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Muhammad Abdul Muin
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INDONESIA
Transformasi
Published by STMIK Bina Patria
ISSN : 19785569     EISSN : 28278550     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics
Jurnal transformasi sebagai wadah untuk mengembangkan Dan mensosialosasikan IPTEk berbasis penelitian dan kajian ilmiah (artikel review) dalam lingkup Informatika, elektronika, manajemen, pendidikan & pembelajaran.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 36 Documents
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Search results for , issue "Vol 21, No 1 (2025): TRANSFORMASI" : 36 Documents clear
KLASIFIKASI INTENSITAS HUJAN DI SAMARINDA MENGGUNAKAN LOGIKA FUZZY MAMDANI Putri, Septi Aulia; Asmita, Rizka; Nggotu, Antonieta Aryuka Paskalia; Hutapea, Vedra Dian Sierrafina; Septiarini, Anindita; Wati, Masna
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.422

Abstract

This study aims to classify rainfall intensity in the Samarinda area into three categories: light rain, moderate rain, and heavy rain based on three meteorological variables: temperature (in °C), air pressure (in hPa), and rainfall (in mm) to provide a more adaptive and accurate classification of rainfall intensity based on local weather conditions in Samarinda, which is prone to disasters due to high rainfall intensity. The data used in this study was obtained from the Meteorology, Climatology, and Geophysics Agency (BMKG) Samarinda for the period of October to December 2024. This study implements the Mamdani Fuzzy Logic method, which consists of the stages of fuzzification, rule base application, inference, and defuzzification. Fuzzy logic was chosen due to its ability to handle data that is ambiguous and uncertain, which is common in weather phenomena. Testing results on 50 random weather condition data samples indicate that the developed Mamdani fuzzy model achieved an accuracy of 100% on the test data, demonstrating consistency between the resulting rainfall intensity classification and actual data. Based on these findings, this model can be utilized as a support tool for decision-making, both by individuals and local government agencies, in efforts to monitor and mitigate extreme weather conditions in Samarinda, East Kalimantan.Keywords : Fuzzy Logic, Mamdani Method, Rainfall Intensity, Classification
SISTEM KEAMANAN BRANKAS DENGAN RFID DOOR LOCK BERBASIS INTERNET OF THINGS (IOT) MENGGUNAKAN CISCO PACKET TRACER -, Amirah -; Talakua, Prisilia; -, Opitasari -; -, Fitria -
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.415

Abstract

The development of Internet of Things (IoT) technology has brought significant transformations in various fields, including security systems in securing valuable assets, such as safes, which require a high level of security. The purpose of this study is to design and implement a safe security system based on RFID and IoT, simulate the system using Cisco Packet Tracer to ensure its functionality and evaluate the effectiveness of the system in securing access to the safe. The system development model used is the ADDIE method which consists of five stages of development, namely; (1) Analysis, (2) Design, (3) Development, (4) Implementation and (5) Evaluation. Problem analysis uses analysis and Feasibility Analysis uses TELOS analysis. The results of the System reliability analysis on this system are Verification Accuracy is 100% accurate in distinguishing valid and invalid tags based on data, while Response Speed is the response time between RFID reading and the door opening an average of 1 second. The system continues to run well as long as the server is active and the device is connected to the network. This research is expected to provide an alternative solution for an affordable and virtually simulated safe security system, as a reference or initial prototype for the development of a larger scale IoT security system and to demonstrate the potential use of Cisco Packet Tracer in RFID and IoT-based security system simulations.
LABORATORIUM SEBAGAI LAYANAN TERPADU DI UNIVERSITAS – INTEGRASI EFISIENSI PELAYANAN DAN MANAJEMEN SUMBER DAYA Yazid, Ahmad
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.433

Abstract

Meningkatnya kebutuhan pelayanan laboratorium yang lebih mudah diakses dan terjadwal di universitas mendorong dibutuhkannya solusi inovasi. Tulisan ini mengajukan konsep laboratorium sebagai layanan terpadu yang menyatukan pelayanan dan pengelolaan laboratorium yang ada melalui satu sistem digital. Dengan memanfaatkan sumber daya teknologi untuk meningkatkan akses, penjadwalan, dan pengurusan administrasi. Pendekatan ini dapat meningkatkan efisiensi, efektivitas, dan kualitas layanan dari laboratorium di univesitas. Hasil dari penelitian ini menunjukkan betapa besarnya kemungkinan dan peluang yang terbuka kepada laboratorium universitas untuk meningkatkan pengelolaan, pelayanan. dan sistem kinerja yang ada.
ANALISIS POTENSI ANAK USIA DINI DALAM IDENTIFIKASI BIDANG MINAT DENGAN METODE SAW Suryadijaya, Dharyana; Fatimah, Firi; Sebayang, Ayu Nuriana; Chandra, David
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.420

Abstract

Penelitian ini bertujuan untuk menganalisis potensi anak usia dini dalam mengidentifikasi bidang minat menggunakan metode Simple Additive Weighting (SAW). Anak usia 4-5 tahun dipilih sebagai objek penelitian karena berada dalam tahap eksplorasi, di mana mereka mulai menunjukkan minat pada berbagai aktivitas. Pendekatan kuantitatif digunakan untuk mengevaluasi multikriteria yang mencakup seni, olahraga, kreativitas, kemampuan sosial, kemampuan kognitif, dan teknologi. Data diperoleh melalui observasi dan kuesioner yang melibatkan orang tua dan guru untuk memahami perilaku anak secara objektif. Metode SAW diterapkan dalam empat langkah utama: penentuan bobot kriteria, normalisasi data, perhitungan skor akhir, dan analisis preferensi. Hasil penelitian menunjukkan bahwa setiap anak memiliki kecenderungan unik terhadap bidang tertentu, seperti seni dan kreativitas, olahraga dan sosial, atau teknologi. Penemuan ini memberikan wawasan bagi orang tua dan pendidik untuk mengarahkan anak secara tepat sesuai dengan bakat dan minat mereka. Kesimpulannya, metode SAW adalah alat yang efektif untuk mendukung pengembangan potensi anak usia dini dengan pendekatan berbasis data. Penelitian ini juga merekomendasikan penggunaan metode serupa untuk mengevaluasi minat anak di kelompok usia lainnya.
SEGMENTASI PELANGGAN MENGGUNAKAN METODE DBSCAN UNTUK MENDETEKSI POLA BELANJA Handayani, Riska Dwi; Astuti, Dwi; Priyoatmoko, Wahyu; Kapti, Kapti
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.439

Abstract

Customer segmentation is one approach used to identify customer characteristics. Accurate segmentation allows companies to personalize offers, increase customer retention and optimize marketing costs. The purpose of this study is to group customer characteristics of a retail company using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method. The DBSCAN method does not require initial determination of the number of clusters, is able to recognize clusters with irregular shapes and can identify outliers or customers with extreme patterns. The dataset used is an external dataset obtained from Kaggle. The dataset contains customer personalization analysis with a total of 2,240 rows and 29 columns. The results of the study show that the DBSCAN method can produce an eps value of 1.2 and produce the highest Silhouette Score of 0.080 with 4 clusters formed. Visualization of segmentation results with PCA dimension reduction techniques into two dimensions to facilitate interpretation. The PCA visualization produces 5 clusters, each of which represents its respective customer group. Thus, this approach offers an adaptive segmentation alternative that is more sensitive to complex behavioral patterns.Keywords : Customer segmentation, DBSCAN, shopping patterns, silhouette scorem, PCA
The Effectiveness of Artificial Intelligence and Deep Learning Tools in Enhancing Academic Journal Writing: A Mixed Methods Study of Arabic Language Education Students in Indonesia Zulaikha, Zulaikha; Setyawan, Cahya Edi; Mabruri, Mabruri; Rauhillah, Siti
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.429

Abstract

This study investigates the effectiveness of Artificial Intelligence (AI) and Deep Learning (DL) tools in enhancing academic journal writing skills among students in the Arabic Language Education program at UIN Maulana Malik Ibrahim Malang. Utilizing a mixed-methods approach within a quasi-experimental design, the research involved 90 final-year students divided into experimental and control groups. The intervention group employed AI-based tools such as ChatGPT, Grammarly, and Quilbolt throughout the writing process, while the control group relied on conventional methods. Data were collected through pre-test and post-test assessments, reflective journals, and structured questionnaires. Quantitative results showed a statistically significant improvement in writing performance among students who used AI tools, with large effect sizes (Cohen’s d 1.0). Qualitative findings revealed that students engaged critically with AI outputs, valued teacher feedback, and developed ethical awareness regarding authorship and originality. The integration of AI tools also increased student confidence, enhanced writing fluency, and promoted autonomous learning. However, limitations in semantic precision and rhetorical fit especially in theology-specific content necessitated human revision. These findings affirm the role of AI as a cognitive scaffold in academic writing and highlight the need for culturally responsive, ethically guided AI integration in language teacher education.Keywords: Artificial Intelligence, Academic Writing, Deep Learning, Arabic Education, Cognitive Scaffold

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