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All Journal Bulletin of Electrical Engineering and Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Nasional Komputasi dan Teknologi Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sains dan Teknologi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Sistem Informasi dan Teknologi Jaringan International Journal of Basic and Applied Science Jurnal Media Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) DISTANCE: Journal of Data Science, Technology, and Computer Science Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Nuansa Informatika Jurnal Sistem Informasi Galuh Jurnal Ilmu Pendidikan dan Humaniora Jurnal Pengabdian Masyarakat Nauli
Manurung, Jonson
Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Physics Social Sciences Transportation

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Design of a Web-Based Notary Deed Archiving System Application at the Office of Notary Ani Yaniatin Pitaloka, S.H. Ahmad Firdaus, Eryan; Hidayat, Topik; Manurung, Jonson; Hidayati, Ajeng; Azhar Prabukusumo, Muhammad
NUANSA INFORMATIKA Vol. 19 No. 1 (2025): Nuansa Informatika 19.1 Januari 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i1.254

Abstract

A notarial deed is a legal document that has strong evidentiary power in court and in various legal transactions. Based on Law No. 2 of 2014 concerning Amendments to Law No. 30 of 2004 on Notary Position (Notary Law), this law regulates the duties, responsibilities, and authority of notaries, including provisions on the archiving and security of documents handled by notaries. Therefore, it is important for notary institutions, lawyers, and various related parties to manage these notarial deeds carefully and effectively, one of which is by paying attention to the archiving of notarial deeds. The archiving of notarial deeds is an important practice in the legal world involving the storage, maintenance, and recording of notarial deed documents that govern legal agreements, property transactions, and other legal actions. By designing a web-based archiving application system, the goal of addressing the risk of damage or loss of physical documents is effectively achieved. The implementation of digital storage methods reduces the likelihood of physical documents being damaged or lost. Document accessibility is also enhanced by the presence of search and digital storage features. Application design steps, such as needs analysis, use case diagrams, activity diagrams, and interface design, provide a comprehensive overview of the desired features and system workflow. This design ensures that user needs are met and the application is easy to use.
Leveraging the BERT Model for Enhanced Sentiment Analysis in Multicontextual Social Media Content Saragih, Hondor; Manurung, Jonson
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 2 (2024): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2024.766.pp82-89

Abstract

The increasing prevalence of social media platforms has led to a surge in user-generated content, necessitating advanced techniques for accurate sentiment analysis. This study investigates the application of the BERT model for sentiment analysis on multicontextual social media content, aiming to enhance sentiment classification accuracy by leveraging contextual embeddings. The research objectives include examining the effectiveness of BERT in capturing sentiments across diverse social media posts and evaluating its performance in comparison to traditional methods. The methodology involves tokenizing text content, converting tokens into contextual embeddings using BERT, and integrating multimedia features for a comprehensive sentiment analysis framework. The results from a numerical example demonstrate that the BERT model achieves a high probability of correctly classifying sentiments, with a notable improvement in accuracy and a low cross-entropy loss. These findings underscore the model's capability to understand contextual nuances and its potential to optimize social media monitoring and analysis processes. The study also highlights limitations such as the need for larger and more diverse datasets and the inclusion of multimedia content to enhance generalizability. Future research should explore hybrid models and address ethical considerations to ensure data privacy and mitigate biases. This work contributes to advancing theoretical frameworks and offers practical implications for businesses and marketers seeking to leverage sentiment analysis for informed decision-making and improved customer engagement strategies.
Analisis Algoritma C4.5 Dan Fuzzy Sugeno Untuk Optimasi Rule Base Fuzzy Jonson Manurung, Jonson Manurung; Bosker Sinaga, Bosker Sinaga; Paska Marto Hasugian, Paska Marto Hasugian; Logaraj, Logaraj; Sethu Ramen, Sethu Ramen
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2488

Abstract

Logika fuzzy dapat mengatasi ketidakmampuan matematika konvensional untuk model sistem nonlinear. Fuzzy sugeno merupakan salah satu metode yang sering digunakan dalam logika fuzzy. Penggunaan metode sugeno dapat mengatasi masalah sistem non linear. Kelemahan dari logika fuzzy adalah meningkatnya beban komputasi yang bertambah secara eksponensial seiring dengan bertambahnya jumlah variabel dan jumlah aturan dalam logika fuzzy. Beberapa cara telah dilakukan oleh para peneliti sebelumnya untuk mengurangi beban komputasi, diantaranya dengan mengurangi sejumlah aturan dalam logika fuzzy. Mengurangi sejumlah aturan akan berdampak pada tingkat akurasi fuzzy yang berkurang. Pada penelitian ini, menggunakan algoritma C4.5 sebagai optimasi rule fuzzy. Hasil perbandingan metode fuzzy sugeno yang diintegrasikan dengan algoritma C4.5 mendapatkan hasil akurasi sebesar 88,57 %. Jumlah luaran yang awalnya 288 rule menjadi hanya 57 rule, hal tersebut menyebabkan beban komputsi berkurang. Disamping beban komputasi yang berkurang, hal tersebut berdampak pada berkurangnnya tingkat akurasi.
Performance Comparison of Naive Bayes and Support Vector Machine Algorithms in Spambot Classification in Emails Manurung, Jonson; Saragih, Hondor
International Journal of Basic and Applied Science Vol. 13 No. 3 (2024): Dec: Optimization and Artificial Intelligence
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v13i3.522

Abstract

In the ever-growing digital era, email spam is a serious threat that affects user productivity and information security. This study aims to analyze the comparative effectiveness of Naive Bayes and SVM algorithms with radial basis function (RBF) kernels in classifying spambots in emails. The methodology used includes collecting email datasets, applying both algorithms for classification, and evaluating performance using accuracy, precision, recall, and f1-score metrics. The results showed that SVM RBF performed better than Gaussian Naive Bayes, with significant improvements in all evaluation metrics. These findings provide important insights for the development of more accurate and efficient spam detection systems, and highlight the importance of selecting appropriate algorithms in the face of complex data classification challenges.
Comparison of k-means clustering with hierarchical agglomerative clustering for the analysis of food security of rice sector in Indonesia Sinaga, Ryan Fahlepy; M Azhar Prabukusumo; Manurung, Jonson
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 1 (2025): March: Intelligent Decision Support System
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i1.290

Abstract

Indonesia's food security depends on the availability and distribution of rice as a staple food. To support data-driven policies, this study applies K-Means Clustering and Hierarchical Agglomerative Clustering (HAC) to cluster 38 provinces based on rice consumption and production patterns. Data is sourced from BPS with attributes: rice consumption per capita, rice production, rice price per kg, and population. These variables were chosen because they reflect the balance of demand, supply, affordability, and food needs. The optimal number of clusters was determined as three, based on Elbow Method and Silhouette Score for K-Means, and Dendrogram and Cophenetic Correlation Coefficient (CCC) for HAC. The clustering results identify regional characteristics related to food security and support the formulation of more targeted rice distribution policies. This study also compares the effectiveness of both methods in supporting equitable and sustainable food distribution strategies.
Mapping ownership of luxury goods and household assets in cities in Jawa Tengah using logistic regression Hanan, Rohman Ali; Firdaus, Eryan Ahmad; Manurung, Jonson
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 1 (2025): March: Intelligent Decision Support System
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i1.292

Abstract

Ownership of luxury goods and household assets is a crucial issue in the Indonesian economy, particularly in Jawa Tengah, as it reflects complex socio-economic dynamics. This study aims to map the distribution of luxury goods and household assets across regencies and cities in Jawa Tengah and analyze the factors influencing their ownership using logistic regression. Socio-economic disparities in asset ownership are driven by factors such as education, income, and access to information, which contribute to broader social inequality and regional economic development.Using data from the Jawa Tengah Statistics Agency, this study examines variations in asset ownership, including motorcycles, refrigerators, and land, across different regions. Findings indicate that regions with higher motor vehicle ownership tend to exhibit stronger economic welfare compared to those with lower asset ownership. Beyond economic factors, psychological and social aspects, including social status and religious influences, also shape decisions regarding luxury goods acquisition.This research contributes to the literature by addressing the underexplored local context of asset ownership in Indonesia. The findings provide insights for policymakers in designing more inclusive and responsive socio-economic policies, aiming to reduce disparities and promote equitable regional development.
Implementation of TOPSIS method in decision support system for used motorcycle purchase recommendation Putra, Muhammad Ridho Alghifari; Manurung, Jonson; Hidayati, Ajeng
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 2 (2025): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i2.289

Abstract

The selection of used motorcycles involves evaluating multiple criteria, such as price, production year, transmission type, vehicle type, mileage, fuel consumption, and engine capacity. This complex decision-making process often leads buyers to rely on subjective judgments or third-party recommendations, which may result in suboptimal choices. To address this issue, this research develops a decision support system based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a Multi-Criteria Decision Making (MCDM) method, which ranks alternatives based on their proximity to the ideal solution. The study introduces innovation by applying TOPSIS to the specific context of used motorcycle selection, providing a data-driven, objective approach in contrast to conventional methods. A quantitative approach was employed, with data collected from online marketplaces and authorized dealerships. The results indicate that the 2019 Honda Revo, priced at Rp. 8,600,000, is the most optimal choice, achieving the highest preference score of 0.862887804. The effectiveness of the TOPSIS method in structuring the selection process ensures a more systematic and accurate decision-making process. Furthermore, the study highlights the influence of key criteria, such as fuel efficiency and mileage, in determining the ranking of alternatives. Future research should focus on integrating additional factors, such as maintenance history and vehicle condition, and exploring the development of web-based or mobile platforms to improve real-world implementation and enhance user accessibility. This system contributes to smarter, more informed decision-making in the used vehicle market, offering a significant advancement over traditional selection methods.
Heart disease prediction using machine learning models Vernando, Deden; Manurung, Jonson; Saragih, Hondor
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 2 (2025): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i2.291

Abstract

Heart disease remains one of the leading causes of death globally, with mortality rates continuing to rise each year. Early detection is critical to reducing the burden of this disease; however, conventional diagnostic methods are often costly, time-consuming, and reliant on specialist expertise. This study aims to evaluate the effectiveness of four machine learning (ML) algorithms—Decision Tree (DT), Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM)—in predicting heart disease using clinical datasets. The methodology involves data preprocessing, feature selection using the Random Forest algorithm, and performance evaluation through metrics such as accuracy, precision, recall, F1-score, and support. Experimental results indicate that KNN achieved the highest accuracy after feature selection, while SVM demonstrated the highest recall despite lower precision. RF offered the most balanced performance, making it a reliable model for real-world medical applications. These findings highlight the importance of selecting appropriate algorithms and features to improve the performance of predictive models. The study suggests that future research should incorporate larger datasets, apply systematic hyperparameter tuning, and explore deep learning techniques to further enhance prediction accuracy.
Sosialisasi Dan Edukasi Tentang Keamanan Data Dan Privasi Di Era Digital Untuk Meningkatkan Kesadaran Dan Perlindungan Masyarakat Manurung, Jonson; Sihombing, Agus Putra Emas; Pandiangan, Boyner
Jurnal Pengabdian Masyarakat Nauli Vol. 2 No. 1 (2023): Agustus, Jurnal Pengabdian Masyarakat Nauli
Publisher : Marcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/nauli.v2i1.103

Abstract

Pengabdian ini melibatkan berbagai kegiatan, termasuk seminar, workshop, pelatihan khusus, dan kampanye sosial media. Melalui pendekatan ini, para peserta (Pemuda Pemudi HKBP Simalingkar Medan) diberikan pemahaman tentang ancaman dan risiko keamanan data, serta praktik keamanan digital yang tepat. Hasil dari pengabdian ini menunjukkan adanya peningkatan kesadaran masyarakat tentang pentingnya keamanan data dan privasi. Peserta pengabdian telah mengubah perilaku dalam menggunakan teknologi dengan lebih bijaksana, termasuk dalam penggunaan kata sandi yang kuat dan pengaturan izin privasi pada akun-akun online mereka. Kampanye sosial media juga berhasil mencapai partisipasi aktif dari masyarakat dalam menyebarkan pesan keamanan data. Kolaborasi dengan lembaga pendidikan, pemerintah, dan organisasi non-profit berkontribusi dalam kesuksesan pengabdian ini dengan memperluas cakupan dan dampak kegiatan sosialisasi dan edukasi. Pengabdian ini menggarisbawahi pentingnya edukasi dan sosialisasi tentang keamanan data dan privasi di era digital dalam menghadapi risiko dan ancaman keamanan. Dengan pemahaman yang lebih baik dan praktik keamanan yang tepat, masyarakat dapat menggunakan teknologi dengan bijaksana dan melindungi data pribadi mereka secara lebih efektif. Pengabdian kepada masyarakat ini menjadi langkah penting dalam menciptakan lingkungan digital yang lebih aman dan dapat dipercaya bagi masyarakat
Sistem Pendukung Keputusan Penilaian Kinerja Pegawai RSUD Dr. Hadrianus Sinaga Dengan Menggunakan Metode Multi Factor Evaluation Process: Sistem Pendukung Keputusan Penilaian Kinerja Pegawai RSUD Dr. Hadrianus Sinaga dengan Menggunakan Metode Multi Factor Evaluation Process Kanur L. P. Situmorang; Manurung, Jonson
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i2.1557

Abstract

Rumah Sakit Umum Daerah (RSUD) DR. Hadrianus Sinaga setiap tahunnya memberikan penghargaan kepada pegawai yang berprestasi. Dalam proses penilaian pegawai berprestasi masih secara manual dan sangat tidak efektif, sehingga dirasa kurang optimal dan memerlukan banyak waktu baik dalam menyusun laporan maupun proses memutuskan calon pegawai berprestasi. Untuk menyelesaikan persoalan tersebut, maka diperlukan suatu Sistem Pendukung Keputusan (SPK) untuk menbantu pihak rumah sakit dalam memilih pegawai yang berkualitas dan berpretasi. Dalam pengambilan keputusan, metode yang dipakai dalam SPK ini adalah Multi Factor Evalution Process (MFEP). Pada metode MFEP ini pengambilan keputusan dilakukan dengan memberikan pertimbangan subjektif dan intuitif terhadap faktor yang dianggap penting. Pertimbangan tersebut berupa pemberiaan bobot atas multifactor yang terlibat dan dianggap penting. Aplikasi yang digunakan dalam pembuatan sistem ini adalah bahasa pemprogramana PHP untuk pembuatan programnya dan MySql untuk pembuatan database. Dengan menggunakan sistem pendukung keputusan ini, pemilihan pegawai berprestasi pada RSUD DR. Hadrianus Sinaga menjadi lebih efektif dan efisien serta menutup kemungkinan terjadinya kecurangan. Dari hasil pengujian system dan hasil analisa data bahwa A8 (Sumihar Tamba) mendapat nilai tertinggi dengan Bobot Evaluasi 81 dan Paling rendah A4 (Lenni Simbolon) dengan Bobot Evaluasi 70,75
Co-Authors Agus Firmansyah Agustina Simangunsong Al Hashim, Safa Ayoub Amran Sitohang Andri Budiman, Mohammad Azhar Prabukusumo, Muhammad Barus, Nadela Bosker Sinaga Bosker Sinaga Bosker Sinaga, Bosker Sinaga Br Sitepu, Siska Feronika Br Tarigan, Nera Mayana Dhaifullah, Rendi Hanif Erika Novianti Eryan Ahmad Firdaus Febrian Wahyu Christanto Ferdinand Tharorogo Wau Firdaus Laia Firdaus Situmorang Hanan, Rohman Ali Hardy Priyatno Ambarita Harpingka Sibarani Hasugian , Paska Marto Hidayati, Ajeng Hondor Saragih Johanes Perdamenta Sembiring Kadin Darlianto Tinambunan Kanur L. P. Situmorang Logaraj Logaraj Logaraj, Logaraj M Azhar Prabukusumo Maria Siahaan Maya Theresia Br. Barus Maya Theresia Br. Barus Merlin Helentina Napitupulu Mina Kumari Muthmainnah, Ihmatull Nuriansyah, Agam Pandiangan, Boyner Poltak Sihombing Prabukusumo, Muhammad Azhar Putra, Muhammad Ridho Alghifari Ramen, Sethu Rinaldy Chaniago Sawaluddin Sawaluddin, Sawaluddin Sethu Ramen Sethu Ramen, Sethu Ramen Sidiq, Maulana Sihombing, Agus Putra Emas Sihotang, Amran Silalahi, Monalisa Hotmauli Simangunsong, Humala Sinaga, Ryan Fahlepy Sri Kumala Sari Topik Hidayat Uzitha Ram Vernando, Deden