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INDONESIA
Jurnal Komputer, Informasi dan Teknologi
Published by Indonesian Journal Publisher
ISSN : -     EISSN : 28072588     DOI : https://doi.org/10.53697/jkomitek.v6i1
Core Subject : Science, Education,
Computer Science & IT Education Languange, Linguistic, Communication & Media
Jurnal Komputer, Informasi dan Teknologi 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 the 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 390 Documents
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Holistik Model Fuzzy Sugeno dan Pengambilan Keputusan Supplier dalam Produksi Air Galon Demineral Ahmad Zaelani; Silvi Arianti; Della Mahaerani; Titah Pramudito; Indira Khoerul Nisa
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 Moch Pamungkas; Denny Irawan
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 Asoka Dhananjaya; Jeanny Pragantha; Darius Haris
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 Nuniek Fahriani
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 Febri Aditiya; Donny Maulana; 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 Mohammad Fauzie; 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.
Analisis QoS Pada Internet Desa Puguk Menggunakan Standar THIPON Afredo Aditam; Marhalim; Khairullah; A.R Walad Mahfuzhi
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.v4i2.2020

Abstract

Jaringan internet juga harus dilakukan analisa agar dapat diketahui bahwa pengguna jaringan atau pelanggan telah merasa puas atau tidak dengan fasilitas jaringan yang diberikan tersebut. Dengan mengetahui analisa jaringan maka akan dapat disimpulkan bahwa pengguna layanan internet mempunyai jaringan yang bagus atau tidak sehingga menjadi salah satu acuan bagi penyedia layanan atau yang disebut ISP (Internet services propeider), untuk memberikan layanan yang lebih baik bagi pengguna. Analisa jaringan menggunakan QoS (Quality of Service) khususnya adalah throughput, dellay dan packet loss mampu memberikan analisa jaringan yang baik, dimana aspek ini yang sering digunakan didalam analisa jaringan. Hasil dari penelitian ini adalah Nilai QoS yang dihasilkan pada pengujian parameter throughput sebesar 52,17% dengan indek 3, sedangkan pada pengujian parameter delay nilai yang dihasilkan sebesar 45ms dengan indek 4 dan pada pengujian parameter packet loss nilai yang dihasilkan sebesar 18,52% dengan nilai indek 2. Dari hasil perhitungan tersebut, layanan internet pada kantor desa puguk termasuk dalam katagori bagus berdasarkan standar THIPON yaitu dengan nilai indeks 3.
Design of a Website-Based Company Profile at SMK Al-Idrus Kutai Kartanegara Mu Fahrozi; Aspianur; Wawan Pranoto
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.v4i2.2038

Abstract

The development of technology in education encourages SMK Al-Idrus Kutai Kartanegara to embrace the digital world. This study aims to address the challenges of limited resources in integrating web design skills by developing a web-based company profile application using the prototyping method. The program involves stages such as requirement gathering, prototype development, user evaluation, and final product development. The resulting application includes interfaces such as a homepage, admin panel, news section, departments, student admission (PPDB), school profile, and login page. Through this activity, students gain practical experience in web development, enabling them to compete in the digital era and meet the demands of the information technology and graphic design industries.
Analysis of the Impact of Interview-Based Feature Selection on the Performance of Machine Learning Algorithms in Mental Health Disorder Classification Hendrick
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.v4i2.2039

Abstract

Mental health issues in the workplace have become an increasingly important concern, particularly in the high-pressure environment of the information technology industry. This study aims to evaluate the impact of feature selection based on interviews on the performance of machine learning models in classifying mental health disorders. The dataset used is sourced from Open Sourcing Mental Illness (OSMI), which consists of various features related to employees' mental health conditions, previously used without feature selection in prior research. Through an interview with an experienced Human Capital professional with a psychological background, relevant features were selected based on domain expertise. Subsequently, machine learning models, namely Random Forest and XGBoost, were trained using two scenarios: without feature selection and with feature selection. The results of the study indicate that feature selection based on interviews can improve model accuracy by 1.67% for Random Forest and 0.67% for XGBoost. These findings emphasize the importance of integrating psychological insights into the data processing to produce more relevant and efficient models. This research provides practical contributions to assist companies in implementing early detection of mental health disorders effectively.
Sentiment Analysis Related to Law No. 6 Of 2023 on the Employment Cluster Using the Bidirectional Long Short-Term Memory Algorithm Anugra M; Munawar
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.v4i2.2051

Abstract

The enactment of UU Cipta Kerja has triggered varied public responses, particularly concerning employment provisions like fixed-term employment (PKWT), the legalization of outsourcing, unfair severance pay, and ease of layoffs. Social media has become a primary platform for the public to share opinions on issues within the law’s employment cluster. This study employs sentiment analysis using the Bidirectional Long Short-Term Memory (Bi-LSTM) algorithm to understand public sentiment about UU Cipta Kerja and sentiment within its content. Bi-LSTM is chosen for its ability to capture temporal relationships and context in long texts, which aids in handling complex sentiment classification. The findings indicate varied public perceptions: neutral sentiment dominates issues like "PKWT" and "Minimum Wage" on Twitter (X), reflecting uncertainty. Positive sentiment appears around "Outsourcing" and "Minimum Wage" provisions, indicating perceived flexibility. Conversely, negative sentiment dominates issues like "Layoffs" and "Severance," on both social media and in UU Cipta Kerja content, signaling concerns over worker rights. The Bi-LSTM model achieved 70.15% accuracy for the Twitter dataset and 83.22% for the law’s content dataset.

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