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All Journal Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) Management Studies and Entrepreneurship Journal (MSEJ) Jurnal Ilmiah Smart Jurnal Teknik Informatika (JUTIF) Bulletin of Computer Science Research Jurnal Ilmiah Manajemen dan Bisnis (JIMBI) Journal of Artificial Intelligence and Engineering Applications (JAIEA) JURNAL ILMU MANAJEMEN SABURAI (JIMS) LEBAH Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Ilmiah Smart
Feriani Astuti Tarigan
STMIK TIME
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PERANCANGAN APLIKASI PENILAIAN KINERJA KEPALA LINGKUNGAN KECAMATAN MEDAN HELVETIA DENGAN METODE GRS & 360 DEGREES BERBASIS ANDROID Tarigan, Feriani Astuti
Majalah Ilmiah METHODA Vol. 13 No. 3 (2023): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol13No3.pp292-298

Abstract

Performance appraisal is an important part of seeing the results of each employee's work performance, including the Head of the Neighborhood who is the spearhead of Government services to the community. However, the Head of Neighborhood has not found a standardized performance appraisal so that the author is interested in making a performance appraisal system for the Head of Neighborhood, especially in Medan Helvetia District and at the same time building an easy-to-use assessment application. This Neighborhood Head Performance Assessment Application uses a combination of the Graphic Rating Scale (GRS) algorithm to make it easier to see the assessment results and the 360 Degrees algorithm so that the assessment results are more objective. The assessment results obtained can be a recommendation for reward and punishment. The application also requires development to iOS-based smartphones so that more users can utilize it.
Digitalisasi Sistem Informasi Peserta Didik dan Donasi Pada Panti Asuhan Salam Damai Dihati Untuk Mewujudkan Generasi Emas Perangin Angin, Johanes Terang Kita; Tarigan, Feriani Astuti; Hidayat, Ferry
Lebah Vol. 19 No. 1 (2025): September: Pengabdian
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/lebah.v19i1.415

Abstract

Pengabdian kepada masyarakat ini bertujuan untuk mendukung transformasi digital pada Panti Asuhan Salam Damai Dihati melalui pengembangan sistem informasi peserta didik dan donasi. Selama ini, pencatatan data peserta didik dan pengelolaan donasi masih dilakukan secara manual sehingga sering menimbulkan keterlambatan informasi, duplikasi data, serta kesulitan dalam pelaporan. Dengan adanya digitalisasi sistem informasi, proses administrasi menjadi lebih efektif, transparan, dan akuntabel. Metode pelaksanaan kegiatan meliputi analisis kebutuhan, perancangan sistem berbasis web, pelatihan pengguna, serta evaluasi penerapan sistem. Hasil implementasi menunjukkan bahwa sistem informasi yang dibangun mampu mempermudah pengelolaan data peserta didik, meningkatkan transparansi donasi, serta memberikan akses informasi yang lebih cepat bagi pengurus dan donatur. Sistem informasi yang dibangun memungkinkan pengurus melakukan pengelolaan data peserta didik secara terintegrasi, menyimpan riwayat perkembangan anak asuh, serta mencatat donasi dengan lebih transparan dan akuntabel. Selain itu, sistem juga dirancang agar mudah digunakan oleh pengurus yang memiliki keterbatasan dalam penguasaan teknologi. Program ini diharapkan dapat menjadi model penguatan kapasitas manajemen panti asuhan berbasis teknologi, sekaligus mendukung tercapainya visi membentuk generasi emas yang unggul dan berdaya saing
Implementasi Chatbot Otomatis Akademik Berbasis Web Menggunakan LLM dan Rule-Based System Studi Kasus: STMIK Time Alvin, Alvin; Robet, Robet; Tarigan, Feriani Astuti
JURNAL INFORMATIKA DAN KOMPUTER Vol 9, No 3 (2025): Oktober 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v9i3.2209

Abstract

Perkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) telah mendorong peningkatan efisiensi layanan informasi melalui penerapan chatbot yang mampu berinteraksi secara alami dengan pengguna. Chatbot merupakan implementasi teknologi berbasis pemrosesan bahasa alami (Natural Language Processing/NLP) yang dirancang untuk memahami dan merespons percakapan manusia. Penelitian ini bertujuan mengembangkan chatbot otomatis layanan akademik STMIK Time berbasis web dengan mengintegrasikan dua pendekatan utama, yaitu Rule-Based System dan Large Language Model (LLM). Metode penelitian meliputi tahap perancangan sistem menggunakan Flowise AI sebagai platform automation workflow, serta pengujian performa sistem melalui dua tahap, yaitu pengujian black box untuk menilai fungsionalitas dan pengujian user experience untuk mengukur persepsi pengguna terhadap kecepatan, akurasi, dan kepuasan. Hasil pengujian menunjukkan bahwa chatbot berfungsi dengan baik dengan capaian kecepatan respons sebesar 51,5%, tingkat akurasi 54,5%, dan tingkat kepuasan pengguna 60,6%. Hasil ini menegaskan bahwa sistem mampu memberikan layanan informasi akademik secara efektif, meskipun aspek kecepatan dan responsivitas masih perlu ditingkatkan. Kesimpulannya, Rule-Based System lebih sesuai untuk percakapan terstruktur, sedangkan Large Language Model (LLM) lebih efektif untuk konteks dinamis. Penelitian ini diharapkan menjadi dasar pengembangan layanan akademik berbasis AI yang lebih adaptif dan responsif di perguruan tinggi.
PENGARUH DIGITAL MARKETING DAN BRAND AWARENESS TERHADAP KEPUTUSAN PEMBELIAN PADA PRODUK AQUA DI DESA CINTA RAKYAT Tarigan, Feriani Astuti; Robin, Robin; Angeline, Shella
Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 8 No 2 (2024): Edisi Mei - Agustus 2024
Publisher : LPPM STIE Muhammadiah Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31955/mea.v8i2.4031

Abstract

Tujuan penelitian ini adalah untuk mengetahui pengaruh digital marketing dan brand awareness terhadap keputusan pembelian pada produk AQUA di Desa Cinta Rakyat. Metode dalam penelitian ini adalah deskriptif kuantitatif. Karena populasinya tidak diketahui, maka teknik pengambilan sampel yang digunakan adalah rumus Lemeshow. Dapat dijelaskan bahwa perhitungan sampel dengan pendekatan rumus Lemeshow dapat digunakan untuk menghitung jumlah sampel dengan besar populasi yang tidak diketahui. Dengan demikian, jumlah sampel yang digunakan sebanyak 96 responden dan teknik pengambilan sampelnya menggunakan Accidental Sampling dimana responden yang ditemui secara tidak sengaja akan terlebih dahulu dijadikan sampel penelitian. Hasil penelitian menunjukkan bahwa secara parsial maupun simultan, digital marketing dan brand awareness berpengaruh signifikan terhadap keputusan pembelian pada produk AQUA di Desa Cinta Rakyat.
Multi-Class Brain Tumor Segmentation and Classification in MRI Using a U-Net and Machine Learning Model Hendrik, Jackri; Pribadi, Octara; Hendri, Hendri; Hoki, Leony; Tarigan, Feriani Astuti; Wijaya, Edi; Ali, Rabei Raad
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5369

Abstract

Brain tumor diagnosis remains a critical challenge in medical imaging, as accurate classification and precise localization are essential for effective treatment planning. Traditional diagnostic approaches often rely on manual interpretation of MRI scans, which can be time-consuming, subjective, and prone to variability across radiologists. To address this limitation, this study proposes a two-stage framework that integrates machine learning (ML) based classifiers for tumor type recognition and a U-Net architecture for tumor segmentation. The classifier was trained to distinguish four tumor categories: glioma, meningioma, pituitary, and no tumor, while the U-Net model was employed to delineate tumor regions at the pixel level, enabling volumetric assessment. The novelty of this research lies in its dual focus that combines classification and segmentation within a single framework, which enhances clinical applicability by offering both diagnostic and spatial insights. Experimental results demonstrated that among the evaluated classifiers, XGBoost achieved the highest accuracy of 86 percent, surpassing other models such as Random Forest, SVC, and Logistic Regression, while the U-Net model delivered consistent segmentation performance across tumor types. These findings highlight the potential of hybrid ML and deep learning solutions to improve reliability, efficiency, and objectivity in brain tumor analysis. In real-world practice, the proposed framework can serve as a valuable decision-support tool, assisting radiologists in early detection, reducing diagnostic workload, and supporting personalized treatment strategies.
IoT Sensor Data Analysis for Early Fire Detection Using Dynamic Threshold Br Tarigan, Widia; Robet, Robet; Tarigan, Feriani Astuti
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15478

Abstract

Early fire detection using Internet of Things (IoT) technology plays a vital role in minimizing potential material losses and casualties. Conventional systems generally still rely on static thresholds that are less adaptive to environmental dynamics, leading to high false alarm rates and delayed detection. This study proposes a dynamic threshold approach based on a hybrid method of Fuzzy Logic–Random Forest–Adaptive Z-Score and compares it with the static threshold method. Testing was conducted using publicly available secondary datasets, and the algorithms were implemented and tested in Jupyter Notebook. Evaluation was performed using accuracy, false alarm rate (FAR), detection time, F1-score, precision, and recall metrics. The test results show that the dynamic threshold method provides better performance with an increase in accuracy from 59.5% to 74.8%, a decrease in FAR from 31.1% to 14.3%, and a reduction in detection time from 21 seconds to 0 seconds. In addition, the F1-score increased from 0.459 to 0.638, precision from 0.473 to 0.716, and recall from 0.446 to 0.575. These results show that the dynamic threshold approach is more adaptive and reliable in IoT-based fire detection systems than conventional static threshold methods.
Pengaruh Lifestyle Flash Sale Promotion dan Diskon Terhadap Minat Beli Pengguna Shopee (Study Kasus pada Gen Z Pengguna Shopee) Sinaga, Rojali A.; Tarigan, Feriani Astuti; Siregar, August Halomoan
Jurnal Ilmiah Manajemen dan Bisnis (JIMBI) Vol 6, No 2 (2025): Jurnal Ilmiah Manajemen dan Bisnis (JIMBI) - Desember
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jimbi.v6i2.6474

Abstract

This research is motivated by the increasing number of Shopee users. This study aims to determine the influence of Lifestyle, Flash Sale Promotion, and Discount on Purchase Intention of Shopee application users in Gen Z situations. This study uses a survey method with a sampling technique using the Lemeshow approach with a maximum estimate of 50% and an error rate of 10%. The sample size in this study consists of 100 samples. Data were analyzed using linear regression analysis. To assess the validity and reliability of the test, 30 consumers were selected from the entire population considered. This study uses a quantitative method. The research method used in this study is quantitative descriptive research, which aims to thoroughly analyze the subject matter. The results show that lifestyle, Lifestyle, Flash Sale Promotion, and Discount have a positive and significant effect on Purchase Intention of Shopee users in Gen Z. The coefficient of determination of 0.236 or 23.6% indicates that the combined influence of lifestyle, Flash Sale Promotion, and Discount in explaining consumer usage decisions is 23.6%. The remaining 76.4% of the variance is likely due to factors outside the studied variables, such as service quality, shipping costs, and so on. The results of this study can be used as a reference for Shopee app developers to improve service quality and increase user trust.
An Analysis of User Satisfaction Toward the Maxim Application in Medan City using the E-Servqual Model Agil, Rezkyta; Octaviandy, Pieter; Tarigan, Feriani Astuti
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1688

Abstract

The development of information technology has facilitated various activities, including online transportation services. Maxim, as one of the digital transportation service providers, has received numerous user complaints, particularly regarding its navigation features, interface design, and electronic payment system. This study aims to analyze user satisfaction with the Maxim application in Medan City using the E-Servqual method, which includes five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. The research used a quantitative approach by distributing online questionnaires to 104 respondents. The results showed that all dimensions had negative GAP values, with tangibles being the most dominant factor affecting user satisfaction. As a solution, a real-time dashboard prototype was designed to help developers monitor feature evaluations directly. This research is expected to serve as a reference for improving the quality of Maxim’s services in the future.
Co-Authors Agil, Rezkyta Ali, Rabei Raad Alvin Alvin, Alvin Angeline, Shella August Halomoan Siregar Bangun, Ratna Sari Rizki Br Tarigan, Widia Christina Didik Aryanto Didik Aryanto Edi Wijaya ENDRI ENDRI Ferry Hidayat Fransisca Fransisca Hendri Hendri Hoki, Leony Irwadi, Irwadi Jackri Hendrik Jackri Hendrik Johanes Terang Kita Perangin Angin Michael Michael Novranda Surbakti Octara Pribadi Pieter Octaviandy, Pieter Robet Robet Robin Robin Siahaan, Agus Maringan Silvia Silvia Silvia Sofyan Sinaga, Rojali A.