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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA J-SAKTI (Jurnal Sains Komputer dan Informatika) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JPM: JURNAL PENGABDIAN MASYARAKAT Bulletin of Computer Science Research Journal of Social Responsibility Projects by Higher Education Forum KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) EXPLORER Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Pengabdian Masyarakat Inovasi Jurnal Bangun Abdimas Jurnal Informatika dan Teknologi Informasi Journal of Computing and Informatics Research Buletin Ilmiah Informatika Teknologi DUNIA KEPERAWATAN: JURNAL KEPERAWATAN DAN KESEHATAN Jurnal Pengabdian Harapan Bangsa Jurnal Teknologi Ilmu Komputer Jurnal INFOTEL Management of Information System Journal Portal Riset dan Inovasi Sistem Perangkat Lunak Journal of Decision Support System Research Jurnal Mitra Pengabdian Farmasi
Abdul Karim
Universitas Labuhanbatu
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

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Enhancing Lung Cancer Detection: Optimizing CNN Architectures through Hyperparameter Tuning Sundari Retno Andani; Poningsih; Abdul Karim
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6357

Abstract

TThis study aimed to compare the performance of various Convolutional Neural Network (CNN) architectures, including LeNet, ResNet, AlexNet, GoogleNet, VGGNet, and the proposed model, in medical image classification for disease detection. The proposed model was developed by adding additional layers and fine-tuning the hyperparameters in the ResNet architecture to enhance its ability to extract complex features. The training and testing processes were conducted using an augmented X-ray image dataset to increase the data diversity. The results indicate that the proposed model achieved the highest testing accuracy of 76.33%, surpassing other models in terms of accuracy, precision, recall, and F1-score. Although there are some limitations in specificity and the Matthews Correlation Coefficient (MCC), the proposed model still demonstrates better generalization ability, with an AUC-ROC score approaching an optimal value. These findings suggest that the proposed model has advantages in medical image classification and holds potential for further development to enhance disease classification accuracy.
Decision Support System for Recipients of Cash Social Assistance using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Method Alfarisi Pasaribu, Ahmad; Saputra, Imam; Karim, Abdul
Journal of Decision Support System Research Vol. 2 No. 2 (2025): January 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/dss.v2i2.95

Abstract

Cash Social Assistance (BST) is assistance in the form of money provided to poor, disadvantaged, and/or vulnerable families affected by the Corona Virus Disease 2019 (COVID-19) outbreak. The amount of Cash Social Assistance is IDR 600,000/family/month. This Cash Social Assistance is a social safety net program of the Ministry of Social Affairs intended for poor and vulnerable families affected by Covid-19. This program is a special assignment assistance from the President. Social assistance for areas outside Jabodetabek is provided in the form of money, while for the Jabodetabek area it is provided in the form of basic necessities. The provision of BST assistance does not include recipients of the Family Hope Program (PKH), Staple Food Cards, and Pre-Employment Cards. To obtain the Cash Social Assistance (BST) funds, the government has set several criteria for which families can be determined and are entitled to receive the Cash Social Assistance (BST). These criteria will later help government agencies in determining which residents can be selected to receive the Poor Family Assistance Fund. Therefore, a government agency must have a Decision Support System for Cash Social Assistance (BST) recommendations using the Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) method, with the existence of a decision support system for determining Cash Social Assistance (BST) it is expected to run well, be on target, and be received by the entitled people. Thus, decision makers can compare the performance between the old system and the decision support system for determining BST funds using the Multi Objective Optimization On The Basis Of Ratio Analysis (MOORA) method without having to re-request data on families who will be given Cash Social Assistance (BST) funds.
Uncovering Smartphone Brand Strategies through Specification-Based Clustering and Classification Karim, Abdul; Ernawati, Andi
Buletin Ilmiah Informatika Teknologi Vol. 4 No. 1: September 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v4i1.167

Abstract

In an increasingly saturated smartphone market, brand differentiation through technical specifications has become a core strategy for attracting diverse consumer segments. This study proposes a machine learning approach to uncover underlying brand strategies by leveraging smartphone specifications and market pricing across multiple regions. We utilize unsupervised clustering algorithms (K-Means, DBSCAN) to segment devices based on technical features, followed by supervised classification models (Random Forest, XGBoost) to identify and interpret brand-driven design strategies. The dataset comprises smartphones released in 2024–2025, including attributes such as RAM, camera specifications, processor type, battery capacity, and launch prices in Pakistan, India, China, USA, and Dubai. Our findings reveal distinct clusters that align with different pricing tiers and show clear brand positioning patterns. Feature importance analysis using SHAP highlights battery capacity, screen size, and processor type as critical variables influencing brand classification. This study provides valuable insights for both manufacturers and consumers in understanding competitive product strategies within the global smartphone market.
Pemanfaatan Digital Marketing Bagi Masyarakat Tanjung Medan Karim, Abdul; Kusmanto; Purba, Elvitrianim
Jurnal Mitra Pengabdian Farmasi Vol. 1 No. 3 (2022): Juni 2022
Publisher : Akademi Farmasi YPPM Mandiri

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

Abstract

Tanjung Medan Village is a village located in the District of West Blade, Labuhanbatu Regency, North Sumatra Province. Tanjung Medan village itself has a lot of agricultural commodities that are obtained, both palm oil, rubber, even rattan and many more incomes that can be obtained in this area. However, with conditions that are too far from urban access, the results obtained are not optimal but can only be used for daily needs. Thus, to overcome the problems faced by the people of Tanjung Medan, we are coaching the use of digital marketing for the people of Tanjung Medan Village, which aims to increase family income. The higher the income, the more prosperous the people are.
Decision Support System for Determining the Best School Extracurricular Activities by Combining the ROC and MAUT Methods Jahril; Abdul Karim; Erlin Windia Ambarsari; Agus Perdana Windarto
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1493

Abstract

The various extracurricular activities at school make students confused and difficult to choose which extracurricular activities are more suitable for participation. However, sometimes there are also students choosing extracurricular activities based on many of their friends. Therefore, determining the best school extracurricular activities is the best solution for students as a reference to find which is the best extracurricular activity. The criteria used in this study in choosing the best extracurricular activities are Regional Event Activities, Allocation, Creativity and Talent Channeling. By utilizing SPK, decision makers can make more systematic decisions, based on a deeper understanding of the various alternatives available and relevant criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. In the context of extracurricular school selection, combining the ROC (Rank Order Centroid) and MAUT (Multi-Attribute Utility Theory) methods in a Decision Support System is an interesting approach. The ROC method is used to cluster and rank schools based on certain criteria, while MAUT helps in the calculation of appropriate weights for these criteria. By integrating these two methods, the SPK can provide a more structured guideline in the selection of extracurricular activities that suit students' interests and needs. The research results obtained show that the Futsal alternative is the first recommendation as the best extracurricular with a final value of 0.655086.
Implementation of the Multi-Objective Optimization Method on the Basic of Ratio Analysis (MOORA) and Entropy Weighting in New Employee Recruitment Karim, Abdul
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4859

Abstract

The problems faced by the company in managing the selection of new employees must be done in the right way so that it can help a good work cycle. The employee recruitment process still uses manual methods so the Human Resource Development (HDR) division has to sort, select and select applicants one by one. The large number of applicants means that the Human Resource Development division often experiences difficulty in selecting prospective employees and there is subjectivity when deciding which employees fit the established criteria. To overcome the problem of making employee recruitment decisions, we will use the Multi-Objective Optimization method based on ratio analysis (MOORA) and weighting using Entropy. In research, data is collected based on the position of prospective employees. The results obtained in this research determine each position that will be accepted by 3 prospective employees, namely Sales Position, Position, Graphic Design, Accounting Staff, IT Support position, Sales Project.
Optimasi Prediksi Harga Sawit Menggunakan Teknik Stacking Algoritma Machine Learning dan Deep Learning dengan SMOTE Karim, Abdul; Bangun, Budianto; Prayetno, Sugeng; Afrendi, Mohammad
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7239

Abstract

The prediction of palm oil prices plays a strategic role in decision-making within the agribusiness sector, particularly in addressing market volatility and imbalanced historical data distribution. This study aims to optimize the accuracy of palm oil price prediction by applying a stacking approach that combines machine learning and deep learning algorithms, while integrating the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance issues. Three main models were employed in this study: Random Forest, Long Short-Term Memory (LSTM), and a model enhanced with SMOTE. The evaluation was conducted using accuracy, precision, recall, and F1-score metrics, supported by confusion matrix analysis. The results indicate that the model integrated with SMOTE outperforms the others, achieving an accuracy of 0.5447, precision of 0.5512, recall of 0.5447, and F1-score of 0.5462. This model also demonstrates a more balanced classification performance compared to the LSTM and Random Forest models. These findings confirm that the application of oversampling techniques such as SMOTE, when combined with appropriate algorithms, can significantly enhance predictive performance in imbalanced datasets. The study contributes to the development of predictive models for commodity prices based on historical data and opens opportunities for further exploration of more adaptive hybrid methods in future research.
Studi Perbandingan Metode Dempster-Shafer dan Teorema Bayes dalam Sistem Pakar Diagnosa Penyakit Sistem Pernapasan Kusmanto, Kusmanto; Esabella, Shinta; Karim, Abdul; Bobbi Kurniawan Nasution, Muhammad; Hidayatullah, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7317

Abstract

Respiratory system disease diagnosis often faces challenges in ensuring the accuracy of results due to the complexity of overlapping symptoms. In particular, a method is needed that is able to handle data uncertainty and utilize existing evidence optimally. This study aims to compare two methods, namely Bayes' Theorem and Dempster-Shafer, in diagnosing three types of respiratory diseases: Asthma, Tuberculosis, and Bronchitis. The solution is done by analyzing the percentage of confidence produced by each method based on symptom data. The results show that Bayes' Theorem produces the highest confidence for Tuberculosis (74.92%), while Dempster-Shafer provides the highest confidence for Bronchitis (80%). This comparison indicates that the selection of methods must be adjusted to the characteristics of the data and the needs of the analysis. This study contributes to providing insight into the advantages and disadvantages of each method, which can be used as a reference in developing a more accurate disease diagnosis decision support system.
Komparasi Kinerja Algoritma Random Forest dan C4.5 untuk Klasifikasi Harga Mobil Ernawati, Andi; Karim, Abdul
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.95

Abstract

Determining car prices is a crucial aspect of the automotive industry that requires accurate data analysis for strategic decision-making. This study aims to compare the performance of the Random Forest and C4.5 algorithms in classifying car prices based on specific features, such as technical specifications, production year, and market conditions. The dataset used in this study consists of [mention the size and source of the dataset if available], analyzed using a cross-validation approach to ensure the accuracy of the results. The performance of both algorithms is evaluated based on several metrics, including accuracy, precision, recall, and F1-score. The results show that the Random Forest algorithm consistently outperforms the C4.5 algorithm across most evaluation metrics, achieving an accuracy of [best Random Forest accuracy] compared to [best C4.5 accuracy]. These findings indicate that the Random Forest algorithm is more effective in handling multivariate data complexity and providing more reliable predictions. The conclusions of this study highlight the potential of Random Forest as the primary method for car price classification, especially in scenarios requiring high accuracy levels. This research also contributes to a comparative understanding of decision-tree-based algorithms for applications in the automotive industry and opens opportunities for further research into developing more adaptive and efficient models.
Analisis Perbandingan Metode SAW dan MAUT Dalam Pemilihan Dokter Terbaik di RSU Setio Husodo Kisaran Karim, Abdul
Jurnal Teknologi Ilmu Komputer Vol. 2 No. 2: Juni 2024
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/jtik.v2i2.235

Abstract

Dokter merupakan bagian yang paling penting yang dimiliki sebuah rumah sakit dalam mempertahakan kelangsungan hidup serta kemampuan dalam bersaing. Dalam hal ini seorang dokter harus memiliki skill bahkan keterampilan untuk meningkatkan akreditas suatu rumah sakit. Supaya kinerja dokter menjadi lebih baik, maka dibutuhkan suatu sistem dalam membantu pemilihan dokter terbaik, dibutuhkan suatu Sistem Pendukung Keputusan Metode SAW dan MAUT Untuk Pemilihan dokter terbaik di rsu setio husodo kisaran. Untuk metode SAW untuk pemilihan dokter terbaik di rsu setio husodo kisaran, untuk urutan peringkat pertama dengan nama Dasya memperoleh nilai 0,8400. Urutan kedua dengan nama Wilona memperoleh nilai 0.8333. dan untuk urutan ketiga dengan nama Sinta memperoleh nilai 0,8133. Sedangkan untuk perhitungan metode MAUT dokter terbaik dengan nama Sinta memperoleh nilai 0,262, untuk urutan kedua dengan nama Wilona memperoleh nilai 0,248, dan untuk urutan ketiga dengan nama putri memperoleh nilai 0.195  
Co-Authors Afrendi, Mohammad Agus Perdana Windarto Agustina Sidabutar Agustina, Asri Widya Ahyuna Ahyuna, Ahyuna Aldiansyah, Ferry Alfarisi Pasaribu, Ahmad Ambiyar, Ambiyar Andi Ernawati Andi Ernawati Andriani, Titi Aritonang, Putri Armasari, Selly Arridha Zikra Syah Asyahri Hadi Nasyuha Awfa, Qifari Bangun, Budianto Bernadus Gunawan Sudarsono Bobbi Kurniawan Nasution, Muhammad Chairul Rizal Cheylani Lukito, Salwa Christiorenfa Br Haloho, Agatha Daulay, Nelly Khairani Dayu Sari, Arini Deny Jollyta Dhea Ananda, Tasya Dito Putro Utomo Dwika Asrani Dwika Assrani Efendi Hutagalung, Jhonson Efendi, Safri Erlin Windia Ambarsari Fadli, Muhammad Bagus Fadlina Fahmi Rizal Febriani, Budi Fifto Nugroho Garuda Ginting Guidio Leonarde Ginting Harahap, Armyka Pratama Hasibuan, Awaludin Heni Pujiastuti Hersatoto Listiyono Hidayatullah, Muhammad I Wayan Sugianta Nirawana Imam Saputra Indah Sari, Leni Indrayani, Puput Iwan Purnama Jahril Jeperson Hutahaean Jeperson Hutahaean Kraugusteeliana Kraugusteeliana Kurniawan Nasution, Muhammad Bobbi Kusmanto Kusmanto Kusmanto Kusmanto M. Rafi Mardinata, Erwin Marha As, Pawa Niassa Meryance Viorentina Siagian Mesran, Mesran Mhd Ali Hanafiah Mhd Bobbi Kurniawan Nasution Moustafa H. Aly Muhammad Bobbi Kurniawan Nasution Muhammad Hamka Muhammad Syahrizal Nababan, Dosmaida Nasution, Mhd Bobbi Kurniawan Nasution, Muhammad Bobbi Kurniawan Natalia Silalahi Nona Oktari Nurlela Nurlela Nurliadi Pane, Rahmadani Pane, Siddik Pohan, Tatang Hidayat Poningsih Pratama, Armyka Prayetno, Sugeng Prayetno, Sugeng Prayetno Purba, Elvitrianim Purba, Elvitrianim Putra Juledi, Angga Putri, Nathania Rahman, Ben Rohani Rohani Roslidar Saidi Ramadan Siregar Saludin Muis Sartika Br Siregar, Amanda Sempurna, Teguh Shinta Esabella Siagian, Yessica Siddik Siregar, Anwar Sinulingga, Raja Ingata Siregar, Feby Khairunnisya Siti Sahara Nasution Soeb Aripin Suha Alvita Suhada, Karya Sundari Retno Andani Supiyandi Supiyandi Suryadi, Sudi Sutrino Dwi Raharjo Syahputra Harahap, Hasmi Syahrial Tengku Mohd Diansyah, Tengku Mohd Triana, Dewi Trianovie, Sri Trianovie, Sri Unung Verawardina Uswatun Hasanah Vita S. Siregar, Siony William Ramdhan William Ramdhan Wilson, Eric Yessica Siagian Yulizar, Isma Ahmad Yuwaldi Away Yuwaldi Away Zebua, Yuniman Zulham Sitorus Zulkifli Zulkifli Zuly Budiarso