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Akbar, Yuma
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Komparasi Penerapan Algoritma C4.5 dan Naïve Bayes untuk Ketepatan Waktu Pengiriman Barang Pada PT. Rtrans Logistik Artamandiri Azzahra, Yasmin Aulia; Akbar, Yuma
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1003

Abstract

The logistics industry faces significant challenges in maintaining the punctual delivery of goods, which is a critical factor in enhancing customer satisfaction and reducing operational costs. This research aims to compare the effectiveness of the C4.5 and Naïve Bayes algorithms in analyzing the factors that influence delivery punctuality at PT. Rtrans Logistics Artamandiri. A dataset comprising 1,000 shipping records and 13 relevant attributes was utilized to assess each algorithm’s predictive performance in supporting decision-making processes related to delivery efficiency. The findings reveal that the C4.5 algorithm achieves a higher accuracy of 95.00%, compared to the Naïve Bayes algorithm, which reached an accuracy of 91.00%. Furthermore, this study highlights the importance of selecting the appropriate algorithm in logistics management to enhance operational efficiency and customer satisfaction. The results of this research are expected to provide a foundation for strategic decision-making in the field of goods delivery, particularly in optimizing delivery timeliness.
Implementasi Algoritma A* (A-Star) untuk mencari Rute Tercepat dari Bandara Soekarno Hatta ke Destinasi Kota Tua Jakarta Arfadhillah, Zahra; Akbar, Yuma
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1006

Abstract

The tourism sector is an economic sector that is growing rapidly. One of the best destinations that can be used as a tourist destination in DKI Jakarta is the Old City of Jakarta. The Old City of Jakarta has easy access and very affordable costs. There are many roads to the Old City of Jakarta, but the road to the Old City of Jakarta is very far away and has traffic congestion, especially towards the weekend, which could potentially make it difficult for tourists who want to visit. Therefore, we need an effective method that can help find the route with the shortest distance and fastest travel time. In this research, the method that can be used to find the fastest path or route is the A*Star algorithm. The results obtained after examining three routes (Jalan Kapuk Kamal Raya, Jalan Peta Barat and Jalan Raya Daan Mogot), obtained the fastest route with a distance of 5,881.5 KM, namely the Jalan Kapuk Kamal Raya route. By applying this method, it is hoped that it can solve the problem of determining the fastest route to the tourist location of the Old City of Jakarta.
Analisis Penggunaan Metode XConnect Main and Backup Link Berbasis VPN MPLS Layer 2 pada Jaringan Metro-Ethernet Saputra, Mochammed Erryandra; Akbar, Yuma
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1009

Abstract

The rapid development of information and communication technology requires excellent scalability, which is crucial for network performance availability. MPLS is a technology that can be used for communication in high-speed backbone networks based on virtual private networks (VPN). MPLS provides solutions to various current computer network problems such as speed, scalability, quality of service (QoS), and network traffic management. This research aims to optimize the scalability of MPLS Layer 2 VPN-based network traffic by applying the xconnect main and backup method implemented in metro Ethernet networks. The network simulation implementation was created using the Emulated Virtual Environment – Next Generation (EVE-NG) application to obtain data on convergence time and QoS parameters according to TIPHON standards, as well as the use of MPLS and Route Reflector to enhance MPLS backbone performance. This research shows that both main and backup MPLS L2VPN paths have good index values in packet delivery according to TIPHON standards, with an average rating of 3.0. Thus, this research can help optimize path scalability to improve the quality of MPLS L2VPN network traffic.
Analisis Penerimaan Pengguna Aplikasi Kipin School Menggunakan Metode Technology Acceptance Model (TAM) Akbar, Yuma; Bachtiar, Yuliana
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1013

Abstract

This study aims to analyze user acceptance of the Kipin School application in educational settings using the Technology Acceptance Model (TAM) approach. In the era of digital transformation, educational applications like Kipin School play a crucial role in enhancing the effectiveness, efficiency, and quality of learning. This application provides advanced features such as student management, lesson scheduling, academic reporting, and communication between teachers, students, and parents. The study evaluates perceived usefulness and perceived ease of use as the main dimensions influencing user attitude, behavioral intention to use, and actual system use of the application. The results of this research are expected to provide valuable insights for application developers to design more effective, innovative solutions that support the improvement of learning quality and educational management in the future. Additionally, this research is also expected to serve as a foundation for further studies in the field of technology acceptance in education.
Analisa Sentimen Pada Media Sosial “X” Pencarian Keyword ChatGPT Menggunakan Algoritma K-Nearest Neighbors (KNN) Akbar, Yuma; Regita, Anggit Nur Hannaa; Sugiyono; Wahyudi, Tri
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1016

Abstract

Sentiment analysis of the use of Artificial Intelligence (AI) is becoming increasingly important in public understanding of today's rapidly evolving technology, as it helps facilitate human activities. One of the key applications is the presence of ChatGPT, an AI capable of interacting with users through user input, such as answering various questions posed. This topic generates a lot of pros and cons, as widely discussed on social media. Research is needed to evaluate how wisely people use this AI. This study proposes an approach using the K-Nearest Neighbors (KNN) algorithm to analyze AI-related sentiment. The KNN algorithm is used to classify sentiment into positive, negative, or neutral, based on the similarity with the closest word in the feature space derived from text data. This method allows for efficient sentiment grouping without the need for complex models. Researchers chose sentiment analysis because it is an appropriate technique for data processing. Of the 1000 reviews collected from social media users on “X,” 853 were positive, and 147 were negative. The data was classified using the KNN algorithm, followed by an accuracy evaluation yielding 84.80%. The results of this sentiment analysis are expected to guide decision-makers in developing and applying AI technology more intelligently, in line with societal needs and expectations.
Implementasi Algoritma A* (A-Star) untuk Mencari Rute Terpendek dari Kelurahan Cibubur ke Perpustakaan Nasional Republik Indonesia Damayanti, Yulia; Akbar, Yuma
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1022

Abstract

Traffic congestion is a major challenge in Indonesia's big cities, including Jakarta, causing unpredictable travel times, increased pollution and reduced quality of life. The causes of traffic jams in Jakarta include limited road infrastructure, an increase in the number of vehicles, and disorderly driver behavior. One solution is to utilize available alternative routes to reduce congestion and provide more efficient travel options. The National Library of the Republic of Indonesia in Jakarta, although it provides complete facilities to support learning and research activities, is often difficult to access due to traffic jams. Travel from the outskirts of cities such as Cibubur to the city center can be hampered by traffic jams at certain points. Therefore, an effective method is needed to find the closest and fastest route. The A* algorithm is an optimal and efficient route finding algorithm, often used in navigation and route planning. Implementation of the A* algorithm can help drivers find the fastest and shortest routes, reduce travel time, save fuel, and increase transportation efficiency. The research results show that of the three routes studied (Jl. Raya Bogor, Jl. DI Pandjaitan, and Jl. H.R. Rasuna Said), the DI Pandjaitan route is the fastest route with a distance of 1,561.5 km. The implementation of the A* method is expected to help find community routes quickly and overcome congestion problems and lack of knowledge about alternative routes.
Monitoring Data Nilai Gizi Balita menggunakan Tableau Public (Studi Kasus : Posyandu Sedap Malam) Akbar, Yuma; Azzahra, Yasmin Aulia; Hartinah, Suci Sugih; Arfadhillah, Zahra
Jurnal Pengabdian Nasional (JPN) Indonesia Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpni.v5i2.674

Abstract

In Indonesia, there are still toddlers with poor nutritional status. Nutrition is food substances needed for the development, growth, and health of a person's body. Toddlers who experience nutritional problems will have an impact on their growth and development, be susceptible to disease, and can even result in death in children under five. Children's growth and development are monitored regularly to detect potential problems early. Utilizing a community-based health system such as Posyandu is the most important key to improving the quality of children's growth and development. Monitoring of children's growth and development in Indonesia is carried out by measuring body weight every month at Posyandu with the Healthy Way Card (KMS) as a supporting tool. Through KMS, growth and development disorders in children can be identified early and appropriate steps can be taken to correct these problems. The Berbabis Tablue Posyandu Service Analysis Information System can help monitor data and information on the nutritional status of each child. The results of this paper show that the use of Tableau in analyzing data on the nutritional status of toddlers can provide a comprehensive and in-depth picture. Interactive visualization allows users to explore data directly, identify patterns, and quickly retrieve important information. With visualization, posyandu cadres can make decisions regarding toddler nutrition programs
Implementasi Platform Edukasi Pada Klinik Medikasih Pondok Kelapa Jakarta Timur Akbar, Yuma; Maulana, Rizki; Ramadhan, Muhammad Arya; Sibarani, Julvan Marzuki Putra
Jurnal Pengabdian Nasional (JPN) Indonesia Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpni.v5i2.680

Abstract

Medikasih Clinic, which is located in Pondok Kelapa Village, Duren Sawit District, East Jakarta City, Special Capital Region of Jakarta, currently relies on a paid platform to manage clinic operations. However, there is no specific health education platform available for patients/customers, and the importance of improving the quality of health services at this clinic is highly recognized. To overcome these challenges, the service team plans to launch a web-based health education platform. This platform aims to support increased patient participation and health literacy by presenting health information from various medical sources. Based on the analysis of popular medical record diagnoses at Medikasih Clinic, we are determined to provide users with easy and reliable access to understanding health conditions, preventive measures, and healthy lifestyle practices. In conclusion, the development of this platform is a progressive step to create a positive impact. A focus on increasing health literacy and patient participation will create a society that is more informed and involved in personal health management. Our recommendation is to engage health experts and specialists to contribute educational content, ensuring the accuracy and reliability of the information presented
Penerapan Visualisasi Data dan Informasi Kependudukan Berbasis Web: Application of Web Based Visualization of Population Data and Information Mayangsari, Descania; Akbar, Yuma; Bebriani, Serli
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 3 (2024): MALCOM July 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i3.1290

Abstract

Pelaksanaan kegiatan ini bertujuan untuk membantu masyarakat di Rukun Warga 01 Jatinegara dalam memantau pertumbuhan dan perkembangan penduduk dalam kurun waktu 1 tahun kebelakang. Pengabdian ini menerapkan dashboard monitoring berbasis Tableau untuk mempermudah pemahaman dan tren dalam pemantauan perkembangan penduduk berbasis website, data disajikan dalam berbentuk grafik., mempermudah dalam pemantauan  yang cepat. Data yang dikumpulkan kualitatif untuk memastikan keakuratan informasi yang diperoleh dengan fokus pada pengumpulan, pengolahan, dan pengembangan data. Hasil dari penelitian yang didapat dengan perbandingan rata – rata data kelahiran : warga meninggal , dan warga pindah dari RW 01 :  pindahan ke RW 01 yaitu: 5 :4 dan 55:33. Hal ini menunjukkan penggunaan tablue public berjalan dengan baik dan dapat memonitoring pertumbuhan penduduk di RW 01 Jatinegara. Melalui kegiatan pengabdian ini, diharapkan masyarakat Rukun Warga 01 Jatinegara juga dapat memonitoring data tentang pertumbuhan warga dengan lebih mudah, akurat dan efektif, serta meningkatkan kesadaran akan memantau perkembangan penduduk di suatu organisasi masyarakat.
Analisis Sentimen Terhadap Program Kartu Indonesia Pintar Kuliah pada Media Sosial X Menggunakan Algoritma Naive Bayes: Sentiment Analysis of the Indonesian Smart College Card Program on Social Media X Using the Naive Bayes Algorithm Pramudita, Diky; Akbar, Yuma; Wahyudi, Tri
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 4 (2024): MALCOM October 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i4.1565

Abstract

Penelitian ini menunjukkan bahwa publik memiliki berbagai tanggapan terhadap Program Kartu Indonesia Pintar Kuliah (KIP-K) yang dapat dikategorikan ke dalam sentimen positif dan negatif. Permasalahan yang diteliti adalah bagaimana tanggapan publik terhadap program KIP-K yang diungkapkan melalui media sosial X. Penelitian ini menggunakan metode analisis sentimen dengan algoritma Naive Bayes dan pendekatan CRISP-DM untuk memastikan proses analisis yang sistematis dan terstruktur. Data yang dikumpulkan sebanyak 1.516 tweet yang mengandung kata kunci "KIP-K" melalui teknik crawling data menggunakan API X. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes efektif dengan akurasi 84.99%, presisi sentimen positif 83.54%, dan presisi sentimen negatif 87.25%. Solusi yang ditawarkan adalah penggunaan teknik machine learning untuk secara otomatis mengkategorikan sentimen dari data teks yang besar dan tidak terstruktur. Manfaat dari penelitian ini adalah memberikan wawasan kepada pemerintah dan pemangku kebijakan tentang persepsi masyarakat terhadap program KIP-K, yang dapat dijadikan dasar untuk evaluasi dan perbaikan program di masa mendatang. Kesimpulannya, algoritma Naive Bayes dapat mengklasifikasikan sentimen dengan baik menggunakan data dari tweet tentang KIP-K, dengan hasil yang menunjukkan dominasi sentimen negatif. Penelitian ini juga berkontribusi dalam pengembangan metode analisis sentimen berbasis machine learning di bidang pendidikan.
Co-Authors AA Sudharmawan, AA Abdillah, Gipari Pradina Abdul Shomad Abdulloh Abror, Ikhsan Adhipramana, Fernanda Aditya Bagas Pramudhi Aditya Zakaria Hidayat Adzani, Adinda Mutiara Agung Pratama Agung Wianata Sugeng Kusuma Agung Wiranata Sugeng Kusuma Ahluna, Faza Ahmad Zulfikar Aidil Rizki Hidayat Aimar, Muqorrobin Akhsani, Ziyat Akmaludin Akmaludin Al Ammaar, Mohammad Farroos Albahy, Abdurrahman Asyam Aldi Sitohang Aldino Nur Ihsan Angga Tristhanaya Anita Rosiana Anwar, Imam Dzikrilloh Arfadhillah, Zahra Arham, Muhammad Ari Ramadhan Arief, Yoga Sofyan Arif, Sulthan Cendikia Arinal, Veri Aula, Raisah Fajri Aulia, Mutia Dwi Awang Hariman, Aloisius Az-zahra, Haura Salsabila Azis, Iim Muhaemin Abdul Aziz Septian Amrullah Azzahra, Yasmin Aulia Bachtiar, Yuliana Bebriani, Serli Benny Sulaiman K Betty Yel, Mesra Bintoro, Bayu Bryan Pratama Cahyono, Bayu Adi Candra Milad Ridha Eislam Dadang Iskandar Mulyana` Dadang Iskandar, Dadang Damayanti, Yulia Dava Septya Arroufu Dedi Dwi Saputra Dewa Gde Adi Murthi Udayana Doddy Mulyadi Saputra Edhy Poerwandono Edhy Poerwandono Eka Satria Maheswara Fadhil Khanifan Achmad Fadillah, Fauzan Fahmi Chairulloh Faisal Akbar Farhani, Aulia Febrianti, Syafira Feni Putriani Fentri Boy Pasaribu Fernanda Adhipramana Gusniar Alfian Noor Hartinah, Suci Sugih Hengky, Mario Hidayat, Aditya Zakaria Ikhwanul Kurnia Rahman Jodi Juliansah Juliansah, Jodi Julianto, Muhammad Rizky Lestari, Dinny Amalia M Ilham Setya Aji M Jundi Hakim Mafazi, Luthfillah Marjuki Maulana Putra Hertaryawan, Ryfan Mayangsari, Descania Meilisa Miftahul Huda Mizsuari Muamar Rizky Muhamad Farisi Muhamad Fikri Nugraha Muhammad Faizal Lazuardi Mulya, Citra Pricylia Ananda Nadip, Muhamad Zaeni Nirat Nirat Nirat, Nirat Novianto, Firza NST, Silvan Nufus, Reda Hayati Nugraha, Muhamad Fikri Nur Arif Khairudin Nur Oktavian Nurfaishal, Muhammad Dzaky Nurmaylina, Vivi Oka Prasetiyo Oky Tria Saputra Oky Tria Saputra7 Permatasari, Veren Nita Piqih Akmal Poerwandono, Edhy Praja Raymond , Samuel Pramudita, Diky Prasetiyo, Oka Putri Wibowo, Salsabila Qibthiyah, Mariyatul Qolbi, Rofika Ramadhan, Muhammad Arya Regita, Anggit Nur Hannaa Rezha Mulia Revandy Richard Franido Richard Franido Rizki Maulana, Rizki Rizky Adawiyah S, Fahmi Chairulloh Widia Safhani, Rizca Sahrul Hidayat Sahrul Hidayat Saputra, Mochammed Erryandra Sarimole, Frencis Matheos Septiansyah, Ade Setiawan, Kiki Sibarani, Julvan Marzuki Putra Sri Lestari Sri Lestari SRI LESTARI Sugiharto, Tri Sugiyono Sugiyono Sugiyono Sumpena Sumpena Sumpena, Sumpena Surapati, Untung Sutisna Sutisna Sutisna Sutisna Suwandi Tegar Muhamad Hafiz Tegar Muhamad Hafiz Toriq, Fatkul Tri Wahyudi Tundo, Tundo Untung Surapati Untung Surapati Untung Wahyudi Untung Wahyudi Wahyu Saputro Wijaya, Rohmat WINDU GATA Yusril Nurhadi AS