combined with the Analytical Hierarchy Process (AHP) method.The research was conducted in Sei Tembo Village, Langkat Regency, with data obtained through observation, interviews with farmers, and literature review. The AHP method was applied to determine the weights of five criteria: water content, pest resistance, productivity, fruit size, and harvest time. Consistency testing produced a CR value of 0.028, indicating reliable weighting. The FMADM method was then used to rank 142 seed alternatives based on these weights.The results showed that the proposed system successfully ranked Srikandi Putih 1 (A32) as the best alternative with a score of 0.950, while Bima5 Bantimurung (A130) had the lowest score of 0.632. Productivity was identified as the dominant factor (weight = 0.484) in determining superior seeds.These findings demonstrate that the web-based DSS can improve accuracy and objectivity in seed selection, helping farmers reduce trial-and-error decisions. Practically, this system supports agricultural productivity improvement and contributes to strengthening national food security by reducing reliance on corn imports.
Analysis Of Public Sentiment Towards Naturalized Players In The Indonesian National Team Using The Naïve Bayes Method T. Raihan Yudisthira; Abdul Halim Hasugian
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i4.398

Abstract

The increasing number of naturalized Indonesian national team players in the Garuda squad has triggered various reactions and opinions among the public, both pro and con. This study aims to identify and classify these sentiments, whether positive, negative, or neutral. The method used in this study is to use Naive Bayes because of its excellent ability to classify text based on the probability of word occurrence. In order to obtain more accurate results, several preprocessing stages need to be carried out through several steps, namely cleaning, case folding, normalization, stopword removal, tokenizing, and stemming on the data to be processed for maximum results from each stage. The results of the study showed that the majority of public sentiment tends to be more neutral towards the contribution of naturalized Indonesian national team players. To determine the percentage of results from the specified classification, a Confusion Matrix will be used. The results of the classification process using the Naive Bayes method produce data into 3 types, namely 33 positive classes, 357 neutral classes, and 13 negative classes with an accuracy value of 89%, precision 63%, recall 34%, and f1-score 33%. This sentiment analysis provides an overview of public comments regarding the presence of naturalized Indonesian national team players regarding public acceptance of the naturalization policy and can be input for PSSI in making decisions regarding the development of the national team in the future in order to improve the quality of the national team in the future
Prediction of Parents’ Satisfaction in Learning Methods Using K-Nearest Neighbor Algorithm Ginting, Masitha Putri Ardhana; Hasugian, Abdul Halim
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1702

Abstract

Parental satisfaction in learning methods is an important indicator for evaluating the quality of education, especially in inclusive schools such as Smart Aurica School. This study aims to predict the level of parental satisfaction with learning methods using the K-Nearest Neighbor (K-NN) algorithm. The research employed a quantitative approach with data collected through questionnaires distributed to parents of students. The collected data were processed through several stages, including data cleaning, normalization, training and testing set division, and distance calculation using Euclidean Distance. The K-NN model was then applied to classify satisfaction levels based on the predetermined K value. The results indicate that the K-NN algorithm can provide accurate predictions of parental satisfaction, achieving a relatively high accuracy rate in testing. These findings demonstrate that K-NN is an effective approach to assist schools in evaluating learning methods and offering data-driven recommendations to improve educational quality. Therefore, this research contributes to the application of machine learning in providing a more objective and accurate evaluation of educational services, which can serve as a strategic basis for school decision-making.
THE USE OF THE AHP AND TOPSIS METHODS IN ANALYZING THE SELECTION OF THE BEST CRYPTO (CASE STUDY: BITCOIN AND SOLANA) Anggraini, Arizka; Hasugian, Abdul Halim
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1757

Abstract

The development of digital financial technology has introduced a variety of crypto assets with different characteristics and mechanisms, necessitating an objective analytical approach to determine the most optimal asset. This research aims to identify the best crypto between Bitcoin and Solana by considering five main criteria: transaction speed, transaction cost, energy consumption, network security, and network stability. The approach used is descriptive quantitative with the application of the Analytic Hierarchy Process (AHP) method to determine the weight of each criterion and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives based on the obtained weights. Data was collected through a literature review and official sources from each crypto platform to ensure the validity and reliability of the results. Based on the analysis, Solana obtained the highest preference value as it showed significant superiority in transaction speed, cost efficiency, and low energy consumption, while Bitcoin remains superior in the aspect of more assured network security and stability. The combination of the AHP and TOPSIS methods proved capable of producing a systematic, rational, and measurable multi-criteria decision-making process. The results of this study have implications for the development of a data-driven digital asset evaluation model, which can serve as a reference for investors, market analysts, and researchers in conducting comparative assessments of crypto asset performance more efficiently, transparently, and based on empirical evidence, in line with the increasing need for analytical instruments in modern financial technology investment.
Co-Authors Abdillah, Ibnu Faiz Adam Damiri Manurung Adi Hartono Aditya Maulana Azanzi Girsang Afandi Sahputra Afiksih, Mufliha Afriani, Dina Aidil Halim Lubis Aidil Halim Lubis Ajeng Dwi Pratiwi Alfarizi, Muhammad Alhabib, Muhammad Farhan Ali Darta Ali Ikhwan Alwy Azyari Harahap Amalia Daulay, Rizki Amelia Anggraini, Arizka Anggraini, Sindi Annisa Shafira Zuhri Apriani, Puja Arif, Mhd. Fakhrozi Armansyah Armansyah Armansyah Aruan, Nur Jamilah Asrul Suwondo AULIA, RIZKA Auliani, Wirna Rizka Azhar, Joehari Azhari, Wahyu Bandaharo, Bandaharo Bermiko Kasah Padang Bunga Nurul Manisa Dea Amallia Deni Fahrizal Dewi Afrianti Dharma, Fahri Dinda Zukhoiriyah Eferoni Ndururu Elsa Azila Rahman Fakhriza, M. Farah Zaida Gema Ramadhan Gilang Armawan Saka Ginting, Masitha Putri Ardhana Girsang, Aditya Maulana Azanzi Gunawan, Gunawan Gunawan, Helmi Hanny Puput Eliyarista Saragih Harahap, Muhammad Fitrah Affandi Harahap, Nasywa Al Afif Hasibuan, Ardina Khoirunnisa Heni Pujiastuti Heri Santoso Heri Santoso Heri Santoso HERI SUSANTO Hidayati, Risma Hsb, Munawir Siddik Ibnu Rusydi Ikhsan, Muhammad Ilham Ilham Ilka Zufria Imam Zaki Husein Nst Irawan, Muhammad Arief Irene Sri Morina Januar, Bagus K Khairunnisa Khaidir Hanafi Khairuna Khairuna Khairunnisa, K Lubis, Akbar Maulana Lubis, Desy Ramadhani Lubis, Indah Alfitri M Mahyudi M. Fakhriza M. Khalil Gibran M. RIZKY RAMADHAN M.Alif Fahrezy Maimunah Rahmadani Marpaung, Rizq Alwi Marwah, Khoirul Wijak Alfaizh Maulida, Dzikra Maya Khairani Mhd Furqan Mhd Ikhsan Rifki Miftahul Jannah Muhammad Ezar Raditya Muhammad Ikhsan Muhammad Ikhsan Muhammad Ridzki Hasibuan Muhammad Sayuthi Muhammad Siddik Hasibuan Muhammad Suhery Mulya Alfan Simatupang Murdani Nadyah Almirah Simanjuntak Nasution, Yazid Hulaini Habbani Nasution, Yurika Nurmaiyah Nurmaiyah Ong, Russell Pahlevi, Mhd Rafly Syah Pazri Prasetio, Muhammad Aditya Prayoga, M. Irsan Pristiwanto, Pristiwanto Putra, Donny Dwi Putri Hanifah Putri, Cindy Ananda Putri, Pebriani Rahadian Fatta Batubara Rahmad Prayogi Harahap Rahmawati Rahmawati Raissa Amanda Putri Rajani, Attila Rakhmat Kurniawan R Ramadhani, Muthia Ramadhani, Silvia Rano, Rano Irawan Reza Muhammad Rijal, Mhd. Nanda Khairul Rina Widyasari Rizki Amalia Rizky Pratama Putra Rizky Ramadhan Rizqi Hidayat Tanjung RR. Ella Evrita Hestiandari Ryo Vikri Alif S, Amri Yuda Sabuki, Robi Saefuddin, Anan Saka, Gilang Armawan Sela, Dhea Shania Oktawijaya Sheila Safira Siahaan, Ahmad Taufik Al Afkari Simanjuntak, Salmah Simatupang, Aidil Akbar Siregar, Muhammad Faisal Siregar, Nora Arianti Siti Hayatul Fauziah Ritonga Siti Juhroini Ritonga Siti Nurhaliza Sofyan Siti Sumita Harahap Sitorus, Ridha Saryani Situmorang, Rantouli Solifiah Batubara, Febi Sriani Sriani Sriani Sriani, S Suandi Padang Suendri Suendri, Suendri Suhardi Suhardi Suhardi, Suhardi Sulindawaty T. Raihan Yudisthira TONNI LIMBONG Tria Elisa Ulfah, Auliana Wahyudi, Zul Attoriq Farhan Wina Fadia Ardianti Windary, Wanda Yani, Sri Suci Yusuf Karim Rambe Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zaidan, Muhammad Zidanul Akbar Ziqra Addilah