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Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Published by Institut Teknologi Pagar Alam
ISSN : 23391871     EISSN : 27157369     DOI : https://doi.org/10.36050/betrik.v10i03
Core Subject : Science,
Computer Science & IT
Besemah Teknologi Informasi dan Komputer (BETRIK) is a national journal published by Pusat Penelitian dan Pengabdian kepada Masyarakat (P3M), Institut Teknologi Pagar Alam (ITPA). This scientific work was published in 3 editions, with topics related to Computers, Technology, and Science. Topics related to this field can be information systems, informatics, computer science, IT business, IT Governance, enterprise architecture planning, software engineering, modeling and simulation, Data Mining, Artificial Neural Network, Digital Image Processing, Algorithm and Programming, Internet of Things (IoT), artificial intelligence, information security, social networking, cloud computing, science, engineering and related topics. The Scientific Journal BETRIK is a peer journal -National review dedicated to the exchange of high-quality research results in all aspects of education and teaching. This journal publishes the latest works in basic theory, experiments and simulations, as well as applications, with systematically proposed methods, adequate reviews of previous works, extended discussions and conclusions. As our commitment to the advancement of education and teaching, the BETRIK Journal follows an open access policy that allows published articles to be available online for free without subscribing.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 239 Documents
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Perancangan Aplikasi Pintar Monitoring Dan Deteksi Anomali BBM Menggunakan Machine Learning Di PT. BDR Solehudin Solehudin; Ahmad Munawir; Wahyu Amaldi
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/cfdvkr55

Abstract

In the digital era, the need for technology-based monitoring systems is increasing, especially in the transportation and logistics industry. PT BDR faces challenges in reporting and monitoring fuel consumption for operational vehicles due to the manual recording process, making it difficult to detect anomalous data and making monitoring less efficient. This study aims to develop a web-based application capable of automatically monitoring and detecting fuel consumption anomalies by utilizing machine learning and deep learning technologies. The system development method uses the CRISP-DM approach, which includes the stages of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The Isolation Forest algorithm is used to detect anomalies based on fuel volume data, mileage, and vehicle consumption ratio, while the MobileNetV2-based Content-Based Image Retrieval (CBIR) method is applied to validate the suitability of gas station photos. The trained model is then integrated into the API using the Flask framework, with testing conducted through blackbox and whitebox testing. The test results show that the system is able to detect anomalies with a good level of accuracy and can be used practically by users. The implementation of this application is expected to improve the company's operational efficiency, reduce potential losses due to fuel misappropriation, and support the digitalization of the fuel monitoring process to be more accurate, effective, and integrated.
Optimasi Hyperparameter WOA-SVM pada Citra Daun Kopi Terpupuk NPK Agustian Prakarsya; Nina Dwi Putriani; Yusi Nurmala Sari; Firza Septian
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/zrj1e094

Abstract

This study aims to analyze the impact of Whale Optimization Algorithm (WOA) optimization on the performance of Support Vector Machine (SVM) in classifying images of coffee leaves treated with NPK fertilizer. WOA is employed to find the optimal combination of SVM parameters to improve classification accuracy. The dataset consists of coffee leaf images that have undergone feature extraction based on color and texture. Performance evaluation was conducted using a confusion matrix, classification report, and heatmap visualization. The results show that the SVM model optimized with WOA performs better than the non-optimized SVM. Specifically, the non-optimized SVM achieved a precision of 0.82, recall of 0.81, and F1-score of 0.81. After optimization with WOA, the model’s precision increased to 0.90, recall to 0.88, and F1-score to 0.87. This study demonstrates that metaheuristic approaches like WOA can significantly enhance the performance of classification algorithms in the context of digital image processing. The findings have practical implications for early detection of plant quality through image-based analysis in technology-driven agriculture
Analisis Vulnerability Assessment Sistem Informasi Pendidikan, Pelatihan PT Azure Samudera Karsa Menggunakan ZAP Soni Ayi Purnama
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/2n4njj02

Abstract

 This study aims to analyze the security of the educational and training information system at PT Azure Samudera Karsa using the vulnerability assessment method. Enhancing the security of information systems is a key priority in order to improve the credibility and quality of the educational and training services provided by PT Azure Samudera Karsa. In today's digital era, information systems that are vulnerable to cyberattacks can lead to various negative consequences, including data breaches, information manipulation, and operational disruptions. Therefore, security evaluation becomes a crucial aspect that must not be overlooked. The tool used to assess the security of the educational and training information system at PT Azure Samudera Karsa is Zed Attack Proxy (ZAP), an open-source application commonly used to detect security vulnerabilities in web applications. The results of the vulnerability assessment revealed three levels of alerts: 3 alerts at the medium level, 6 alerts at the low level, and 3 informational alerts, totaling 13 alerts. These findings serve as an important basis for management to take immediate corrective actions to minimize risks and enhance the protection of the system in use.
Prediksi Jumlah Titik Ruang Terbuka Hijau (RTH) Menggunakan Metode Regresi Linier dan Model Random Forest M. Azzuhri Dinata; Helda Yenni; Wirta Agustin; Aguston
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/d81adt50

Abstract

The development and preservation of Green Open Space (GOS) is an important part of maintaining environmental balance, especially in the Sumatra Ecoregion. This study aims to predict the number of GOS points using a linear regression approach and the Random Forest algorithm. The data used include variables such as area and forest area from several provinces in Sumatra. Model performance evaluation was carried out using MAE, RMSE, and coefficient of determination (R²) metrics. The analysis results show that the Random Forest model has superior performance compared to linear regression, with an MAE value of 5.52, RMSE of 5.88, and R² of 0.74. Meanwhile, linear regression was only able to achieve an R² of 0.45. These findings indicate that Random Forest is more effective in capturing non-linear data patterns and more accurate in predicting the number of GOS points. This study contributes to the use of data science technology to support sustainable environmental planning, as well as becoming a basis for data-based spatial planning policy making
DIFFERENTIATION STRATEGY TO INCREASE THE LOAD FACTOROF LRT SUMSEL THROUGH THE IMPLEMENTATION OF A TRANSITORIENTED DEVELOPMENT (TOD) SYSTEM Muhammad Fariz; Zahera Mega Utama; Franky
BETRIK Vol. 15 No. 02 (2024): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/x6gpa966

Abstract

This research examines the phenomenon of increasing the number of South SumatraLRT users through a differentiation strategy based on Transit Oriented Development (TOD).Using a qualitative descriptive approach, this research explores the TOD concept implementedby South Sumatra LRT managers in Palembang City. Data was collected through observation,interviews and documentation from January to October 2023. The results of the analysis showthat the implementation of TOD has increased the load factor of the South Sumatra LRT, althoughit still faces several challenges such as overlapping stakeholder interests and a lack of effectivepromotion. This research method involves preliminary observations to understand the context ofthe South Sumatra LRT, followed by field research to obtain more in-depth data. Informants wereselected purposively based on their expertise and relevance to the research topic. Data wereanalyzed through triangulation of sources and theories to ensure the validity of the results. Theresults of the analysis show that the TOD-based differentiation strategy has a positive impact onthe South Sumatra LRT load factor, especially through infrastructure development and effectivepromotion. This research concludes that a TOD-based differentiation strategy can be an effectivemodel for increasing the use of mass transportation services such as the South Sumatra LRT. Byinvolving collaboration between the government and the private sector, as well as improvingfacilities and promotions, the South Sumatra LRT can become a transportation alternative that ismore popular with the public. However, further steps are needed to overcome the challenges stillbeing faced, such as overlapping stakeholder interests and the use of private transportation.
SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN SISWAMISKIN MENGGUNAKAN METODE MOORA SDN1 KEMBANGSARI MUIS; Adi Susanto; Firman Santoso
BETRIK Vol. 15 No. 02 (2024): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/1s44aq36

Abstract

Penelitian ini bertujuan mengoptimalkan alokasi bantuan siswa miskin melalui sistem pendukung Keputusan (SPK) dengan menerapkan metode MOORA untuk menentukan penerima bantuan siswa miskin di SDN 1 Kembangsari masalah yang terjadi di SDN 1 kembangsari Proses penetapan masih dilakukan secara konvensional sehingga dana BSM tidak tepat sasaran dan terdapat kesenjangan sosial diantara guru dan wali murid maka dari itu peneliti menggunakan 4 kriteria untuk diajukan sebagai salah satu acuan dalam menetapakan penerima bantuan siswa miskin di SDN 1 Kembangsari dengan menerapkan Metode Multi objective optimization by ratio analisys (MOORA) penelitian ini berfokus untuk berkontribusi pada efektifnya  enyaluran dana BSM sehingga tidak ada lagi kesenjangan sosial diantara wali murid dan guru
DIFFERENTIATION STRATEGY IN BANGSRING UNDERWATERBANYUWANGI ECOTOURISM Jodi Hapro Kelana; Zahera Mega Utama; Franky
BETRIK Vol. 15 No. 02 (2024): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/3hdrgv51

Abstract

This research aims to explore the strategies implemented by the management of Bangsring Underwater Banyuwangi Ecotourism through the differentiation strategy model, including content, context, and infrastructure. The approach used in this research is qualitative with a descriptive research type. This research shows that Bangsring Underwater management uses a differentiation model to increase tourist visits post-COVID-19. In the content dimension, Bangsring Underwater actively innovates on conservation-based destination products. Second, in the context dimension, the management implements integrated digital media marketing with the Government's digital platforms and regularly collaborates with various stakeholders. Third, in theinfrastructure dimension, the management provides comprehensive services during COVID-19, including reservations, tour package promotions, tours in collaboration with the district government, homestays, Personal Protective Equipment (PPE), Dive Centers, and additional facilities and equipment.
APLIKASI E KANTIN MAHASISWA BERBASIS MOBILE PADA POLITEKNIK TAKUMI MENGGUNAKAN METODE MOBILE D Anis Lelitasari; Reza Ilyasa; Rangga Gading Satria; Rifky Akbar Vetian; Rizaldi Putra; Arief Fathul Ulum
BETRIK Vol. 15 No. 02 (2024): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/trzp8v90

Abstract

Kantin Elektronik telah menjadi solusi inovatif untuk memperbaiki sistem pembelian makanan, minuman, dan peralatan lain di Politeknik Takumi. Penelitian ini menginvestigasi implementasi Aplikasi Kantin Elektronik sebagai platform yang memfasilitasi transaksi bagi civitas kampus dan juga sebagai wadah untuk mengembangkan wirausaha di lingkungan kampus. Metode pengembangan sistem yang digunakan yaitu metode Mobie -D, databse menggunakan NoSQL serta aplikasi dibngun menggunakan Flutter. Dari Teknologi tersebut aplikasi yang dihasilkan berupa aplikasi mobile, dimna pengguna dapat mengistal pada perangkat seluler untuk menggunakan aplikasi tersebut aplikasi ini dapat mempermudah civitas academica Politeknik Takumi dalam memesan makanan serta pencatatan adminstrasi lebih rapi danterdokumentasi. Dengan adanya aplikasi ini civitasacademica Politeknik Takumi sangat terbantu, mahasiswa tidak perlu mengantri membeli makanan, proses transaksi lebih mudah. Dari aplikasi ini dapat mendorong wirausaha di Politeknik Takumi, mahasiswa dapat berdagang melalui aplikasi ini serta mempromosikan daganganya dengan mudah kedapanya dapat dikembangkan menjadi koperasi kampus.
ALAT MONITORING DAYA LISTRIK BERBASIS IOT PADA PONPES SALAFIYAH SYAFI’IYAHSUKOREJO (P2S3) MENGGUNAKAN NODEMCU DAN BLYNK Muhammad Haikal Bisri; Firman Santoso; Farihin Lazim
BETRIK Vol. 15 No. 02 (2024): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/rz8kkq92

Abstract

Energi listrik sudah menjadi salah satu kebutuhan primer dalam kehidupan manusia. Penggunaan energi listrik pada pondok pesantren salafiyah syafi’iyah sukorejo begitu penting dalam sektor penunjang kehidupan santri. Demi menjaga kualitas listrik agar kinerja dan usia pakainya baik maka diperlukannya alat yang dapat memonitoring secara berkala untuk menghindari terjadinya pemborosan serta pemakaian energi listrik secara illegal. Namun proses pengecekan masih dilakukan secara manual. Maka dari permasalahan diatas dilakukanlah penelitian berupa perancangan alat monitoring daya listrik berbasis IoT pada ponpes salafiyah syafi’iyah sukorejo. Perancangan alat ini yaitu dengan merancang perangkat lunak dan perangkat keras. Perangkat keras yang digunakan yaitu board ESP32 untuk membaca dan mengolah data sensor tegangan, arus dan energy dari modul sensor PZEM-004T secara jarak jauh. Kemudian perancangan perangkat lunak dengan menggunakan aplikasi Blynk yang dihubungkan melalui koneksi internet. Hasil pada pengujian alat mampu bekerja dengan baik dalam membaca tegangan, arus, energy serta memiliki tingkat akurasi sebesar 100%.
KLASIFIKASI PENJUALAN WALMART MENGGUNAKAN ALGORITMA C4.5 Iftar Ramadhan; Rangga Febrio Waleska; Syarifuddin elmi; Lusiana Efrizoni; Rahmaddeni
BETRIK Vol. 15 No. 02 (2024): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/pjbkse24

Abstract

Penelitian ini bertujuan untuk memprediksi penjualan Walmart dengan menggunakan algoritma C4.5, sebuah metode pohon keputusan yang populer dalam data mining. Prediksi penjualan merupakan aspek krusial bagi strategi bisnis Walmart untuk mengoptimalkan persediaan dan meningkatkan keuntungan. Dataset yang digunakan dalam penelitian ini mencakup data historis penjualan Walmart yang terdiri dari berbagai variabel seperti store, date, weakly sales, holiday flag, temperature, fuel price, uci, unemployment dan faktor-faktor lain yang mempengaruhi penjualan. Dari data variabel tersebut akan melakukan klasifikasi pada data penjualan walmart dari 6.345 record. Hasil pengujian metode dengan evaluasi modeling menunjukkan bahwa metode C4.5 mendapatkan hasil acuracy 0.94, precision 0.43, dan recall 0.75.

Page 17 of 24 | Total Record : 239

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