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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Mantik INFOKUM INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH Jurnal Matematika Dan Ilmu Pengetahuan Alam LLDikti Wilayah 1 (JUMPA) International Journal of Enterprise Modelling Law and Economics Jurnal Pengabdian Masyarakat Nauli
Jonhariono Sihotang
Universitas Putra Abadi Langkat, Sumatera Utara, Indonesia
Aerospace Engineering 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation

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IMPLEMENTATION OF GRAY LEVEL TRANSFORMATION METHOD FOR SHARPING 2D IMAGES Jonhariono Sihotang
INFOKUM Vol. 8 No. 1, Desembe (2019): Data Mining,Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (555.179 KB)

Abstract

At present image processing plays an important role, in which the processing does not only provide effects that make an image more artistic but can also improve the quality of the image itself. In the field of photography and film that is used in making animated advertisements on television, or creating effects from dangerous scenes that cannot be done by real humans. Not all digital images have a visual appearance that satisfies the human eye. Dissatisfaction can arise due to interference or lack of maximization of the image quality, such as spots appearing caused by the process of capturing imperfect images, lack of image sharpness due to uneven lighting and resulting in non-uniform intensity, image contrast is too low so objects are difficult separated from the background or interference caused by dirt that adheres to the image.
ANALYSIS OF SERVICE SATISFACTION LEVEL USING ROUGH SET ALGORITHM Jonhariono Sihotang
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

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Abstract

Data mining Is a technique that combines traditional data analysis techniques with algorithms for processing large amounts of data. Data mining can be used to perform data analysis and find important patterns in data. Data mining will be a benchmark or reference for making data mining processing decisions that can be done with the Rough Set method. Rough Set Method is one of the methods above that allows us to make decisions in hotel services because in this method there are formulations or stages of problem mechanics and a Result (decision) of a combination that may occur from the criteria above. From the results (decisions) derived from the processed data mining, it can be used as a reference for decision making. The Rought Set Method is a mathematical technique developed since 1980.
Evaluation of Information Technology Governance by Using CobIT 5 Framework at Higher Education Jonhariono Sihotang; Erwin Setiawan Panjaitan; Roni Yunis
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

IT (Information Technology) governance is an important thing in every organization where at this time Information Technology has become an important role in the sustainability of an organization. Therefore, to produce good organizational goals, good IT governance is needed as well. In this study, there are several problems that must be managed by the organization but have been summarized in the problem of resource optimization. To solve these problems, the COBIT 5 framework was chosen as a framework that would become a reference for solving these problems. There are 16 processes that will solve organizational problems, namely EDM02, EDM04, APO01, APO03, APO04, APO07, APO08, APO10, APO13, BAI01, BAI02, BAI04, DSS01, DSS03, DSS04, MEA01 and using PAM (Process Assessment Model) as tools to evaluate. The purpose of this study was to determine the level of organizational IT capabilities, and to analyze the gap between the organizational target value (to be) and the capability value obtained by the current organization (to be). After knowing the gap value, this value will be used as a basis for producing a recommendation for improvement for the organization.
A hybrid approach for adaptive fuzzy network partitioning and rule generation using rough set theory: Improving data-driven decision making through accurate and interpretable rules Jonhariono Sihotang; Aisyah Alesha; Juliana Batubara; Sonya Enjelina Gorat; Firta Sari Panjaitan
International Journal of Enterprise Modelling Vol. 16 No. 1 (2022): Jan: Enterprise Modelling
Publisher : International Enterprise Integration Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (489.041 KB) | DOI: 10.35335/emod.v16i1.54

Abstract

Data-driven decision making is vital in credit risk assessment and other areas. Complex datasets are hard to rule. We use adaptive fuzzy network partitioning, rough set theory, and rule generation to improve data-driven credit risk assessment. An adaptive fuzzy network partitioning algorithm is used to cluster the dataset. Each cluster instance receives fuzzy membership degrees. Next, rough set-based attribute reduction identifies credit risk assessment attributes inside each cluster. Finally, attributes are used to build accurate and understandable credit risk assessment criteria. A loan application dataset is used to test the suggested method. The results show successful loan application clustering and the creation of credit risk criteria for each cluster. Accurate predictions and interpretable rules improve credit risk assessment comprehension and decision-making. By merging adaptive fuzzy network partitioning, rough set theory, and rule generation, the hybrid methodology overcomes classic technique constraints. These methods create a comprehensive framework for credit risk assessment criteria that improves accuracy and interpretability. Financial institutions and credit providers may benefit from the approach. The proposed approach can be tested in multiple domains and extended to handle increasingly complicated datasets. Evaluating the methodology on real-world datasets and comparing it to existing methods can also reveal its practicality and efficacy. This research generates accurate and interpretable rules for data-driven credit risk assessment using a hybrid method. Adaptive fuzzy network partitioning, rough set theory, and rule generation can improve decision-making across domains
Optimization of Inventory Ordering Decision in Retail Business using Exponential Smoothing Approach and Decision Support System Jonhariono Sihotang
International Journal of Mechanical Computational and Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v12i2.121

Abstract

In the context of a challenging retail business, optimizing inventory ordering decisions is crucial to maintain product availability and avoid excessive storage costs. Decision Support System (DSS) approach with the application of exponential smoothing method has emerged as an effective solution to integrate data analysis and more precise decision making. This abstract discusses how exponential smoothing is used in optimizing inventory ordering decisions in retail businesses. We explain the concept of exponential smoothing as a forecasting technique that integrates historical data and future predictions. We also analyze the steps of implementing exponential smoothing in DSS, including smoothing parameters, initialization of initial levels, and forecast calculation. The benefits and challenges in the use of exponential smoothing are discussed in the context of inventory optimization and ordering decision making. The results show that exponential smoothing can provide forecasts that are more adaptive and responsive to changes in demand, with the potential to improve operational efficiency and customer satisfaction. Nonetheless, an understanding of the product characteristics and limitations of the method needs to be considered. This research illustrates how the use of exponential smoothing in DSS can provide valuable guidance for retailers in optimizing inventory and making inventory decisions.
New Method for Identification and Response to Infectious Disease Patterns Based on Comprehensive Health Service Data Desi Vinsensia; Siskawati Amri; Jonhariono Sihotang; Hengki Tamando Sihotang
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.4000

Abstract

Infectious diseases continue to pose a major threat to global public health and require early detection and effective response strategies. Despite advances in information technology and data analysis, the full potential of health data in identifying disease patterns and trends remains underutilised. This study aims to propose a comprehensive new mathematical model (new method) that utilises health data to identify infectious disease patterns and trends by exploring the potential of data-driven care approaches in addressing public health challenges associated with infectious diseases. The research methods used are exploratory data collection and analytical model development. The research results obtained mathematical models and algorithms that consider data of period, time, patterns, and trends of dangerous diseases, statistical analysis, and recommendations. Data visualisation and in-depth analysis were conducted in the research to improve the ability to respond to infectious disease threats and provide better decision-making solutions in improving outbreak response, as well as improving preparedness in addressing public health challenges. This research contributes to health practitioners and decision-makers.
Cutting-edge optimization methods for sustainable and resilient supply chains Fauziah, Sifa; Colicchia, Cagno Stone; Blackhurst, Alcívar; Sihotang, Jonhariono
Jurnal Matematika Dan Ilmu Pengetahuan Alam LLDikti Wilayah 1 (JUMPA) Vol. 41 No. 1 (2024): Mathematics and natural science
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah I Sumatra Utara (LLDikti I)

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Abstract

This research develops a comprehensive multi-objective optimization framework for sustainable and resilient supply chains, integrating cost efficiency, sustainability, and resilience into a unified model. The study advances traditional supply chain optimization, which often prioritizes singular objectives, by presenting a robust mathematical formulation that balances production, transportation, sustainability, and resilience investments. A numerical example demonstrates the model's practical application, highlighting key findings such as the ability to achieve cost efficiency while reducing environmental impact and enhancing supply chain robustness through moderate resilience investments. The research makes significant contributions by introducing a holistic approach to supply chain management, offering a practical tool for decision-makers. However, the model's complexity and reliance on accurate data present implementation challenges. Future research opportunities include incorporating non-linear relationships, applying advanced optimization techniques, and customizing the model for specific industries. This study underscores the importance of an integrated approach to supply chain optimization, providing a foundation for developing supply chains that are efficient, sustainable, and resilient in an increasingly dynamic global environment.
Impact of Poverty Reduction Programs on Healthcare Access in Remote Ar-eas: Fostering Community Development for Sustainable Health Amri, Siskawati; Sihotang , Jonhariono
Law and Economics Vol. 17 No. 3 (2023): October: Law and Economics
Publisher : Institute for Law and Economics Studies

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/laweco.v17i3.43

Abstract

This research investigates the impact of poverty reduction programs on healthcare access in remote areas, aiming to discern their effectiveness in addressing healthcare disparities. Employing a mixed-method approach, the study combines quantitative surveys, qualitative interviews, and focus group discussions to gather comprehensive data. The research reveals promising outcomes, demonstrating a significant increase in healthcare utilization among communities benefiting from poverty reduction initiatives. Improvements in healthcare infrastructure, positive health outcomes, and economic empowerment are evident, indicating the success of these programs in enhancing healthcare access. However, limitations including geographical constraints, potential biases, and sample representativeness are acknowledged. While acknowledging these constraints, the findings emphasize the significance of continued support for poverty reduction programs, policy development, and community involvement to sustain and expand the positive impact on healthcare access in remote areas. This research offers vital insights, contributing to academic knowledge, policy development, and practice, supporting the global agenda of sustainable development goals and advocating for more inclusive and equitable healthcare access in marginalized regions
Strategi Pengawasan Orang Tua dalam Mengelola Waktu Bermain Gadget Anak di Desa Pancurbatu Sihotang, Jonhariono; Manalu, Amran
Jurnal Pengabdian Masyarakat Nauli Vol. 2 No. 2 (2024): Februari, Jurnal Pengabdian Masyarakat Nauli
Publisher : Marcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/nauli.v2i2.141

Abstract

Penelitian ini bertujuan untuk menganalisis strategi pengawasan orang tua terhadap penggunaan gadget oleh anak-anak di Desa Pancurbatu, dengan memperhatikan tantangan dalam konteks pedesaan. Metode kualitatif dengan pendekatan studi kasus digunakan, melibatkan wawancara mendalam, observasi langsung, dan analisis dokumen terkait. Hasil penelitian menunjukkan variasi strategi pengawasan, seperti penetapan batasan waktu harian dan penggunaan aplikasi pengawasan khusus, namun masih terdapat kebutuhan akan edukasi yang lebih mendalam bagi orang tua. Implikasi penelitian ini adalah perlunya kolaborasi antara orang tua, komunitas lokal, dan lembaga pendidikan dalam menyusun strategi pengawasan yang lebih holistik dan berkelanjutan, guna mengoptimalkan penggunaan gadget oleh anak-anak di era digital.
Co-Authors Aisyah Alesha Blackhurst, Alcívar Colicchia, Cagno Stone Erwin Setiawan Panjaitan Firta Sari Panjaitan Hengki Tamando Sihotang Juliana Batubara Manalu, Amran Roni Yunis Sifa Fauziah, Sifa Siskawati Amri Sonya Enjelina Gorat Vinsensia, Desi