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JUTIM (Jurnal Teknik Informatika Musirawas)
Published by Universitas Bina Insan Lubuklinggau
ISSN : 25411888     EISSN : 26145782     DOI : https://doi.org/10.32767/jutim
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Engineering Other
Jurnal Teknik Informatika Musirawas merupakan Jurnal ilmiah yang meliputi kompetensi Human Computer Interaction, IT Governance, Networking Technology, New Media Technology, Information Search Engine, Multimedia, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Computer Network Security, Natural Language Processing, Software Engineering, Programming Methodology and Paradigm, Data Engineering, Information Management, Knowledge Based Management System, Game Technology Jurnal Teknik Informatika Musirawas terbit sebanyak dua kali dalam satu tahun, pada bulan Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 223 Documents
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PENGEMBANGAN SISTEM PEMANTAUAN KUALITAS UDARA BERBASIS INTERNET OF THINGS DI LINGKUNGAN GELORA KADRIE OENING Al Akbar, Mohamad Febriansyah; Hallim, Abd.; Arbansyah, Arbansyah
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 10 No 1 (2025): JUTIM (Jurnal Teknik Informatika Musirawas) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v10i1.2679

Abstract

Polusi udara merupakan masalah lingkungan global serius dengan dampak kesehatan signifikan, diperburuk oleh keterbatasan sistem pemantauan konvensional yang ada. Kondisi udara di Gelora Kadrie Oening, Samarinda, yang pernah mencapai kategori "sangat tidak sehat", menggarisbawahi urgensi pemantauan lokal. Penelitian ini bertujuan merancang dan mengimplementasikan sistem pemantauan kualitas udara berbasis Internet of Things (IoT) untuk menyediakan informasi real-time guna mendukung kesehatan pengguna fasilitas. Sistem dikembangkan menggunakan model Waterfall, melibatkan mikrokontroler ESP32, sensor PM2.5, DHT22, MQ-135, dan LCD. Data dikirim ke server via HTTP POST, disimpan di MySQL, kemudian divisualisasikan melalui dashboard web dan dikirim sebagai notifikasi Telegram. Hasil menunjukkan sistem berhasil diimplementasikan dan diuji fungsionalitasnya; akuisisi, transmisi data, tampilan web real-time (termasuk historis dan rekomendasi adaptif), serta notifikasi Telegram terbukti efektif. Pengujian di lapangan memvalidasi akurasi sensor PM2.5, serta menunjukkan rata-rata PM2.5 7.9 µg/m³ (BAIK) di dalam stadion dan 18.89 µg/m³ (SEDANG) di jalur keluar masuk GOR, membuktikan kemampuan sistem dalam menyediakan informasi kualitas udara yang akurat dan responsif di lokasi berbeda.
KOMPARASI ALGORITMA PENENTUAN ASOSSIATION RULE PENJUALAN PRODUK aktavera, Beni; Alamsyah, M.Nur; Wijaya, Harma Oktafia Lingga; Armanto, Armanto
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 10 No 1 (2025): JUTIM (Jurnal Teknik Informatika Musirawas) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v10i1.2638

Abstract

In the digital era, transaction data analysis has become an important strategy for increasing business effectiveness, including bakeries. One technique that is often used is association analysis, with the Apriori and FP-Growth algorithms as the main approaches. The main problem is to determine a more efficient and relevant algorithm to support business decision making in bakeries, especially in purchasing pattern analysis. This research aims to compare the performance of the Apriori and FP-Growth algorithms in determining association rules in bakery transaction data. The research methodology includes transaction data collection, data pre-processing, algorithm implementation, performance testing, and results analysis. Parameters analyzed include processing time, number of generated rules, and efficiency at different dataset scales. Testing was carried out with Python software, utilizing libraries such as mlxtend and pandas. The research results show that the FP-Growth algorithm is superior in time efficiency and scalability, especially on large datasets, thanks to its approach that does not require the formation of candidate itemsets. Meanwhile, the Apriori algorithm is easier to implement and remains relevant for small datasets with the right parameters. This research offers novelty by focusing on the application of both algorithms in a bakery context, providing specific insights into how to optimize stock management and design data-driven promotions. These results provide an important contribution for bakeries and similar business sectors to utilize data analysis as a strategic tool in increasing customer satisfaction and competitiveness.
KLASIFIKASI JENIS PENYAKIT KATARAK MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR Rahmadayanti, Fitria; Angraini, Inda; ., Sulaiman
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 10 No 1 (2025): JUTIM (Jurnal Teknik Informatika Musirawas) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v10i1.2688

Abstract

The purpose of this study is to assist the Besemah City Hospital in Pagar Alam in classifying cataract data. The large number of cataract sufferers causes the eye polyclinic to collect data randomly and so that it is incomplete in submitting reports, with the classification of cataract disease or data grouping to make it easier for the polyclinic to find out which cataract disease groups are the highest based on their causes and to make it easier for the eye polyclinic to collect reports. The study applies the K-Nearest Neighbor (KNN) method as an algorithm for cataract data classification. The development method used is CRIPS-DM consisting of six phases, namely the business understanding process, data understanding, data preparation, modeling, evaluation and Deployment. There are 842 data from the results of the classification of cataract disease types using the KNN algorithm which were tested with rapid miner types of unsficified cataract disease 390, senile nuclear cataract 43, senile incifient cataract 196, unscified cataract 39, other cataracts 1, complicated cataract 67, senile cataract 11, senile cataract morgagnian type 0, invatile juvenile 4, traumatic cataract 0, and the results of the rapid miner accuracy of 89.19% performance vector.

Page 23 of 23 | Total Record : 223

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