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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) 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) Jurnal Pengabdian Masyarakat Gemilang (JPMG) 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 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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Pengembalian Data Yang Hilang Pada Dataset Dengan Menggunakan Algoritma K-Nearest Neighbor Imputation Data Mining Bangun, Budianto; Karim, Abdul Karim
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.8014

Abstract

One of the things that is really hoped for when collecting data is to produce complete data. In research, incomplete data will affect the results obtained. because the process carried out in the research was not optimal. A dataset is a collection of information that is stored for a long time and becomes a large pile of data. Missing values in the dataset will be an important problem and must be handled in research. Therefore, data recovery is needed. Data mining is a process carried out in computer research. Where data mining will process data that has been collected first, either data collected by yourself (primary data) or data that has been collected in a dataset (secondary data). Recovery is the process of recovering data that is lost or cannot be found. The K-Nearest Neighbor Imputation algorithm is a system that uses a supervised learning algorithm and aims to discover new data patterns by connecting existing data patterns with new data. KNNI is an approach used to identify objects based on certain information, namely the closest distance to the object
Penerapan Data Mining Untuk Pengelompokan Terhadap Kualitas Kinerja Karyawan Dengan Menggunakan Algoritma K-Medoids Clustering Karim, Abdul; Esabella, Shinta; Kusmanto, Kusmanto; Hidayatullah, Muhammad; Suryadi, Sudi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7445

Abstract

HR management is recognized as a global issue and an integral part of competitiveness in the arena of globalization. The organizational structure is the placement of tasks from the very top to the placement of very basic tasks. Assessing the quality of employee performance is one of the work evaluation sessions that can provide the best for industry and citizens. In position placement, if someone does not suit the position they have, it will cause problems such as the company's operational processes not running well. Performance appraisal of employees aims to see the performance results that have been carried out or given by employees when occupying a position. Problems related to performance appraisal are important problems that must be resolved immediately. Data mining is a data processing process in the past, where data in data mining is a collection of data that has been collected over a certain period of time. Information data mining is a series of processes for exploring added value in the form of data produced by extracting and identifying patterns in an information base. Clustering is a part of data mining that aims to group based on the formation of new clusters. The K-Medoids algorithm is a partitional clustering procedure that minimizes the distance between labeled points. The K-Medoids algorithm is a classic Clustering partition technique that groups data sets of ni objects into k groups known a priori. From the results of research conducted using the K-Medoids method, 3 clusters were obtained. Where in cluster 1 there are 4 employees, in cluster 2 there are 3 employees and in cluster 3 there are 3 employees.
Decision Support System for Best Teacher Selection using the Multi-Objective Optimization on the Basic of Ratio Analysis (MOORA) Sudarsono, Bernadus Gunawan; Karim, Abdul
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5736

Abstract

Teachers are one of the most important assets owned by companies in their efforts to maintain survival, develop, ability to compete and earn profits. The selection of the best teachers will produce valid and useful information for employee administrative decisions such as promotions, training, transfers including reward systems and other decisions. Decision Support System is a computerized system and is designed to increase the effectiveness in decision making to solve semi-structured and unstructured problems so that the decision making process can be of higher quality. This application that will be made is an application that is guided by the MOORA method. The calculation results using the MOORA method revealed that alternative A5 shows the best performance with a score of 1.246, while alternative A9 occupies the lowest position with a score of 0.546.
Clusterisasi Tingkat Pengangguran Terbuka Menurut Provinsi di Indonesia Menggunakan Algoritma K-Medoids Karim, Abdul; Esabella, Shinta; Kusmanto, Kusmanto; Suryadi, Sudi; Mardinata, Erwin
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6198

Abstract

The Open Unemployment Rate (OER) in Indonesia decreased in February 2024 to 4.82%, showing an improvement compared to February 2023. Despite the decline in TPT, there are still regions with TPT reaching 7.02%, which could potentially lead to negative consequences such as increased crime. Efforts to address TPT include increasing economic growth, developing the quality of education and training. This research utilises clustering in data mining. The number of clusters formed was 3 clusters with a DBI value of -1.685. This study uses K-Medoids clustering to group 38 provinces based on TPT. Of the 38 data, there is incomplete data so preprocessing is done using the "filter example" operator in rapidminer to eliminate incomplete data so that there are 34 data that will be used in this study (after preprocessing). The results show 4 provinces with the highest TPT (Riau Islands, DKI Jakarta, West Java, and Banten) with a percentage of 11.76%.
Analisis Perbandingan Metode WASPAS dan TOPSIS dengan Menggunakan Pembobotan ROC dalam Sistem Pendukung Keputusan Penentuan Sales Sepeda Motor Terbaik Sudarsono, Bernadus Gunawan; Suhada, Karya; Karim, Abdul
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6222

Abstract

Determining the best motorcycle salesperson is an important aspect in improving sales performance and motivation in automotive companies. This process must be carried out objectively by considering various criteria, such as performance achievement, discipline, teamwork, communication skills and responsibility. However, decision making is often complex because it involves many factors and varying criteria. Therefore, a Decision Support System (DSS) is needed that is able to process and analyze data effectively. This study aims to analyze the comparison of two multi-criteria methods, namely Weighted Aggregated Sum Product Assessment (WASPAS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), in determining the best motorcycle salesperson. Both methods use Rank Order Centroid (ROC) weighting to give weight to the assessment criteria. Based on the results of the analysis, it can be seen that both methods provide consistent results, although there are differences in the final ranking. The results of the study indicate that the WASPAS and TOPSIS methods are equally effective in determining the best alternative, with differences in the order of priorities that can be used as further consideration by decision makers. The results of the two methods show that the alternative with the highest performance according to both methods is Febriansyah, who is in first place both in the TOPSIS method with a value of 0.796 and in the WASPAS method with a value of 0.810.
Penerapan Complex Proportional Assessment (COPRAS) Dalam Penentuan Kepolisian Sektor Terbaik Ginting, Garuda; Alvita, Suha; Mesran, M; Karim, Abdul; Syahrizal, Muhammad; Daulay, Nelly Khairani
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.254

Abstract

In determining the best Sector Police, many criteria must be had by every Sector Police to be the best. Some of the criteria used to determine the best Sector Police are Polsek services, completion of the crime, number of personnel, cleanliness of the Sectoral Police, and number of criminal acts. Determination of the best Sector Police to improve the performance of personnel so that they are encouraged to be better at doing their jobs than before. To avoid mistakes and be precise in determining the best Police Sector, a decision support system is needed. In this study, a case will be raised, namely finding the best alternative based on the existing criteria using the Complex Proportional Assessment (COPRAS) method. The COPRAS method is used to analyze different alternatives and estimate alternatives according to the level of utility where the values of the attributes are expressed in intervals to increase efficiency and increase accuracy in the decision-making process.
Optimizing LSTM with Grid Search and Regularization Techniques to Enhance Accuracy in Human Activity Recognition Budiarso, Zuly; Listiyono, Hersatoto; Karim, Abdul
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.433

Abstract

This study aims to enhance the accuracy of Long Short-Term Memory (LSTM) models for human activity recognition using the UCI Human Activity Recognition (HAR) dataset. The dataset comprises time-series data from accelerometer and gyroscope sensors on smartphones worn by 30 volunteers as they performed everyday activities such as walking, climbing stairs, descending stairs, sitting, standing, and lying down. Optimization was carried out using Grid Search for hyperparameter tuning and L2 regularization to prevent overfitting. The results show that the optimized LSTM model improved accuracy from 92.33% to 94.50%, precision from 93.12% to 94.61%, recall from 92.33% to 94.50%, and F1-score from 92.32% to 94.51% compared to the standard LSTM model. Despite these improvements, the study encountered several challenges, particularly in tuning hyperparameters, which required significant computational resources and time due to the complexity of the search space. Additionally, balancing regularization to prevent both underfitting and overfitting proved to be a delicate process. Further limitations include the model's performance variability with different sensor placements and potential overfitting to specific activity patterns. However, the implementation of hyperparameter optimization and regularization proved effective in improving the model's ability to recognize human activity patterns from complex sensor data. Therefore, this approach holds significant potential for broader applications in sensor-based human activity recognition systems, though further research is needed to address these limitations and generalize the findings.
Penerapan Complex Proportional Assessment (COPRAS) Dalam Penentuan Kepolisian Sektor Terbaik Ginting, Garuda; Alvita, Suha; Mesran, M; Karim, Abdul; Syahrizal, Muhammad; Daulay, Nelly Khairani
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (885.927 KB) | DOI: 10.30645/j-sakti.v4i2.254

Abstract

In determining the best Sector Police, many criteria must be had by every Sector Police to be the best. Some of the criteria used to determine the best Sector Police are Polsek services, completion of the crime, number of personnel, cleanliness of the Sectoral Police, and number of criminal acts. Determination of the best Sector Police to improve the performance of personnel so that they are encouraged to be better at doing their jobs than before. To avoid mistakes and be precise in determining the best Police Sector, a decision support system is needed. In this study, a case will be raised, namely finding the best alternative based on the existing criteria using the Complex Proportional Assessment (COPRAS) method. The COPRAS method is used to analyze different alternatives and estimate alternatives according to the level of utility where the values of the attributes are expressed in intervals to increase efficiency and increase accuracy in the decision-making process.
Pemanfaatan Artificial Intelligence Untuk Pemasaran Digital Bagi Kelompok Rumah Usaha Mikro, Kecil, dan Menengah Labuhanbatu Purnama, Iwan; Syahputra Harahap, Hasmi; Karim, Abdul; Sempurna, Teguh; Marha As, Pawa Niassa
JPM: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v5i2.2191

Abstract

The use of Artificial Intelligence (AI) in digital marketing has become an effective strategy in increasing the competitiveness of small and medium enterprises. This community service activity aims to identify the benefits and implementation of AI in digital marketing strategies for SME house groups in Labuhanbatu. By using AI technology, SMEs can increase marketing efficiency, target consumers more precisely, and optimize promotional costs. This study uses a qualitative descriptive method, by collecting data through interviews and observations on SME actors who have adopted AI in their marketing activities. The stages of implementing the community service program are carried out in five core stages, namely: Socialization (Digital Marketing and Cooperatives), Training (Use of Web, GPT Chat and Training in Making Cooperative Formation Documents), Application of Technology (computers, laptops, androids and others), Evaluation Assistance (product monitoring and evaluation and use of AI), and Program Sustainability (Improving good Marketing Results). The results of community service activities show that the use of AI can help SMEs in conducting market segmentation, content personalization, and customer service automation, which overall contribute to increased sales and consumer loyalty. However, challenges such as lack of digital literacy and limited resources are still major obstacles in the optimal implementation of AI. Therefore, regular training and mentoring are needed for UMKM house groups in Labuhanbatu so that they can make maximum use of AI in digital marketing strategies.
Studi Kasus Sengketa Konsumen Dalam E-Commerce Indrayani, Puput; Siregar, Feby Khairunnisya; Aritonang, Putri; Yulizar, Isma Ahmad; Aldiansyah, Ferry; Hamka, Muhammad; Karim, Abdul
Portal Riset dan Inovasi Sistem Perangkat Lunak Vol. 3 No. 1 (2025): Artikel Penelitian
Publisher : SoraTekno Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59696/prinsip.v3i1.77

Abstract

Perkembangan e-commerce yang pesat membawa berbagai kemudahan bagi konsumen dalam bertransaksi. Namun, hal ini juga memunculkan berbagai permasalahan hukum terkait sengketa konsumen, seperti penipuan, barang tidak sesuai deskripsi, keterlambatan pengiriman, hingga ketidaksesuaian kebijakan pengembalian barang. Penelitian ini bertujuan untuk menganalisis berbagai kasus sengketa konsumen dalam e-commerce, faktor-faktor penyebabnya, serta mekanisme penyelesaian yang tersedia, baik melalui mediasi, arbitrase, maupun jalur hukum. Metode penelitian yang digunakan adalah studi kasus dengan pendekatan kualitatif, mengkaji regulasi yang berlaku serta berbagai kasus yang telah terjadi. Hasil penelitian menunjukkan bahwa perlindungan konsumen dalam transaksi digital masih menghadapi berbagai tantangan, terutama dalam hal kesadaran konsumen terhadap hak-haknya serta efektivitas penegakan hukum. Oleh karena itu, diperlukan perbaikan regulasi serta peningkatan edukasi bagi konsumen dan pelaku usaha dalam e-commerce guna menciptakan ekosistem perdagangan digital yang lebih aman dan adil.
Co-Authors 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 Cheylani Lukito, Salwa Christiorenfa Br Haloho, Agatha Daulay, Nelly Khairani Dayu Sari, Arini Dhea Ananda, Tasya Efendi Hutagalung, Jhonson Efendi, Safri Erlin Windia Ambarsari Fadli, Muhammad Bagus Fadlina Fahmi Rizal Febriani, Budi Fifto Nugroho Garuda 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 Iwan Purnama Jahril Jeperson Hutahaean Kraugusteeliana Kraugusteeliana Kusmanto Kusmanto Kusmanto Kusmanto M. Rafi Mardinata, Erwin Marha As, Pawa Niassa Meryance Viorentina Siagian Mesran, Mesran Mhd Ali Hanafiah Mhd Bobbi Kurniawan Nasution 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 Purba, Elvitrianim Purba, Elvitrianim Putra Juledi, Angga Putri, Nathania Rahman, Ben Rizal, Chairul Rohani Rohani 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 Triana, Dewi Trianovie, Sri Trianovie, Sri Unung Verawardina Uswatun Hasanah Vita S. Siregar, Siony Wilson, Eric Yessica Siagian Yulizar, Isma Ahmad Zebua, Yuniman Zulkifli Zulkifli Zuly Budiarso