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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 Armada Informatika Journal Of Computer Science And Technology 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 Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Content Marketing Strategy in Increasing Student MSME Brand Awareness Pius Deski Manalu; Dedi Irawan; Mutiara S. Simanjuntak; Dody Hidayat
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.209

Abstract

This study is motivated by the low level of brand awareness among student-owned micro, small, and medium enterprises (MSMEs), which is mainly caused by the suboptimal implementation of digital marketing strategies, particularly content marketing. The main problem addressed in this research is how content marketing strategies can improve brand awareness among student MSMEs. This study aims to analyze the effect of content marketing on brand awareness and to identify effective content strategies that support such improvement. The research employs a quantitative approach using a survey method involving 100 student MSME actors in the Padang Bulan area. Data were collected through questionnaires using a Likert scale and analyzed using simple linear regression and t-test. The results indicate that content marketing has a positive and significant effect on brand awareness, with a regression coefficient of 0.68 and a significance value of 0.000 (less than 0.05). Additionally, about 78% of respondents actively use social media for marketing purposes, while only 65% ​​have structured content strategies. This finding suggests that improving content quality, creativity, and consistency can significantly enhance brand awareness. This study is expected to provide practical insights for student MSMEs in optimizing content-based digital marketing strategies.
Enhancing Cross-Organizational Healthcare Analytics Through Blockchain-Enabled Federated Learning Mutiara S. Simanjuntak; Aji Priyambodo; Elshad Yusifov
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 2 (2025): June: Global Science: Journal of Information Technology and Computer Science
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i2.176

Abstract

This study explores the integration of blockchain technology with federated learning (FL) to enhance cross-organizational healthcare analytics while ensuring privacy and data security. Federated learning allows multiple institutions to collaboratively train machine learning models without sharing sensitive patient data. Instead, local data is used to train models, and only model parameters are exchanged. However, privacy concerns and data sharing inefficiencies have hindered broader healthcare collaboration. Blockchain, a decentralized ledger technology, addresses these concerns by ensuring data integrity and transparency, providing an immutable and tamper-proof record of all transactions. This study investigates how the combination of blockchain and federated learning can overcome these challenges, facilitating secure and efficient data sharing between healthcare institutions. The study uses synthetic multi-institution healthcare datasets to simulate real-world collaboration scenarios. The blockchain-enabled federated learning system ensures that no raw patient data is shared, significantly reducing the risk of privacy breaches while still allowing healthcare institutions to collaborate on predictive model development. The results show that while there is a slight decrease in model accuracy compared to centralized methods, the trade-off is outweighed by the privacy and security benefits. Blockchain’s integration ensures that model updates are transparent, enhancing trust between institutions and reducing concerns about data integrity. Moreover, the use of blockchain’s smart contracts automates and enforces compliance, further streamlining collaboration. This research contributes to the field by demonstrating how blockchain-integrated federated learning can create a secure, scalable, and privacy-preserving framework for collaborative healthcare analytics. The findings underscore the potential for this approach to enhance healthcare outcomes and improve decision-making across institutions while ensuring patient data protection.
Optimalisasi Strategi Promosi Penerimaan Mahasiswa Baru Melalui Analisis Data Historis Husna Gemasih; Erika Fahmi Ginting; Suci Andryani; Mutiara S. Simanjuntak
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 2 (2026): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i2.753

Abstract

Promosi penerimaan mahasiswa baru (PMB) merupakan salah satu faktor penting dalam meningkatkan jumlah dan kualitas calon mahasiswa. Namun, strategi promosi yang belum memanfaatkan data historis secara optimal dapat menyebabkan kegiatan promosi kurang tepat sasaran. Penelitian ini bertujuan untuk menganalisis data historis PMB sebagai dasar dalam menyusun strategi promosi yang lebih efektif pada Jurusan Teknologi Informasi dan Komputer Politeknik Negeri Lhokseumawe. Penelitian menggunakan pendekatan kuantitatif deskriptif dengan memanfaatkan data sekunder PMB periode 2023–2025. Analisis dilakukan melalui tahapan data cleaning, transformasi data, statistik deskriptif, segmentasi calon mahasiswa, dan visualisasi data menggunakan dashboard analitik. Variabel yang dianalisis meliputi program studi, asal sekolah, jurusan asal sekolah, kecamatan, kabupaten/kota, provinsi, jalur masuk, dan sumber informasi pendaftar. Hasil penelitian menunjukkan bahwa sebagian besar pendaftar berasal dari Provinsi Aceh, khususnya Kabupaten Aceh Utara dan Kota Lhokseumawe, dengan dominasi lulusan jurusan IPA serta peminat terbesar pada Program Studi Teknik Informatika. Instagram dan website menjadi sumber informasi utama bagi calon mahasiswa. Pemanfaatan data historis melalui visualisasi data mampu memberikan informasi yang lebih komprehensif mengenai karakteristik calon mahasiswa sehingga dapat mendukung pengambilan keputusan dalam penyusunan strategi promosi PMB yang lebih terarah, efektif, dan berbasis data. New student admissions (PMB) promotion is an important factor in increasing the number and quality of prospective students. However, promotional strategies that do not optimally utilize historical data can result in less targeted promotional activities. This study aims to analyze historical PMB data as a basis for developing a more effective promotional strategy in the Information and Computer Technology Department of the Lhokseumawe State Polytechnic. The study uses a descriptive quantitative approach utilizing secondary PMB data for the 2023–2025 period. The analysis was carried out through the stages of data cleaning, data transformation, descriptive statistics, prospective student segmentation, and data visualization using an analytical dashboard. The variables analyzed included study program, school of origin, major of origin of school, sub-district, regency/city, province, admission route, and applicant information sources. The results show that most applicants come from Aceh Province, especially North Aceh Regency and Lhokseumawe City, with a predominance of science graduates and the greatest interest in the Informatics Engineering Study Program. Instagram and websites are the main sources of information for prospective students. The use of historical data through data visualization can provide more comprehensive information regarding the characteristics of prospective students so that it can support decision-making in developing more targeted, effective, and data-based PMB promotion strategies. 
Penerapan Data Mining Dalam Estimasi Harga Emas Menggunakan Algoritma Trend Moment Pada PT Victoeria Vici Erika Fahmi Ginting; Husna Gemasih; Suci Andriyani; Mutiara S. Simanjuntak; Chindi Dwi Lestari Nainggolan
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 2 (2026): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i2.754

Abstract

Emas merupakan salah satu jenis komoditi yang paling banyak diminati untuk tujuan investasi, karena dipandang sebagai instrumen yang lebih aman dibandingkan saham serta memiliki nilai jual yang selalu bergerak mengikuti kondisi pasar. PT Victoeria Vici, sebagai pelaku usaha perhiasan emas custom, menghadapi kendala dalam menentukan estimasi harga jual kepada pelanggan, sebab proses pengerjaan pesanan custom membutuhkan waktu hingga 14 hari, sementara harga emas bergerak fluktuatif dan tidak terstruktur setiap harinya sehingga estimasi harga menjadi tidak akurat dan tidak efektif. Berdasarkan permasalahan tersebut, penelitian ini menerapkan konsep Data Mining dengan algoritma Trend Moment untuk mengestimasi harga emas pada rentang waktu tertentu. Data yang digunakan merupakan data historis harga emas per gram pada PT Victoeria Vici periode Agustus–Oktober 2021 sebanyak 92 data. Tahapan penelitian meliputi pengumpulan data, penentuan variabel X dan Y, eliminasi untuk memperoleh nilai konstanta a dan slope b, serta penerapan persamaan Y = a + bX untuk memperoleh nilai estimasi. Hasil perhitungan menunjukkan nilai a = 720.871,725 dan b = 3,108 sehingga model estimasi mampu menghasilkan proyeksi harga emas yang mendekati pola data historis. Model ini kemudian diimplementasikan ke dalam aplikasi berbasis desktop menggunakan Microsoft Visual Basic 2010 dan basis data Microsoft Access, dilengkapi Crystal Report untuk pencetakan laporan hasil estimasi. Hasil penelitian menunjukkan bahwa algoritma Trend Moment dapat membantu PT Victoeria Vici dalam memperoleh estimasi harga emas secara lebih cepat, konsisten, dan terdokumentasi. Gold is one of the most sought-after commodities for investment purposes, as it is regarded as a safer instrument compared to stocks and has a selling value that constantly fluctuates with market conditions. PT Victoeria Vici, a custom gold jewelry business, faces difficulty in determining the estimated selling price offered to customers because the production process for custom orders takes up to 14 days, while gold prices move in an unstructured and fluctuating manner every day, making manual price estimation inaccurate and ineffective. Based on this problem, this study applies the concept of Data Mining using the Trend Moment algorithm to estimate gold prices over a certain period of time. The data used is historical daily gold price data per gram from PT Victoeria Vici for the period of August–October 2021, consisting of 92 records. The research stages include data collection, determination of the X and Y variables, elimination to obtain the constant value a and the slope b, and the application of the equation Y = a + bX to obtain the estimated value. The calculation results show a value of a = 720,871.725 and b = 3.108, so that the estimation model is able to produce gold price projections that closely follow the pattern of historical data. This model was then implemented into a desktop-based application using Microsoft Visual Basic 2010 and a Microsoft Access database, equipped with Crystal Report for printing estimation result reports. The results show that the Trend Moment algorithm can help PT Victoeria Vici obtain gold price estimations more quickly, consistently, and in a well-documented manner.
TECEPEBI SIMULASI DAN CHATBOT DALAM PENGAJARAN BAHASA INGGRIS STUDI KASUS: UPT SD NEGERI 060941 Evi Yanti Manullang; Fachrun Nissa; Mutiara S. Simanjuntak; Iskandar Iskandar; Suwardy Riduan
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
Co-Authors Aji Priyambodo Allwine Arnold Pakpahan Baehaqi Chairil Umri Chindi Dwi Lestari Nainggolan Dedi Irawan Elshad Yusifov Erika Fahmi Ginting Evi Yanti Manullang Fachrun Nissa Ginting, Syahril Hidayat, Dody Hongjie Dai Husna Gemasih IRNA TRIANNUR LUBIS Iskandar Iskandar Iskandar Iskandar Joel Panjaitan Juanto Simangunsong Juanto Simangunsong Junifa, Dira Manalu, Pius Deski Manullang, Evi Yanti Nissa, Fachrun Nurafni Damanik Nurmala Dewi Simanjuntak Pieter Leuvanggi Hutagalung Pius Deski Manalu 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 Suci Andriyani Suci Andryani Suwardy Riduan Syofyan Anwar Syahputra Syofyan Anwar Syahputra Teddy Surya Gunawan Wanayumini