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INDONESIA
Jurnal Komputer, Informasi dan Teknologi
Published by Indonesian Journal Publisher
ISSN : 2807256     EISSN : 28072588     DOI : https://doi.org/10.53697/jkomitek.v1i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
KOMITEK Journal (Computer, Information and Technology) journal was founded in 2021. It is an interesting and useful national journal for all parties with an interest in research in various fields of, or closely related to, the disciplines of Computer, Information and Technology. KOMITEK Journal aims to provide a highly readable and valuable addition to the literature that will serve as an indispensable reference tool for years to come. The scope of the journal includes all new theoretical and experimental findings in the field of Computers, Information and Technology or any closely related field. The journal also encourages submission of critical review articles covering advances in the latest research in the field of Computers, Information and Technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 377 Documents
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Deteksi Objek Video Bahasa Isyarat Untuk Anak Tuna Rungu dan Tuna Wicara Menggunakan YOLOv8 Maheza Fresmanda, Muhammad; Istiadi; Syahroni Wahyu Iriananda
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1895

Abstract

Penelitian ini bertujuan untuk mengimplementasikan keberhasilan model algoritma YOLOv8 dalam mendeteksi abjad bahasa isyarat Indonesia (BISINDO) berbasis video. BISINDO merupakan adaptasi American Sign Language (ASL) yang disesuaikan dengan budaya Indonesia agar lebih mudah digunakan. Itu bergantung pada gerakan dua tangan untuk komunikasi. Model YOLOv8 mampu mendeteksi dan mengklasifikasikan bahasa isyarat Indonesia dengan tingkat akurasi yang cukup baik, mencapai precision 93,35%, recall 70,25%, mAP50 64,05% dan mAP50-95 45,88%. Temuan ini diharapkan dapat memberikan kontribusi positif dalam pendidikan dan komunikasi untuk anak tunarungu dan tunawicara
Methodology of Strengthening Students’ Media Literacy Isakov, Olimjon
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1900

Abstract

In today’s digital age, media literacy has become an essential skill for students. The rise of social media, fake news, and information overload necessitates that students critically evaluate and understand media messages. Media literacy involves the ability to access, analyze, evaluate, create, and communicate using various forms of media. It is not merely about learning to use digital tools, but about understanding how media influences perceptions and behavior. The growing role of media in shaping political, social, and cultural realities makes it essential to adopt methodologies that strengthen students' media literacy skills. This article explores key methodologies that educators can implement to enhance media literacy in students.
Implementation of the Design Thinking Method in Optimizing the UI/UX of the Maxim Application Destari, Salsabilla; Admirani, Ica; Darlies, Meiyi
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1922

Abstract

The Maxim application faces low user satisfaction, particularly in terms of ease of navigation and feature access speed. The average user satisfaction with ease of navigation before the improvements was 53.44%, while satisfaction with feature access speed reached only 52.43%. This study aims to improve the quality of the user interface (UI) and user experience (UX) by applying the Design Thinking method. This method involves five stages empathize, define, ideate, prototype, and test, which are used to identify problems, design solutions, and test the results of the improvements. Data were collected through interviews, questionnaires, and user reviews on Playstore, which were then evaluated using A/B testing with 100 respondents. The results showed that after the improvements, user satisfaction with ease of navigation increased to 73.77%, while feature access speed increased to 73.00%. Therefore, the application of the Design Thinking method successfully enhanced both the ease of use and the speed of feature access in the Maxim application.
Identification of Cactus Species Using the MobileNet Convolutional Neural Network Model William Mulyadi; Chairisni Lubis
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1933

Abstract

The objective of this design is to create a system capable of accurately and precisely classifying different types of succulent cacti. The system design aims to create a succulent cactus classification application using a Convolutional Neural Network (CNN) with the MobileNet architecture. The process involves collecting cactus images, dividing them into training and test datasets, and developing a CNN model to recognize patterns in succulent cactus species. The training data is used to train the CNN model, and the test data evaluates the model's accuracy. The trained model, stored in Tf.lite format, successfully classifies 15 cactus types, achieving high accuracy by employing preprocessing steps like resizing, normalization, and background removal. Over 1,200 cactus images were taken with a smartphone, categorized into 15 classes, and prepared to ensure optimal lighting, angle, background, and resolution (224x224 pixels). The MobileNet model was chosen for its high accuracy and efficiency. Hardware used includes a Samsung A54 smartphone and an Intel i7 laptop, with software such as Python, Kotlin, and Android Studio facilitating development. This design ensures the application’s accessibility, making it a valuable tool for cactus enthusiasts and the general public to easily identify different succulent cactus types. Testing of the cactus species classification program using the Convolutional Neural Network (CNN) method with the MobileNetV2 architecture yielded strong results, achieving over 90% accuracy in classifying 15 cactus species. The highest training accuracy of 0.9837 was achieved at 150 epochs without early stopping, outperforming other epoch configurations. The model successfully classified species across five main genera—Kalanchoe, Crassula, Echeveria, Haworthia, and Euphorbia. This high accuracy highlights the model's effectiveness, making it a useful tool for cactus enthusiasts and the public to accurately identify and distinguish cactus species.
Holistik Model Fuzzy Sugeno dan Pengambilan Keputusan Supplier dalam Produksi Air Galon Demineral Zaelani, Ahmad; Arianti, Silvi; Mahaerani, Della; Pramudito, Titah; Nisa, Indira Khoerul
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1938

Abstract

Perusahaan memiliki bisnis produk air demineral galon 19 Liter dengan prioritas kesehatan konsumen dan memiliki keuntungan maksimal atas perolehan penjualan. Jika jumlah produk yang telah diproduksi ke calon konsumen kurang dari jumlah input yaitu permintaan maka perusahaan akan mengalami kehilangan peluang untuk mendapatkan keuntungan maksimal. PT PTK dalam pengambilan kebutuhan membutuhkan alat untuk menganalisis akar permasalahan yang terjadi dalam pemilihan supplier galon sebagai penunjang efisiensi produksi air demineral galon yaitu dengan nama produk Quatri. Penelitian ini menggabungkan metode fuzzy Sugeno dan Superdecision secara keseluruhan sebagai satu kesatuan untuk membangun sistem pendukung keputusan terintegrasi dalam optimasi produksi air minum dalam kemasan. Metode fuzzy Sugeno diimplementasikan dalam menentukan jumlah produksi galon Quatri yang optimal berdasarkan input permintaan dan persediaan, sedangkan Superdecision digunakan untuk memilih supplier yang paling sesuai dengan kriteria perusahaan untuk penunjang proses produksi. Hasil penelitian menunjukkan bahwa model terintegrasi ini mampu memberikan rekomendasi secara komprehensif dan akurat dibandingkan menggunakan masing-masing metode secara terpisah.
Monitoring and Control System for Temperature, Humidity, and Air Quality in LVMDP Panel Rooms to Improve the Reliability of LVMDP Panel Components Using Fuzzy Logic Pamungkas, Moch; Irawan, Denny
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1958

Abstract

Power Distribution System plays a crucial role in modern life. Low Voltage Distribution Panel (LVMDP) is a critical component within this system, responsible for distributing low-voltage electricity to various loads. Optimal reliability and performance of LVMDP are essential to ensure continuity and stability of power supply. Environmental factors such as temperature, humidity, and air quality can significantly impact the reliability and lifespan of electrical equipment in LVMDP. An Internet of Things (IoT) and Fuzzy Logic-based Monitoring and Control System offers an innovative solution to address these issues. The IoT Monitoring System enables real-time monitoring of temperature, humidity, and air quality, allowing for early detection of environmental changes that could potentially damage equipment. The Fuzzy Control System then responds to these changes automatically and adaptively, regulating cooling, heating, circulation, dehumidifier, or humidifier devices to maintain optimal environmental conditions. Implementing this Monitoring and Control System not only enhances equipment reliability and lifespan but also reduces the risk of power supply disruptions. Therefore, the development and implementation of this system serve as an innovative and essential solution in maintaining the reliability of the power system. Advancements in IoT and Fuzzy Logic technologies open up opportunities to improve the overall reliability and efficiency of the Power Distribution System. This Monitoring and Control System presents a strategic step that can yield significant positive impacts on the reliability and performance of the Power Distribution System as a whole.
Rancangan Pembuatan Puzzle 2D "Perfect Match" untuk Perangkat Android Dhananjaya, Asoka; Pragantha, Jeanny; Haris, Darius
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1961

Abstract

“Perfect Match” adalah game puzzle match-3 dengan tampilan 2D yang dirancang untuk perangkat Android. Unity serta C# sebagai bahasa pemrograman digunakan dalam pengembangan game ini. Game ini dirancang dengan tujuan sebagai sarana hiburan dengan mengajak pemain untuk mencocokkan objek serta menggunakan strategi untuk menyelesaikan level. Uji yang dilakukan oleh dosen pembimbing menggunakan metode blackbox testing dan alpha testing, pengujian yang dilakukan terhadap responden yang berjumlah 30 dilakukan menggunakan beta testing yang melalui survei. Pengujian yang dilakukan menunjukkan hasil yakni mayoritas responden merasa tampilan dan gameplay menarik, meskipun terdapat kekurangan dalam variasi power-ups pada level lanjut.
Penerapan Kriptografi DES Untuk Keamanan Data Teks Pada File PDF Menggunakan Bahasa Pemrograman Phyton Fahriani, Nuniek
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1997

Abstract

Pada seni kriptografi banyak teknik enkripsi yang bisa dmanfaatkan, diantaranya adalah teknik “Data Encryption Standard (DES)” yang tergolong jenis cipher blok yang menggunakan kunci simetris yang dapat mengenkripsi pesan sebanyak 64 bit. Terdapat tiga tahapan operasi untuk teknik data encryption standard-DES, tahap satu dengan menjalankan perubahan letak atau permutasi, selanjutnya dilakukan rotasi, dan langkah ketiga adalah melakukan fungsi substitusi. Pada penelitian ini bahasa permograman yang digunakan adalah bahasa python. Objek yang menjadi sebagai plainteks (teks asli) adalah file dokumen PDF (portable document format). Program python yang dijalankan dapat melakukan enkripsi sekaligus melakukan kompresi ukuran PDF (portable document format) menjadi lebih kecil. Dengan hasil file plainteks awal sebesar 7.55 KB (7.732 bytes). Sesudah dilakukan enkripsi menjadi 1.99 KB (2.039 bytes). Selanjutnya adalah proses dekripsi mengembalikan lagi ke dalam teks yang bisa dibaca dengan ukuran file sebesar 1.30 KB (1.336 bytes).
The Use of Naïve Bayes Algorithm in Sentiment Analysis of Grab Application Reviews Aditiya, Febri; Maulana, Donny; Edora
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.1999

Abstract

This study aims to analyze the sentiment of Grab application user reviews using the Naïve Bayes algorithm. In conducting the analysis, how well the Naïve Bayes algorithm can analyze Grab application user review data. Thus, this process refers to the elements that affect the accuracy of the Naïve Bayes analysis. to analyze the sentiment of Grab application user reviews using the Naïve Bayes algorithm. Thus, it not only evaluates the accuracy of the Naïve Bayes method, but also considers the problem of imbalanced class, because in reality not all datasets can be accessed perfectly. To consider the problem of data imbalance, this study requires the Adaptive Synthetic Sampling or ADASYN technique which is used in machine learning to overcome the problem of class imbalance in the dataset. The tools used in processing the algorithm in the method and conducting the analysis use Google Colab. This study focuses on the classification of positive and negative sentiments from user reviews taken by the scraping process from the Google Play Store platform. The analysis process involves data preprocessing, including tokenization, stemming, and word weighting, to improve the accuracy of sentiment classification. Based on the results of this study, the Naïve Bayes model sought an accuracy result of 85.33%, the precision result obtained was 80.55% and the recall result in this research test was 79.09%, from these results by implementing calculations using a confusion matrix and dividing the data into testing data and training data
Klasifikasi Pengadaan Obat Jaminan Kesehatan Nasional Melalui E-Purchasing Menggunakan Algoritma K-Nearest Neighbor Fauzie, Mohammad; Supatman
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.2003

Abstract

Pemenuhan stok obat berkualitas dalam jumlah cukup merupakan target yang harus dicapai dalam program Jaminan Kesehatan Nasional (JKN) yang dilaksanakan oleh fasilitas kesehatan secara elektronik. Penelitian ini bertujuan melakukan klasifikasi pengadaan obat JKN melalui E-purchasing. Data penelitian bersumber dari dashboard transaksi pada E-Katalog atau Katalog Elektronik Sektoral Kementerian Kesehatan selama periode Januari hingga Oktober tahun 2024 menggunakan algoritma K-Nearest Neighbor (K-NN). Pengujian dengan euclidean distance yaitu jarak kedekatan data latih dan data uji berdasarkan tiga atribut yaitu tingkat komponen dalam negeri, kuantitas, dan harga satuan obat. Jumlah dataset sebanyak 156 record dengan perbandingan data 80:20. Hasil penelitian menunjukkan accuracy tertinggi sebesar 98% pada nilai k=7 dan k=9 sedangkan accuracy terendah sebesar 94% pada nilai k=3. Hasil ini membuktikan bahwa algoritma K-Nearest Neighbor mampu melakukan klasifikasi obat JKN melalui E-purchasing dengan baik.

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