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All Journal Journal of Applied Geospatial Information Jurnal Mantik Penusa JOURNAL OF SCIENCE AND SOCIAL RESEARCH CSRID (Computer Science Research and Its Development Journal) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer International Journal of Economics Development Research (IJEDR) Journal of Intelligent Decision Support System (IDSS) Jurnal Teknik Informatika (JUTIF) International Journal of Basic and Applied Science Jurnal Mandiri IT Jurnal Minfo Polgan (JMP) Jurnal Pengabdian Kepada Masyarakat Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Venus: Jurnal Publikasi Rumpun Ilmu Teknik Indonesia Bergerak: Jurnal Hasil Kegiatan Pengabdian Masyarakat Jurnal Bisnis Digital Global Science: Journal of Information Technology and Computer Science Jurnal Teknik Informatika dan Teknologi Informasi
Mutiara S. Simanjuntak
Politeknik Negeri Lhokseumawe
Agriculture, Biological Sciences & Forestry Humanities 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 Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA DOKTER MENGGUNAKAN METODE WEIGHT PRODUCT (WP) BERBASIS WEB Junifa, Dira; Aisyah, Siti; Simanjuntak, Angelina Cikita Mutiara; Ginting, Syahril
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2019): 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 | Full PDF (264.645 KB) | DOI: 10.34012/jusikom.v3i1.561

Abstract

The doctor is someone who because of his knowledge tries to heal people who are sick. One effort to spur doctors' performance is by conducting a performance evaluation. At present the job evaluation system at Royal Prima Medan Hospital is still done conventionally and the results of the assessment are subjective. Based on this, the author designed a Decision Support System for Evaluating Doctor Performance using WEB-based Weighted Product (WP). There are five criteria in evaluating doctor's performance including assessment of patient care, interpersonal and communication skills, writing and completeness of medical records, professionalism / work behavior. The research was conducted by looking for the weight values of the criteria and then processing the ranking from the doctor's judgment. Keywords: Decision Support System, Weight Product, WEB
Design of Digital Mobile Application for Marine and Coastal Observation in Northern part of Sumatra Matondang, Aprima A.; Simanjuntak, Mutiara; Simangunsong, Juanto
Journal of Applied Geospatial Information Vol. 8 No. 2 (2024): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v8i2.9166

Abstract

We have successfully developed a mobile program to address the challenges of marine and coastal observation serves as a solution to the communication gap between local peoples with ocean issues. In this app, we examine common of marine problems encountered by civilian and discuss the methods used to diagnose and resolve these issues. Some preventive measures can be taken are mangrove replanting programs, satellite and drone monitoring systems to monitor illegal activities at sea and campaigns to reduce the use of single-use plastics and raise awareness of the importance of marine conservation. These can be combined in a digital application connected to a smartphone. The application can answer future challenges related to observation and preventive measures for strengthening and mitigating disasters in marine and coastal ecosystems that can support maritime-based economic resilience in Indonesia. The application is MyOcean that can handle several problems related with ocean issues. The following displays the home page and registration page on the web-based boarding search application. By utilizing these applications, users can improve their understanding, management, and preservation of coastal areas. These applications are suitable for various groups, including fishermen, government, and the general public.
Enhancing The Precision Detection and Grading of Diabetic Retinopathy through Digital Retinal Imaging Using 3D Convolutional Neural Networks Allwine, Autho; Simanjuntak, Mutiara S; Pulungan, Wahyu Aji
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4387

Abstract

Diabetic retinopathy (DR) is a pressing global health issue that affects the retina and is closely linked to diabetes, leading to vision impairment and blindness, particularly in adults. With the rising incidence of diabetes, the need for efficient and accurate DR screening is critical for early intervention and improved patient outcomes. Automated screening solutions can streamline this process, allowing healthcare professionals to focus more on patient care.In this study, we harnessed advanced deep learning techniques, specifically 3D convolutional neural networks (3D-CNNs), to classify DR into binary categories (presence or absence) and five multiclass categories: mild, moderate, no DR, proliferative DR, and severe DR. Our goal was to enhance diagnostic Precision in ophthalmology. To optimize our models, We embraced two methods transformative data augmentation: random shifting and random weak Gaussian blurring, empowering our model to reach new heights,as well as their combination. Our results showed that, for binary classification, the combined augmentation achieved significant success, The multiclass model was trained without any data augmentation excelled in Precision. These findings highlight the importance of large, high-quality research datas in deep learning algorithms. By leveraging advanced methodologies and robust data, we can transform diabetic retinopathy screening, promoting earlier detection and better treatment outcomes for those affected.
TECEPEBI SIMULASI DAN CHATBOT DALAM PENGAJARAN BAHASA INGGRIS STUDI KASUS: UPT SD NEGERI 060941 Manullang, Evi Yanti; Nissa, Fachrun; Simanjuntak, Mutiara S.; Iskandar, Iskandar; Riduan, Suwardy
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4567

Abstract

Abstract: English learning at the elementary school level is still limited, especially in developing authentic speaking skills. This research developed TeCePeBi (Intelligent Technology for Speaking Learning), a chatbot-based interactive media + simulation that applies a communicative approach. Using the ADDIE R&D model, the system was designed, built, and tested on students of SD Negeri 060889, Medan (n = 45). The initial phase of the trial (1020 students) resulted in a prototype that was then tested on a larger group (30 students) for 8 weeks. Evaluations include a pre/posttest of speaking skills, a confidence questionnaire, and a satisfaction interview. The results showed a significant increase in speaking scores (Δ = + 18.2 points, p < 0.01) as well as an improvement in the perception of self-confidence (the average score increased from 3.1 to 4.3 on a scale of 5). In addition, 87% of students reported a more independent and flexible learning experience. These findings confirm the potential of TeCePeBi as an AI-based solution to improve English spoken competence in elementary school students. Keyword: tecepebi; primary school; speaking skills; chatbot; Simulation Abstrak: Pembelajaran bahasa Inggris pada tingkat Sekolah Dasar (SD) masih mengalami keterbatasan, terutama dalam mengembangkan keterampilan berbicara yang autentik. Penelitian ini mengembangkan TeCePeBi (Teknologi Cerdas untuk Pembelajaran Berbicara), sebuah media interaktif berbasis chatbot + simulasi yang menerapkan pendekatan komunikatif. Menggunakan model R&D ADDIE, sistem dirancang, dibangun, dan diuji pada siswa SD Negeri 060889, Medan (n = 45). Uji coba tahap awal (10‑20 siswa) menghasilkan prototipe yang kemudian diuji pada kelompok lebih besar (30 siswa) selama 8 minggu. Evaluasi meliputi pre‑/post‑test keterampilan berbicara, kuesioner kepercayaan diri, dan wawancara kepuasan. Hasil menunjukkan peningkatan signifikan skor berbicara (Δ = + 18,2 poin, p < 0,01) serta peningkatan persepsi kepercayaan diri (skor rata‑rata naik dari 3,1 menjadi 4,3 pada skala 5). Selain itu, 87 % siswa melaporkan pengalaman belajar yang lebih mandiri dan fleksibel. Temuan ini menegaskan potensi TeCePeBi sebagai solusi berbasis AI untuk memperbaiki kompetensi lisan bahasa Inggris pada siswa SD. Kata kunci: tecepebi; sekolah dasar; keterampilan berbicara; chatbot; simulasi
MSME Financial Performance: The Role of Green Accounting, Green Intellectual Capital, and Fintech in the Sustainability of MSMEs Aristantya, Selvi; Sairun, Aryani; Simanjuntak, Mutiara S.; Lubis, Irna Triannur
International Journal of Economics Development Research (IJEDR) Vol. 6 No. 6 (2025): International Journal of Economics Development Research (IJEDR)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ijedr.v6i6.9285

Abstract

This study examines and tests personality-mediated management behaviour in MSMEs in Semarang City in relation to financial attitudes and financial experience. Version 25 of SPSS was used to process the data. In Semarang City, 88 MSME business actors made up the sample. The study findings indicate that there is a substantial relationship between personality and financial views as well as experience. There is a considerable impact of financial attitudes on management conduct. Regarding how management conduct is impacted by financial experience, personality has a major impact on how managers behave. Not only does financial experience have a substantial impact on management behaviour mediated by personality, but financial views also have a big influence. Thus, each of the seven current hypotheses has a noteworthy and beneficial impact.
Mental disorder classification with exploratory data analysis (EDA) Simangunsong, Juanto; Simanjuntak, Mutiara S; Simanjuntak, Nurmala Dewi
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.252

Abstract

Classification of mental disorders is the process of grouping mental disorders into categories based on their symptoms, causes and consequences.  EDA is a data analysis strategy that emphasizes open-mindedness, creativity and diverse perspectives. EDA aims to explore as much data as possible, without imposing previous assumptions or models, until a coherent, coherent story emerges. EDA can help generate new hypotheses, identify patterns and outliers, and uncover underlying structures and relationships in data. This paper shows how EDA can be used to analyze and understand mental disorders data from a variety of sources and perspectives. We used EDA methods to explore the characteristics, prevalence, and distribution of mental disorders, as well as the relationships and interactions between mental disorders and other variables. We also compared EDA results with mental disorder classification systems such as the Diagnostic and Statistical Manual of Mental Disorders (DSM). We show that EDA can provide a more comprehensive and nuanced understanding of mental disorder data, as well as highlight the challenges and limitations of mental disorder classification. We hope this paper will illustrate the potential and benefits of EDA for mental disorders research and practice
¬¬¬Design of search information system using mobile application for car problems in Deli Serdang regency Matondang, Aprima; Simanjuntak, Andrean; Simanjuntak, Mutiara; Simangunsong, Juanto
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.326

Abstract

We successfully developed the mobile program that can solve the car problems that may be difficult to find the location of garage service. We developed MyBengkel as the solution of the problems between car owners and garage location. We delve into the common types of car problems encountered by drivers and explore the methods used to diagnose and resolve them. From routine maintenance to complex repairs, we will discuss the underlying causes of these issues and examine the technologies and tools employed in modern automotive diagnostics. The location interest in Deli Serdang regency and ist surrounding. The data compilation shows the total casualties in 2021 and 2022 is ranging at 80 – 120 cases in Deli Serdang with various roads type. This application makes it easy to get information on car problems facilities, appropriate prices and boarding car and garage service locations for local peoples and increases promotional opportunities for the garage owners in Deli Serdang locations
Etika Dan Tanggung Jawab Digital Bagi Siswa/I SMP Negeri 2 Sihotang Kabupaten Samosir Mutiara S. Simanjuntak; Juanto Simangunsong; Aprima Matondang
Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Vol. 1 No. 1 (2024): Januari: Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/transformasi.v1i1.79

Abstract

SMP Negeri 2 Sihotang is located in Samosir Regency, which is one of the koban schools for flash floods that occur at the end of 2023. This PKM aims to increase awareness of ethics and digital responsibility among junior high school students. With the widespread use of digital technology, especially among teenagers, it is important to introduce the concept of ethics and responsibility in its use. This PKM will adopt an educative approach that involves students directly in the understanding of digital ethics and its impact on individuals and society. The method used with the Socialization method, as well as the creation of multimedia-based educational materials. The main target of this PKM is students of SMP Negeri 2 Sihotang in Samosir Regency. Through an approach that focuses on student participation, it is expected to create a better understanding of the importance of acting responsibly in a digital environment. The expected outcome of this PKM is an increase in students' awareness of ethical and responsible practices in the use of digital technology, as well as their ability to take wise decisions in online situations. Thus, this PKM is expected to make a positive contribution to the formation of good digital character and behavior among students of SMP Negeri 2 Sihotang and the wider community.
INTEGRASI PROJECT-BASED LEARNING UNTUK MENINGKATKAN CAPAIAN PEMBELAJARAN PRAKTIKUM COMPUTER VISION BERBASIS DEEP LEARNING Simanjuntak, Mutiara S; Manalu, Pius Deski
Jurnal Bisnis Digital Vol 5, No 2 (2025): Vol 5, No 2 (2025) : Edisi Juli - Desember 2025
Publisher : Fakultas Ekonomi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37598/bidig.v5i2.2647

Abstract

Pembelajaran praktikum computer vision berbasis deep learning pada pendidikan vokasi masih didominasi oleh pendekatan tutorial konvensional yang berfokus pada prosedur teknis dan kurang mendorong keterlibatan aktif serta kemampuan pemecahan masalah mahasiswa. Penelitian ini bertujuan menganalisis pengaruh integrasi Project-Based Learning terhadap peningkatan capaian pembelajaran mahasiswa pada mata kuliah Praktikum Computer Vision berbasis Deep Learning. Metode penelitian yang digunakan adalah kuasi-eksperimen dengan pendekatan deskriptif kuantitatif menggunakan desain satu kelompok dengan pengukuran sebelum dan sesudah perlakuan. Kebaruan penelitian ini terletak pada perancangan Project-Based Learning yang terintegrasi secara sistematis dalam praktikum computer vision pendidikan vokasi serta pengukuran capaian pembelajaran yang mencakup aspek kognitif, psikomotorik, dan afektif. Hasil penelitian menunjukkan adanya peningkatan nilai rata-rata capaian pembelajaran mahasiswa setelah penerapan Project-Based Learning, yang diperkuat oleh nilai gain score dan hasil uji statistik yang signifikan. Temuan ini menunjukkan bahwa pembelajaran berbasis proyek mampu meningkatkan pemahaman konsep, kemampuan analitis, dan keterampilan implementatif mahasiswa. Penelitian ini menyimpulkan bahwa integrasi Project-Based Learning efektif diterapkan pada praktikum computer vision berbasis deep learning di pendidikan vokasi. Penelitian selanjutnya disarankan untuk melibatkan sampel yang lebih luas dan mengkaji variabel tambahan guna memperkuat generalisasi hasil penelitian.
Implementasi Algoritma Klasifikasi untuk Analisis Sentimen Media Sosial Tiktok Tahun 2025 Pius Deski Manalu; Mutiara Simanjuntak; Chairil Umri
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 1 (2025): April: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i2.5644

Abstract

TikTok has emerged as one of the fastest-growing social media platforms in 2025, especially among the younger generation. Beyond being a space for creative content sharing, TikTok has also become a vital platform for the exchange of public opinion, primarily through user comments. As user engagement intensifies, sentiment analysis on TikTok comments becomes increasingly essential to understanding public perception of various issues, trends, public figures, and brands. This study aims to analyze sentiment in TikTok user comments using machine learning classification algorithms. The research compares the performance of three widely used algorithms in text classification: Naive Bayes, Support Vector Machine (SVM), and Random Forest. A dataset of 5,000 public TikTok comments was collected through web scraping of trending videos from January to March 2025. The comments, written in Indonesian, underwent several text pre-processing steps, including tokenization, stopword removal, and stemming, to normalize the data. The TF-IDF method was then applied to extract numerical features from the textual data. A stratified data split was used to divide the dataset into training (80%) and testing (20%) subsets, ensuring balanced sentiment class distribution. Performance evaluation was conducted using accuracy, precision, recall, and F1-score metrics. Among the tested models, SVM achieved the highest accuracy of 89.7%, outperforming Naive Bayes and Random Forest across all metrics. These results indicate that SVM is particularly well-suited for classifying short, informal text such as TikTok comments. The findings contribute to the advancement of sentiment analysis in social media environments, specifically for Indonesian language data on TikTok. Moreover, the study provides valuable insights for industry stakeholders, marketers, and academic researchers seeking to implement data-driven public opinion analysis using machine learning techniques on emerging social media platforms.
Co-Authors Aji Priyambodo Allwine Arnold Pakpahan Baehaqi Chairil Umri Elshad Yusifov Ginting, Syahril Hongjie Dai Iskandar Iskandar Joel Panjaitan Juanto Simangunsong Juanto Simangunsong Junifa, Dira LUBIS, IRNA TRIANNUR Manalu, Pius Deski Manullang, Evi Yanti Nissa, Fachrun Nurafni Damanik Pieter Leuvanggi Hutagalung Pius Deski Manalu Pulungan, Wahyu Aji Regina Sirait - Rico Wijaya Riduan, Suwardy Rika Rosnelly Sairun, Aryani Selvi Aristantya Simangunsong, Juanto Simanjuntak, Andrean Simanjuntak, Nurmala Dewi Siti Aisyah Syofyan Anwar Syahputra Syofyan Anwar Syahputra Teddy Surya Gunawan Wanayumini