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MULTINETICS
Published by Politeknik Negeri Jakarta
ISSN : 24432245     EISSN : 24432334     DOI : -
Core Subject : Science,
Computer Science & IT
Multinetics is a peer-reviewed journal is published twice a year (May and November). Multinetics aims to provide a forum exchange and an interface between researchers and practitioners in any computer and informatics engineering related field. Scopes this journal are Content-Based Multimedia Retrieval, Multimedia Application, Mobile Computing & Applications, The Internet of Things, Information Systems and Technologies, E- Learning & Distance Learning, Infrastructure Systems and Services, E-Business & E-Commerce, Artificial Intelligence, Embedded System, Network & Data Communication, Big Data and Data Mining, Software Engineering, Computer Network and Architecture, Soft Computing and Intelligent System and Networks and Telecommunication Systems
Arjuna Subject : -
Articles 314 Documents
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Tingkat Kerawanan Desa Berdasakan Dampak Bencana Kab.Bojonegoro Dengan Metode Clustering Algoritma K-Means Fahrur Rozi, Imam; Muhammad Afif Hendrawan; Thalia Amira Rifda
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.6686

Abstract

The Bojonegoro Regency is a region that is quite prone to disasters, especially floods, landslides, and extreme weather. There have been 2,162 recorded incidents in the past three years, causing significant material and moral losses totaling IDR 1,986,210,000. In an effort to reduce future losses, early prevention measures can be taken by conducting research on the potential disaster-prone areas based on the impact of disasters that have occurred in the region. This study utilized data from 430 villages (2019-2022), considering 6 disaster impact parameters, including the number of disaster events, casualties, affected houses, affected land, material losses, and facility damage. The objective was to identify the vulnerability level of villages using the K-Means Clustering method. The optimal number of clusters was validated using the Davies Bouldin Index (DBI), and the data mining process followed the CRISP-DM standard. The trial results indicated that the optimal number of clusters is k=3. Cluster analysis revealed that Cluster 1 (3 villages) experienced more significant disasters, causing more damage to houses and land; Cluster 2 (17 villages) faced disasters with significant casualties, while Cluster 3 (410 villages) experienced disasters with the lowest impact.
Aplikasi Gate Portable Sebagai Efisiensi Proses Pendataan Kendaraan Pada Terminal Peti Kemas Pelabuhan Batu Ampar Nasrullah, Muchamad Fajri Amirul; Wahyuni, Anggun Dini
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.6689

Abstract

Penelitian ini berupaya untuk mengatasi beberapa tantangan yang dihadapi oleh staf di Terminal Peti Kemas Pelabuhan Batu Ampar, PT Persero Batam, khususnya yang terkait dengan waktu yang lama dan potensi kesalahan yang tinggi dalam pencatatan data peti kemas secara manual. Ketidakakuratan tersebut dapat menghambat efisiensi operasional pelabuhan, yang menyebabkan keterlambatan dalam proses penerimaan dan pelepasan peti kemas. Menanggapi masalah yang ada ini, aplikasi Gate Portable berbasis seluler dikembangkan untuk mengotomatiskan proses verifikasi dan pencatatan data. Aplikasi ini dibangun menggunakan bahasa pemrograman Dart dan kerangka kerja Flutter, dan terintegrasi dengan sistem BCTOS melalui REST API, yang memungkinkan pengambilan data secara real-time melalui pemindaian kode QR di lokasi. Proses pengembangan menggunakan metodologi pembuatan prototipe, yang mendorong keterlibatan pengguna dan pemilik sistem secara berkelanjutan di seluruh tahapan pengembangan. Pendekatan ini memastikan bahwa aplikasi tetap selaras dengan persyaratan pengguna sambil memungkinkan penyesuaian yang diperlukan berdasarkan evaluasi yang sedang berlangsung. Tahap pengujian menunjukkan bahwa aplikasi Gate Portable secara signifikan meningkatkan efisiensi operasional. Secara khusus, waktu yang dibutuhkan untuk pengumpulan data berkurang dari rata-rata sepuluh menit menjadi lima menit untuk setiap transaksi nya. Selain itu, keakuratan pencatatan data pun meningkat pesat, sehingga alur kerja operasional berjalan lebih lancar dan risiko kesalahan di lapangan pun dapat diminimalkan.
Face Recognition sebagai Local Control Access Area dengan Face-Api.Js dan Euclidean Distance: Face Recognition sebagai Local Control Access Area dengan Face-Api.Js dan Euclidean Distance Warsuta, Bambang; Nalawati, Rizki Elisa
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.6755

Abstract

Penelitian ini mengusulkan sebuah sistem pengendalian akses berbasis face-recognition dengan menggabungkan algoritma Manhattan Distance dan library dari face-api.js. Kontribusi utama penelitian ini adalah integrasi algoritma Manhattan Distance dalam sistem pengenalan wajah, penggunaan face-api.js untuk mempermudah pengembangan, serta evaluasi kinerja yang komprehensif. Sistem ini telah berhasil mengimplementasikan Manhattan Distance untuk mengukur kemiripan fitur wajah. Sistem ini telah dievaluasi menggunakan berbagai metrik seperti akurasi, presisi, dan recall. Hasil uji menunjukkan kinerja yang baik dengan nilai akurasi mencapai 95 ke atas untuk deteksi wajah dan 100% untuk pengenalan wajah, terutama saat dikombinasikan dengan face-api.js, bahkan dengan dataset yang terbatas.
Potensi Penerapan VANET Untuk Pengembangan Smart City di Kota Ternate Djohar, Fahrizal
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.6774

Abstract

Abstrak-- Pengembangan Internet of Things (IoT) telah menjadi fokus penelitian selama beberapa tahun terakhir dan diperkirakan akan terus berkembang di masa depan. Komunikasi antar perangkat juga sedang dikembangkan seperti teknologi Vehicle Ad-hoc Network (VANET) memungkinkan pertukaran informasi antar kendaraan, namun memiliki karakteristik unik seperti mobilitas tinggi antar node, topologi yang sangat dinamis, tingkat kehilangan data yang cukup signifikan, dan durasi komunikasi antar node yang relatif singkat. Disamping itu, dengan meningkatnya jumlah kendaraan di kota, hal ini dapat dimanfaatkan untuk pengembangan sistem komunikasi di masa mendatang. Penelitian ini bertujuan untuk menghadirkan peluang sistem komunikasi antar kendaraan pada daerah perkotaan, menjadikan VANET sebagai pilihan utama untuk penerapan. Simulasi dilakukan dengan memodelkan kondisi jalan yang dinamis dan mobilitas kendaraan yang tinggi, serta mengukur parameter utama seperti tingkat penerimaan paket, dan tingkat kehilangan paket. Empat protokol digunakan dengan parameter tingkat penerimaan dan jumlah paket yang diterima, dan hasilnya menunjukkan bahwa protokol dengan kinerja terbaik secara berurutan adalah DSR, AODV, DSDV, dan OLSR. Dengan demikian, penelitian ini diharapkan dapat memberikan kontribusi sebagai salah satu konsep smart city dalam pengembangan kota di masa depan.
Rancang Bangun Sistem Otomasi untuk Pemeliharaan Reptil Bearded Dragon Berbasis Internet of Things Zain, Ayu Rosyida
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.6093

Abstract

Reptiles, including bearded dragons, have become a popular trend in the pet world, with live animal imports reaching USD 52,111,601. This increase is due to the interest of the Indonesian community in keeping exotic pets. In several European countries, bearded dragons even rank third as the most commonly kept pets after dogs and cats. However, the care of bearded dragons requires intensive attention to prevent diseases such as Metabolic Bone Disease (MBD), obesity, and others. Therefore, an automatic bearded dragon care system is proposed for terrariums, equipped with scheduled lighting and feeding, automatic heating and cooling, and automatic water supply. In its implementation, the system uses DHT22 temperature and humidity sensors, HC-SR04 ultrasonic sensor, and RTCDS3231. This device utilizes Arduino Mega and ESP32 as the medium for transmitting and receiving data from each sensor. This research yielded an average accuracy value of 97.92% for temperature and 86.36% for humidity using the DHT22 sensor, 97.55% accuracy for the feeding and water status using the ultrasonic sensor, and 99.93% accuracy using the RTCDS3231. After undergoing a 5-day durability test with 5 schemes, this device has good durability. With this device, it is hoped to assist bearded dragon owners in their care efforts.
ANALISIS SENTIMEN KELUHAN PEGAWAI DENGAN MENGGUNAKAN MACHINE LEARNING Syahra, anita alfi; Mohamad Nurkamal Fauzan; Cahyo Prianto
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.6894

Abstract

PT Dirgantara Indonesia (PTDI) faces challenges in managing employee complaints. This research aims to improve PTDI employee complaint management through sentiment analysis using the Naive Bayes algorithm with the CRISP-DM method. The stages applied include business understanding, data understanding, data preparation, modeling, evaluation and implementation. Employee complaint data is collected and processed using stop words removal and tokenization techniques. The Naive Bayes model is trained and evaluated using accuracy, precision, recall and F1-score metrics. The research results show that the Naive Bayes model is effective in grouping employee complaints into mild and severe categories. The model has an accuracy of 88.5%. The implementation of this sentiment analysis system is expected to help PTDI management handle employee complaints more quickly and precisely, increasing satisfaction and productivity. This research also contributes to the development of the science of sentiment analysis and machine learning, as well as its application in complaint management in companies. With this system, PTDI management can identify and prioritize complaints that require immediate handling, increasing operational efficiency and service quality to employees. This research provides practical solutions for PTDI and adds insight into the application of machine learning in managing employee complaints.
Penerapan Algoritma Support Vector Machine untuk Melakukan Analisis Potensi Tsunami di Indonesia Prasetyo, Hary; Maulana, Asep Erlan
MULTINETICS Vol. 10 No. 2 (2024): MULTINETICS Nopember (2024)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v10i2.7245

Abstract

Indonesia is located in the Pacific Ring of Fire, so it often experiences earthquakes that have the potential to cause tsunamis. This study aims to evaluate the performance of Support Vector Machine (SVM) in predicting potential tsunamis in Indonesia using the knowledge discovery in databases method which includes data collection, processing, transformation, data mining, and evaluation. The data were taken from BMKG and categorized based on the depth and magnitude of the earthquake. SVM models were tested with various kernels such as Linear, Polynomial, RBF, and Sigmoid to determine the best performance. The results showed that the Polynomial kernel gave the highest accuracy of 97%, with 99% precision, 94% recall, and 97% F1-score. This model is expected to contribute to the tsunami early warning system in Indonesia and improve disaster mitigation.
IMPLEMENTASI PEMBLOKAN SITUS DENGAN FIREWALL LAYER 7 PROTOCOL MENGGUNAKAN METODE NDLC PADA ROUTER MIKROTIK Imawan, Sonny Aditya; Dwiasnati, Saruni
MULTINETICS Vol. 11 No. 1 (2025): MULTINETICS Mei (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i1.6844

Abstract

In the current era of technological advancement, companies' dependency on computer networks is increasing. Intensive internet usage during working hours presents challenges in efficiently managing bandwidth. Uncontrolled activities such as accessing social media, playing online games, and streaming videos can degrade network quality, disrupt productivity, and cause service dissatisfaction. This research aims to enhance the efficiency of network usage in the company by focusing on reducing bandwidth due to uncontrolled internet usage, particularly by identifying and blocking access to websites unrelated to work activities using Firewall Layer 7 Protocol. Approximately 45% of employees frequently visit other sites during working hours. System development is carried out using the Network Development Life Cycle (NDLC) method, which illustrates the continuous cycle of computer network development. Testing results in the research using the BlackBox method with Winbox software to assess the planned system performance successfully blocked sites, online games, and increased bandwidth; after implementation, the bandwidth achieved was above 50Mbps during working hours. This method is expected to provide effective solutions to improve network quality, optimize bandwidth usage, and support overall company productivity.
ANALISIS KEAMANAN WEBSITE KOTA DEPOK MENGGUNAKAN METODE VULNERABILITY ASSESSMENT Kurniawan, Asep; Iik Muhamad Malik Matin
MULTINETICS Vol. 11 No. 1 (2025): MULTINETICS Mei (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i1.7226

Abstract

The increasing use of the internet and websites also increases the threat level of hacking data and information on the internet, especially websites. The National Cyber and Crypto Agency (BSSN) noted that until April 2022, cyber attacks in Indonesia reached 100 million cases. The current rampant case is pishing using the .go.id domain. With the rise of these events to maintain and prevent intrusions and attacks, a security analysis of the website is carried out using the vulnerability assessment method using Owasp ZAP, Acunetix, Vega, Nessus and Skipfish tools that can help find out the vulnerabilities on the website. The purpose of this study is to obtain website vulnerabilities as an anticipatory step from intrusions and other attacks and to determine the level of vulnerability obtained so as not to become a threat to the website and an opportunity for hackers. The results of the analysis found that the depok.go.id website is not yet safe because there are still 5 types of vulnerabilities through internal and external networks with risk alert level High, namely: Hash Disclosure - Mac OSX salted SHA-1, DNS Server Spoofed request Amplification DDoS, Session Cookie Without Secure Flag, Integer Overflow, and Page Fingerprint Diffenrential Detected - Possible Local File Include.
Algoritma K-Means untuk Meningkatkan Silhouette Score pada Pengelompokan Data Stok Bahan Manufaktur di PT. XYZ Kabupaten Majalengka Guntur, Jivi Muzaqi
MULTINETICS Vol. 11 No. 1 (2025): MULTINETICS Mei (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i1.7259

Abstract

Abstrak -- Clustering adalah teknik analisis data yang digunakan untuk mengelompokkan data ke dalam kelompok-kelompok berdasarkan karakteristik yang sama. Tantangan utama dalam pengelompokan adalah menentukan jumlah cluster yang optimal, karena hal ini secara signifikan berdampak pada kualitas hasil. Penelitian ini menggunakan algoritma K-Means untuk mengelompokkan data, yang bertujuan untuk mengidentifikasi jumlah cluster yang optimal dengan menggunakan Silhouette Score dan untuk mengungkap karakteristik unik dari setiap cluster. Penelitian ini mengadopsi pendekatan Knowledge Discovery in Database (KDD), yang meliputi pemilihan data, pra-pemrosesan, transformasi, penggalian data, dan evaluasi hasil. Eksperimen dilakukan untuk menentukan jumlah cluster yang optimal, yang diukur dengan Silhouette Score, sebuah metrik yang mengevaluasi kualitas pengelompokan dengan menilai seberapa baik titik-titik data sesuai dengan cluster yang ditugaskan dibandingkan dengan yang lain. Hasilnya menunjukkan bahwa jumlah cluster yang optimal adalah dua (k=2), dengan Silhouette Score sebesar 0,361658. Analisis lebih lanjut mengidentifikasi dua karakteristik yang berbeda dalam data: Cluster 0, ditandai dengan nilai stok yard dan kilogram di bawah rata-rata, dan Cluster 1, ditandai dengan nilai stok yard dan kilogram di atas rata-rata. Studi ini menyimpulkan bahwa algoritma K-Means, yang dioptimalkan menggunakan Silhouette Score, secara efektif mengidentifikasi pola yang signifikan dalam data, memberikan wawasan yang berharga untuk manajemen stok. Temuan ini diharapkan dapat mendukung pengambilan keputusan strategis dalam manajemen stok, terutama dalam merumuskan kebijakan berdasarkan karakteristik unik dari setiap klaster yang teridentifikasi.

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