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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Syntax Literate: Jurnal Ilmiah Indonesia Journal of Economic, Bussines and Accounting (COSTING) Jurnal Eksplora Informatika SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan INTECOMS: Journal of Information Technology and Computer Science Jurnal Bakti Masyarakat Indonesia Jurnal Sains dan Teknologi Jurnal Pendidikan, Sains dan Teknologi Jurnal Indonesia Sosial Teknologi Communication and Information Journal Jurnal Serina Abdimas
Irvan Lewenusa, Irvan
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Visualisasi Data Penjualan PT XYZ Dengan Tableau Sagaro, Ariya; Sutrisno, Tri; Lewenusa, Irvan
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 6 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i6.13031

Abstract

In a competitive business environment, Company XYZ faced challenges in efficiently managing and analyzing sales data. To address this issue, this study developed an interactive dashboard that simplifies data visualization through prototyping methods, using the Extract, Transform, and Load (ETL) process with Google Colab and Python, and final visualization using Tableau. The goal was to speed up and clarify the decision-making process by presenting sales data in various visual formats such as graphs, charts, and maps. The author faced several significant challenges including integrating inconsistent data from various sources, gaining a deep understanding of user needs, overcoming technological limitations, designing an intuitive user interface, and the necessity for comprehensive testing to ensure system reliability. As a result, this dashboard enhanced operational efficiency and data analysis quality at Company XYZ, enabling quicker responses to market dynamics and improving the company’s competitiveness. With this dashboard, Company XYZ has been able to minimize data analysis time while enhancing accuracy in their business and operational strategies.
PERANCANGAN DASHBOARD INTERAKTIF UNTUK APLIKASI PEMANTAUAN KEDISIPLINAN KARYAWAN DI PT XYZ Yoewono, Gregorius Farrel; Sutrisno, Tri; Lewenusa, Irvan
Journal of Economic, Bussines and Accounting (COSTING) Vol 7 No 5 (2024): Journal of Economic, Bussines and Accounting (COSTING)
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/costing.v7i6.13074

Abstract

Dalam era digital yang terus berkembang, PT XYZ menghadapi tantangan dalam memantau kedisiplinan karyawan secara real-time. Permasalahan yang muncul adalah keterbatasan sistem manajemen perusahaan yang tidak memiliki alat visualisasi data yang memadai, sehingga informasi disiplin karyawan sulit diakses secara cepat oleh berbagai departemen. Penelitian ini bertujuan merancang dashboard interaktif menggunakan Grafana untuk membantu memvisualisasikan data kedisiplinan karyawan. Metode pengembangan yang digunakan adalah Solo Scrum, yang meliputi tahap identifikasi kebutuhan, pembuatan backlog, sprint, dan deployment. Hasil penelitian menunjukkan bahwa dashboard yang dirancang dapat menampilkan data real-time terkait kehadiran dan ketepatan waktu karyawan, serta mengurangi potensi kesalahan manusia dalam pengolahan data. Kesimpulannya, dashboard ini memudahkan PT XYZ dalam memantau kedisiplinan karyawan dan mendukung pengambilan keputusan strategis.
ANALISA SENTIMEN TERHADAP COSPLAYER PADA PLATFORM SOSIAL MEDIA INSTAGRAM MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING Mario, Eric; Budiyantara, Agus; Lewenusa, Irvan
Journal of Economic, Bussines and Accounting (COSTING) Vol 7 No 5 (2024): Journal of Economic, Bussines and Accounting (COSTING)
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/costing.v7i6.13096

Abstract

Media sosial, khususnya Instagram, berperan penting sebagai platform bagi cosplayer untuk berbagi konten serta berkomunikasi dengan pengikutnya. Komentar dari pengguna berisi berbagai pandangan yang dapat dianalisis guna memahami sentimen audiens terhadap cosplayer. Penelitian ini mengumpulkan data komentar Instagram melalui API dan memprosesnya dengan cleaning serta preprocessing untuk menghilangkan informasi tidak relevan dan menormalkan teks. Setelah itu, Untuk klasifikasi sentimen, beberapa model IndoBERT diuji, di antaranya indobenchmark/indobert-base-p1 dengan akurasi 76,34%, yang menunjukkan kinerja unggul dibandingkan model lainnya seperti indobertweet-base-uncased 55,82% dan indobert-base-uncased 43,31%. Metode Simple Additive Weighting (SAW) digunakan untuk membobotkan serta menganalisis sentimen, sehingga memungkinkan pemeringkatan kategori konten berdasarkan tanggapan pengguna. Hasil analisis menunjukkan bahwa unggahan Daily Share memperoleh respons positif paling tinggi, yang menunjukkan ketertarikan audiens pada konten yang bersifat personal. Sebaliknya, Giveaway memiliki tingkat keterlibatan terendah. Hasil ini memberikan masukan kepada cosplayer agar lebih fokus pada konten yang menarik minat positif dan relevan bagi audiens. Dengan wawasan ini, cosplayer dapat merancang strategi konten dan interaksi yang lebih efektif untuk meningkatkan engagement dan reputasi mereka di media sosial.
Pengembangan aplikasi manajemen stok UMKM rumah makan lesehan Bu Yus Lewenusa, Irvan; Afrial, Farhan; Handhayani, Teny
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i1.28372

Abstract

AbstrakUsaha Mikro Kecil dan Menengah (UMKM) merupakan salah satu usaha mikro yang memberdayakan industri rumahan. UMKM Indonesia memiliki kontribusi sebesar 15.8% terhadap rantai pasok produksi global di tingkat ASEAN. Rumah makan Lesehan Bu Yus merupakan rumah makan yang menjual berbagai jenis makanan. Penjualan rumah makan Lesehan Bu Yus di lakukan secara langsung di rumah makan maupun dengan menerima pesanan melalui platform online. Rumah makan ini mengalami kendala dalam pengelolaan stok bahan baku yang masih dilakukan secara manual, sehingga sering terjadi ketidakakuratan data stok. Tujuan kegiatan Pengabdian Kepada Masyarakat (PKM) ini adalah untuk membatu meningkatkan dan mengembangkan UMKM khususnya rumah makan Lesehan Bu Yus yang berlokasi di Jl. Taman Krakatau No. 25 Kabupaten Serang Banten. Metode yang digunakan dalam kegiatan PKM ini meliputi beberapa tahap mengikuti Software Development Life Cycle (SDLC) Agile Scrumn yaitu analisis kebutuhan, perancangan sistem, pengembangan sistem pengujian dan implementasi serta evaluasi. dengan memanfaatkan teknologi informasi mengembangkan sebuah aplikasi Inventory Management Stock (IMS) berbasis web yang dirancang khusus untuk membantu mengelola stok menggunakan metode Economic Order Quantity (EOQ) dan Safety Stock. Hasil dari kegiatan ini menunjukkan bahwa pemanfaatan teknologi informasi dalam pengelolaan stok bahan baku  dapat meningkatkan efisiensi operasional Rumah makan Lesehan Bu Yus, mengoptimalkan biaya pengadaan bahan baku, serta memberikan kontribusi positif dalam pengembangan UMKM melalui penerapan sistem manajemen stok berbasis web. Kata kunci: economic order quantity; inventory management; UMKM; pengabdian masyarakat; safety stock Abstract Micro, Small, and Medium Enterprises (MSMEs) are one of the micro enterprises that empower home industries. Indonesian MSMEs contribute 15.8% to the global production supply chain at the ASEAN level. Lesehan Bu Yus restaurant is a restaurant that sells various types of food. The sales at Lesehan Bu Yus restaurant are conducted directly at the restaurant as well as by receiving orders through online platforms. This restaurant faces challenges in managing raw material stock, which is still done manually, leading to frequent inaccuracies in stock data. The objective of this Community Service (PKM) activity is to help improve and develop MSMEs, specifically the Lesehan Bu Yus restaurant located at Jl. Taman Krakatau No. 25, Serang Regency, Banten. The method used in this community service activity includes several stages following the Software Development Life Cycle (SDLC) Agile Scrum, namely requirement analysis, system design, system development, testing, implementation, and evaluation. by utilizing information technology to develop a web-based Inventory Management Stock (IMS) application specifically designed to help manage stock using the Economic Order Quantity (EOQ) and Safety Stock methods. The results of this activity show that the use of information technology in managing raw material stock can improve the operational efficiency of Rumah Makan Lesehan Bu Yus, optimize the procurement costs of raw materials, and provide a positive contribution to the development of SMEs through the implementation of a web-based stock management system. Keywords: economic order quantity; inventory management; MSMEs; community service; safety stock
Clustering Data Meteorologi di Pulau Kalimantan Menggunakan Algoritma K-Means Kusuma, Jordi Pradipta; Lewenusa, Irvan; Handhayani, Teny
Eksplora Informatika Vol 14 No 2 (2025): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i2.1131

Abstract

Kalimantan merupakan salah satu pulau yang ada di wilayah Indonesia. Clustering data meteorologi pulau Kalimantan bertujuan untuk mengelompokkan kota-kota di wilayah tersebut guna mempelajari pertanda perubahan iklim. Artikel ini menggunakan data meteorologi time series harian dari 17 kota periode 1 Januari 2012 sampai 31 Juli 2023. Data dikumpulkan dari dari 17 kota yang tersebar di Pulau Kalimantan meliputi variabel temperatur minimum, temperatur maksimum, temperatur rata-rata, dan kecepatan angin rata-rata. Clustering dilakukan menggunakan metode K-Means dan K-Medoid. Metode Silhouette dan Davied Bouldin Index digunakan untuk memilih jumlah cluster optimal. Berdasarkan hasil evaluasi, metode K-Means mengungguli kinerja metode K-Medoid. Hasil eksperimen dengan menggunakan algoritma K-Means memperoleh jumlah cluster terbaik yaitu dua cluster dengan nilai Silhouette dan Davies Bouldin Index masing-masing sebesar 0.139 dan 1.923. Hasil clustering menggunakan metode K-Means memperoleh hasil kota Pontianak, Palangkaraya, Sambas, Ketapang, Sintang, Kapuas Hulu, Melawi, Kuburaya, Kotawaringin Barat, Kotawaringin Timur, Barito Selatan, dan Berau berada di Cluster 1. Tarakan, Balikpapan, Banjarmasin, Samarinda, dan Nunukan berada di Cluster 2. Trend tahunan variabel temperatur minimum di kota-kota cluster 1 mengalami kenaikan. Secara umum, tren tahunan menunjukkan bahwa kecepatan angin rata-rata dari tahun 2012 – 2023 mengalami penurunan. Kenaikan temperatur dan penurunan kecepatan angin menjadi tanda adanya perubahan iklim.
An Analysis of Meteorological Data in Sumatra and Nearby using Agglomerative Clustering Handhayani, Teny; Lewenusa, Irvan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5663

Abstract

Sumatra is one of the biggest and the second most crowded islands in Indonesia. Sumatra is also a place of abundance of tropical flora and fauna. This paper aims to cluster the cities in Sumatra and nearby based on the meteorology data. It implements Agglomerative hierarchical clustering and uses a daily time series dataset from 17 cities from 1 January 2010 to 31 December 2023. The dataset contains variables minimum temperature, maximum temperature, average temperature, humidity, sunshine duration, and average wind speed. The preprocessing data was dedicated to managing the missing values and data aggregation to create single-form data. The single-form data contains cities and meteorological variables used as an input for the clustering algorithm, i.e. K-Means, Fuzzy C-Means, K-Medoid, intelligent K-KMeans, and Agglomerative clustering. The Agglomerative clustering outperforms other methods (i.e. K-Means, Fuzzy C-Means, K-Medoid, and intelligent K-KMeans) and produces Silhouette scores of 0.11. The clusters are then analyzed to find their unique pattern. The cut-off when the number cluster is two, Agglomerative hierarchical clustering gathers Aceh, Sabang, Pekanbaru, Padang, and Padang Lawas in Cluster 1. Other cities, i.e., Nagan Raya, Batam, Jambi, Bandar Lampung, Medan, Pangkalpinang, Palembang, Bengkulu, Belitung, Tapanuli, Deli Serdang, and Nias are in Cluster 2. The results can be briefly explained that the characteristic of Cluster 1 has a higher average temperature, lower humidity, and lower sunshine duration than cities in Cluster 2. However, Cluster 1 has a lower average minimum temperature than Cluster 2. The pairs of cities which have the most similarities are (Aceh, Sabang), (Pekanbaru, Padang Lawas), (Nagan Raya, Nias), (Jambi, Palembang), (Bengkulu, Tapanuli), and (Medan, Deli Serdang). The annual trend in several cities shows that there exists an increasing trend in minimum temperature, rising sunshine duration, and decreasing wind speed. These are signs of climate change that need a proper handling.
Meningkatkan Efektivitas Penilaian Karyawan Di Bawaslu Jakarta Barat Dengan Sistem Pendukung Keputusan Berbasis Analytical Hierarchy Process Wulandari, Lita Eka; Sutrisno , Tri; Lewenusa, Irvan
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3099

Abstract

Employees are an important resource in a company or agency, including the West Jakarta City Bawaslu, which routinely assesses the performance of its employees. This assessment is often time consuming and prone to human error, given that the process is still carried out manually. For this reason, this research aims to design a web-based Decision Support System (SPK) using the Analytical Hierarchy Process (AHP) method that can assist Bawaslu in determining the best employees more efficiently and accurately. The AHP method is used because it is able to break down complex problems into simpler and more structured ones, and provides a measurement scale that can be used to determine priorities in selecting the best employees. Research data was collected through interviews with the leadership of the West Jakarta Bawaslu and literature studies related to the AHP method. The results of this study are expected to facilitate decision making in selecting the best employees and improve the efficiency of the performance appraisal process at the West Jakarta Bawaslu.
Chatbot Interaktif Berbasis Transformer untuk Penyediaan Informasi Dinamis di Industri Esports Calvin, Calvin; Mawardi, Viny Christanti; Lewenusa, Irvan
Comit: Communication, Information and Technology Journal Vol. 3 No. 2 (2025): Comit: Communication and Information Journal
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/comit.v3i2.8906

Abstract

The esports industry is experiencing rapid growth and has given rise to the need for an information system that is able to present news quickly and relevantly. This study develops an interactive chatbot based on the BART (Bidirectional and Auto-Regressive Transformers) model to answer user questions directly based on information collected through web scraping. The system is designed using Python and Flask, and uses MongoDB as data storage. Evaluation is carried out through F1-Score and Conversation-Based Evaluation to assess system performance in terms of relevance, coherence, and fluency of answers. The results show that the chatbot is able to provide accurate and coherent answers with fast response times, although there are still challenges in terms of recall and understanding ambiguous contexts.
Perencanaan Sistem Informasi Web Pemesanan Toko Niko Elektrik Mendita, Gaizka; Sutrisno, Tri; Lewenusa, Irvan
Jurnal Pendidikan, Sains Dan Teknologi Vol. 4 No. 3 (2025): Juli-September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jpst.v4i3.3096

Abstract

The advancement of information technology has had a significant impact on the business sector, especially in the growth of e-commerce, which provides opportunities for SMEs to increase sales and expand their market reach. Niko Electric Store, founded in 2003 in Jakarta, is one of the SMEs that have adapted to this trend by transitioning to an e-commerce platform to remain competitive. This research focuses on the development of the Niko Electric Store e-commerce website using the System Development Life Cycle (SDLC) methodology, which includes the planning, analysis, design, development, and testing phases. The website is designed to facilitate customers in accessing products such as LED lights, cables, and power outlets, and offers features such as online shopping, a secure payment system, and responsive customer service. Additionally, promotional campaigns and attractive offers are also integrated to enhance user engagement. This development aims to expand market reach, improve operational efficiency, and simplify customer transactions. By utilizing a structured SDLC approach, this project ensures the quality of the website and user satisfaction. This digital transformation is expected to help Niko Electric Store remain competitive, better meet customer needs, and drive sustainable business growth in the digital era.
Clustering Data Meteorologi di Pulau Kalimantan Menggunakan Algoritma K-Means Kusuma, Jordi Pradipta; Lewenusa, Irvan; Handhayani, Teny
Eksplora Informatika Vol 14 No 2 (2025): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i2.1131

Abstract

Kalimantan merupakan salah satu pulau yang ada di wilayah Indonesia. Clustering data meteorologi pulau Kalimantan bertujuan untuk mengelompokkan kota-kota di wilayah tersebut guna mempelajari pertanda perubahan iklim. Artikel ini menggunakan data meteorologi time series harian dari 17 kota periode 1 Januari 2012 sampai 31 Juli 2023. Data dikumpulkan dari dari 17 kota yang tersebar di Pulau Kalimantan meliputi variabel temperatur minimum, temperatur maksimum, temperatur rata-rata, dan kecepatan angin rata-rata. Clustering dilakukan menggunakan metode K-Means dan K-Medoid. Metode Silhouette dan Davied Bouldin Index digunakan untuk memilih jumlah cluster optimal. Berdasarkan hasil evaluasi, metode K-Means mengungguli kinerja metode K-Medoid. Hasil eksperimen dengan menggunakan algoritma K-Means memperoleh jumlah cluster terbaik yaitu dua cluster dengan nilai Silhouette dan Davies Bouldin Index masing-masing sebesar 0.139 dan 1.923. Hasil clustering menggunakan metode K-Means memperoleh hasil kota Pontianak, Palangkaraya, Sambas, Ketapang, Sintang, Kapuas Hulu, Melawi, Kuburaya, Kotawaringin Barat, Kotawaringin Timur, Barito Selatan, dan Berau berada di Cluster 1. Tarakan, Balikpapan, Banjarmasin, Samarinda, dan Nunukan berada di Cluster 2. Trend tahunan variabel temperatur minimum di kota-kota cluster 1 mengalami kenaikan. Secara umum, tren tahunan menunjukkan bahwa kecepatan angin rata-rata dari tahun 2012 – 2023 mengalami penurunan. Kenaikan temperatur dan penurunan kecepatan angin menjadi tanda adanya perubahan iklim.
Co-Authors Afrial, Farhan Budiyantara, Agus Calvin Calvin Cecillia Chung Kusuma, Jordi Pradipta Leonardo Lestari, Lutfiana Sinta Mario, Eric Mendita, Gaizka Sagaro, Ariya Siahaan, William Abram Hatigoran Sutrisno , Tri Teny Handhayani TRI SUTRISNO Viny Christanti M Wulandari, Lita Eka Yoewono, Gregorius Farrel Zyad Rusdi