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All Journal International Journal Of Science, Technology & Management (IJSTM) Jurnal Pengabdian Masyarakat Gemilang (JPMG)
Juni Yanris, Gomal
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Aerospace Engineering Agriculture, Biological Sciences & Forestry 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Transportation

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Sosialisasi Pentingnya Pendidikan Berkarakter Dalam Upaya Menciptakan Generasi Bebas Narkoba di SMA Harapan Mandiri Tan Kim, Hek; Rostina, Rostina; Juni Yanris, Gomal; Lolita A. Pardede, Sovia; Wongsosudono, Corinna
Jurnal Pengabdian Masyarakat Gemilang (JPMG) Vol. 2 No. 1: Januari 2022
Publisher : HIMPUNAN DOSEN GEMILANG INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (260.01 KB) | DOI: 10.58369/jpmg.v2i1.51

Abstract

Pengabdian Kepada Masyarakat ini merupakan salah satu dari tugas Tridharma Perguruan Tinggi. Kegiatan ini dilakukan dalam bentuk webinar.Webinar ini dirancang sesuai dengan visi dan misi bagi siswa-siswidi sekolah SMA swasta Harapan Mandiri Medan dalam penerapan pendidikan berkarakter agar dapatmengantarkan mereka menjadi lebih matang dalam mengolah emosi dan menjadi lebih percaya diri sehingga tidak mudah dipengaruhi untuk menjadi pelaku penyalahgunaan narkoba, serta dapat meningkatkan kemampuan para siswa dalam mengembangkan potensi yang dimiliki sehingga lebih mampu untuk bereksplorasi dan berkreasi dalam hal-hal yang positif dan bermanfaat.Webinar ini perlu dilaksanakan untuk mendukung upaya Pencegahan dan Pemberantasan Penyalahgunaan dan Peredaran Gelap Narkoba (P4GN), sehingga semua siswa-siswi SMA Swasta Yayasan Perguruan Harapan Mandiri Medan dapat imun terhadap pengaruh jahat narkoba yang dapat mengancam kapan saja dan di mana saja, serta memaksimalkan peran tenaga pendidik dalam membentengi para siswa dari masalah narkoba yang dapat mengancam masa depan generasi bangsa, sekaligus mensterilkan lingkungan pendidikan dari pengaruh narkoba.Dari hasil webinar ini terlihat tingkat partisipasi siswa-siswi sekolah swasta SMA Harapan Mandiri yang antusias untuk mengikuti webinar tersebut dan bersemangat dalam kesungguhan untuk memperhatikan materi pembelajaran yang disajikan sehingga kegiatan ini dapat terlaksana dengan baik.
Design Of A Budget Processing Information System At Sat Reskrim Of Polres Labuhanbatu Web Based Martasya Berkat Silaen, Dian; Juni Yanris, Gomal; Nirmala Sari Hasibuan, Mila; Rohayani Hasibuan, Elysa
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1163

Abstract

Capital expenditures carried out by regional governments produce infrastructure in an area both for providing basic services to the community and to encourage regional governments to provide potential sources of local revenue. The Financial Report of the National Police of the Republic of Indonesia consists of a budget realization report, balance sheet, operational report, report on changes in equity and notes on the financial report as attached, which is the responsibility of the National Police which has been prepared based on an adequate internal control system. The aim of this research is to be able to design an information system for processing budget data to unit of Sat Reskrim the Polres Labuhanbatu is web-based so that it can help operational work, especially in processing financial data, to be more effective and efficient
Implementation of the K-Means Clustering Method in Clustering Poor Population in Bandar Kumbul Village, Labuhanbatu Regency Maharani, Aulia; Juni Yanris, Gomal; Aini Nasution, Fitri
International Journal of Science, Technology & Management Vol. 6 No. 1 (2025): January 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i1.1209

Abstract

Poverty is one of the crucial social problems in rural areas. The problem of poverty in rural areas is increasingly in the spotlight because of its broad impact on the community's economic and social sustainability. The varying levels of poverty require an appropriate analytical approach to design effective intervention programs. In an effort to understand and address this problem, this study uses the K-Means Clustering method to group the poor population. We use K-Means clustering to identify and group hamlets based on their poverty levels. This study aims to categorize the hamlets in Bandar Kumbul Village into multiple clusters according to their poverty levels, thereby identifying which hamlets necessitate more focused attention. The research methods used include collecting data on the number of poor people from 2013 to 2022 in each hamlet, data preprocessing, applying the Elbow method to determine the optimal number of clusters, and applying the K-Means Clustering algorithm to group the hamlets. The results of the study show that there are three main clusters with different characteristics. Cluster 0 includes Hutaimbaru and Mailil Julu hamlets with high poverty levels. Cluster 1 only includes the Pasir Sidimpuan hamlet, which has medium poverty levels. Cluster 2 includes Aek Mardomu, Bandar Kumbul, Mailil Jae, Sidodadi, and Singga Mata hamlets with low poverty levels. Variations in distance from the cluster center indicate significant differences in the distribution of poverty in each hamlet. The K-Means Clustering method is effective in identifying and grouping hamlets based on poverty levels, providing useful insights for the government and stakeholders to design more targeted intervention programs. Clusters with high poverty levels require immediate intervention, while clusters with medium and low poverty levels require maintenance and support to prevent an increase in poverty. This study provides a strong foundation for decision-making and policies to reduce poverty levels in Bandar Kumbul Village more effectively and sustainably.
Web-based Palm Oil Seedling Sales Information System (Case Study: CV. XYZ) Ramadhani, Siska; Sihombing, Volvo; Juni Yanris, Gomal
International Journal of Science, Technology & Management Vol. 6 No. 1 (2025): January 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i1.1213

Abstract

Oil palm seedling sales are one of the important aspects of the agricultural industry in Indonesia. However, conventional sales processes often encounter various obstacles, such as limited access to information for consumers, difficulties in inventory management, and low operational efficiency. To overcome these problems, this study aims to develop a Web-based Oil Palm Seedling Sales Information System at CV. XYZ. We designed this system to offer a comprehensive solution for sales management, encompassing stock recording and real-time transaction processing. This study uses a system development method with the waterfall method, in which the development stages include requirements, system design, implementation, verification, and maintenance. We collected data through direct observation at CV XYZ, interviews with management and customers, and related literature studies. Users then tested the prototype to identify potential problems and gather feedback for system improvement. According to the study's findings, the implementation of this web-based information system has resulted in increased efficiency in sales and inventory management. Users can easily access product information, place orders, and track the status of their orders. In addition, this system also allows integration with payment gateways, so that the transaction process becomes faster and safer. This system simplifies customer data management, sales recording, and financial report analysis from a management standpoint. At CV. XYZ, the development of the Web-based Palm Oil Seedling Sales Information System positively impacted operational efficiency and effectiveness. This system not only increases customer satisfaction by providing faster and more transparent services, but it also helps management make more accurate decisions based on available data. We need to add more advanced data analysis features to forecast sales trends and market demands, and integrate the system with e-commerce platforms to broaden our market reach.
Implementation Of The Support Vector Machine Method In Predicting Student Graduation Abdillah, Syakira; Juni Yanris, Gomal; Sihombing, Volvo
International Journal of Science, Technology & Management Vol. 6 No. 1 (2025): January 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i1.1265

Abstract

Student graduation is an important indicator of the quality of education at a higher education institution. A high graduation rate not only indicates success in the learning process but also has a positive impact on the reputation of the institution. Conversely, a low graduation rate can be a signal of problems that require special attention. Various factors, both academic and non-academic, influence higher education institutions in ensuring timely student graduation. Therefore, we need a method that can accurately predict student graduation to carry out early intervention. This study aims to apply the support vector machine method in predicting student graduation. We chose this method due to its capacity to classify complex data. We use historical student data, such as Semester Achievement Index scores, as input variables to build a prediction model. We evaluate the model using precision, recall, and f1-score metrics. According to the study's findings, the support vector machine model's accuracy level is 71.20%. This method is good at predicting students who graduate with a precision of 95%, recall of 72%, and f1-score of 82%. However, the model's performance in predicting students who failed was less than satisfactory, with a precision of only 17%, a recall of 62%, and an f1-score of 26%. The imbalance in data between passed and failed students contributed to this result. The Support Vector Machine method effectively predicts student graduation for the majority class (passed), but requires special handling of the data imbalance to enhance the accuracy of predictions for the minority class (failed). Universities expect to use the results of this study to carry out early intervention and increase student graduation rates.
Co-Authors Abdillah, Syakira Aini Nasution, Fitri Corinna Wongsosudono Hek, Tan Kim Lolita A. Pardede, Sovia Maharani, Aulia Martasya Berkat Silaen, Dian Nirmala Sari Hasibuan, Mila Ramadhani, Siska Rohayani Hasibuan, Elysa Rostina Rostina Sihombing, Volvo