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Pembuatan Sistem Prediksi Penjualan Dan Persediaan Barang Menggunakan Metode Double Exponential Smoothing Dan Economic Order Quantity (EOQ) : (Studi Kasus : Bengkel Ivan Jaya Motor) Octaviani, Vincentia Indri; Maulana, Hendra; Sihananto, Andreas Nugroho
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 2 No 2 (2023): JUSIFOR - DESEMBER 2023
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/jusifor.v2i2.3407

Abstract

Bengkel Ivan Jaya Motor adalah sebuah bisnis yang bergerak di bidang otomotif. Selain menawarkan jasa service mobil, Ivan Jaya Motor juga menjual berbagai merk oli serta sparepart mobil. Namun dalam menjalankan bisnisnya, Bengkel Ivan Jaya Motor melakukan segala aktivitas operasinya masih menggunakan cara manual. Termasuk dalam melakukan proses penjualan maupun pengelolaan persediaan barang. Untuk mengatasi permasalahan yang dihadapi, Bengkel Ivan Jaya Motor membutuhkan sebuah sistem prediksi penjualan dan persediaan barang. Sistem yang dibuat berbasis web dan menggunakan metode prediksi double exponential smoothing Brown dengan nilai alpha α = 0,1. Yang mana menghasilkan nilai kesalahan prediksi terendah berdasarkan perhitungan MAPE (Mean Absolute Percentage Error), yaitu 12,53508%. Ini berarti karena berada pada interval 10% hingga 20% maka termasuk dalam peramalan yang baik, sedangkan untuk memprediksi persediaan secara optimal digunakan metode Economic Order Quantity (EOQ)
Implementasi Metode Fuzzy Time Series Pada Pengembangan Sistem Informasi Penjualan Pada Segoku Catering Surabaya Suryandari, Sabrina Heryanti; Prami, Made Hanindia; Sihananto, Andreas Nugroho
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 2 No 2 (2023): JUSIFOR - DESEMBER 2023
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/jusifor.v2i2.3415

Abstract

Perkembangan organisasi, bisnis, dan industri, termasuk industri katering, dapat dicapai dengan lebih cepat dan mudah dengan penggunaan teknologi komputer yang mencakup pengolahan data. Katering, juga disebut sebagai jasa boga adalah bisnis yang melayani pemesanan berbagai macam makanan untuk pesta maupun untuk kebutuhan perusahaan. Segoku Catering Surabaya adalah perusahaan katering yang data penjualan dan pendapatan dimasukkan secara manual dalam buku arsip, yang memakan waktu dan menyulitkan perhitungan laba dan rugi. Jadi, penelitian ini bertujuan untuk membantu pemilik catering membuat laporan pendapatan bulanan. Sistem juga dapat melakukan peramalan laba bulanan untuk mengetahui laba rugi setiap bulan. Sistem dapat melakukan peramalan penjualan untuk mengetahui produk mana yang diminati oleh pembeli. Semua hal tersebut dilakukan dengan menggunakan metode seri waktu Fuzzy, yang terkenal memiliki tingkat akurasi yang tinggi dalam peramalan jangka pendek, juga menggunakan perhitungan rata-rata kesalahan untuk peramalan jangka panjang. Hasilnya, sistem dapat digunakan untuk melihat data laba bulanan, dan data prediksi laba bulanan.
Perbandingan Performa Klasifikasi Citra Ikan Menggunakan Metode K-Nearest Neighbor (K-NN) Dan Convolutional Neural Network (CNN) Abdurrahman, Nizar; Rahmat, Basuki; Sihananto, Andreas Nugroho
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 2 No 2 (2023): JUSIFOR - DESEMBER 2023
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/jusifor.v2i2.3728

Abstract

Perairan daratan Indonesia memiliki keanekaragaman jenis ikan, mencakup variasi ikan air tawar, payau, dan laut. Meskipun Indonesia memiliki lebih dari 2.000 spesies ikan, hanya sekitar 25% yang dapat dibudidayakan. Beberapa jenis ikan seperti lele, mujair, bandeng, patin, dan gurami menjadi pilihan utama dalam budidaya ikan konsumsi. Dalam konteks ini, penelitian menggunakan teknologi citra digital untuk membandingkan dua metode klasifikasi, yaitu k-NN dan CNN, dengan fokus pada citra ikan. Metode k-NN dan CNN diuji dengan menggunakan dua skenario pembagian dataset, yaitu 80:20 dan 90:10. Hasil eksperimen menunjukkan bahwa CNN menghasilkan akurasi yang lebih tinggi dibandingkan k-NN pada kedua skenario. Akurasi CNN mencapai 88% pada rasio data 80:20 dan 80% pada rasio 90:10, sedangkan k-NN mencapai 66% dan 72% pada skenario yang sama. Meskipun performa metode dapat dipengaruhi oleh berbagai faktor, hasil penelitian ini memberikan indikasi bahwa CNN lebih efektif dalam mengklasifikasikan citra ikan. Keunggulan ini dapat memberikan kontribusi penting dalam pemilihan metode klasifikasi untuk pengolahan citra ikan.
Testing posketanmu website with google penetration testing and OWASP Top 10 Sebrina, Aida Fitriya; Junaidi, Achmad; Sihananto, Andreas Nugroho
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5204

Abstract

Data integrity has become vital in the quickly evolving digital era, pushing cybersecurity to a critical concern. Securing cybersecurity is crucial for systems such as the Posketanmu website in Mojokerto Regency, as it is responsible for safeguarding sensitive personal information. The objective of this research is to detect, evaluate, and exploit on any security weaknesses present on the Posketanmu website. The methodology combines the Google Penetration Testing strategy with the latest OWASP Top 10 2021 criteria. The penetration testing procedure comprises five distinct steps: Initially, the process involves collecting data and comprehending the platform by utilizing several programs such as Nmap, Nslookup, Wappalizer, Whatweb, Whois, and Google Hacking. Furthermore, the process involves utilizing ZAP to do vulnerability scanning, resulting in the creation of thorough reports. Furthermore, doing a vulnerability assessment, which involves manual testing and classification according to OWASP standards. Furthermore, effectively capitalizing on all eleven identified vulnerabilities. Ultimately, the task involves adhering to the OWASP Top 10 2021 standards by documenting, reporting, and suggesting solutions for any identified issues. This investigation found and resolved four significant security vulnerabilities on the Posketanmu website: stored XSS, unset CSP header, unset Strict-Transport-Security header, and open redirect. The implementation of Google Penetration Testing and adherence to the OWASP Top 10 2021 criteria have greatly improved the security of the Posketanmu website, ensuring the protection of Mojokerto Regency citizens' data.
Implementasi YOLOv8 Pada Robot Deteksi Objek Rasjid, Azka Avicenna; Rahmat, Basuki; Sihananto, Andreas Nugroho
Journal of Technology and System Information Vol. 1 No. 3 (2024): July
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jtsi.v1i3.2969

Abstract

Pendeteksian objek merupakan salah satu tantangan utama dalam pengembangan robotika, khususnya untuk aplikasi yang membutuhkan identifikasi berbagai objek dalam lingkungan yang beragam. Penelitian ini ditujukan untuk implementasi YOLOv8 pada Robot Deteksi Objek. Metode penelitian mencakup pelatihan YOLOv8 menggunakan dataset yang terdiri dari 150 gambar untuk setiap kelas objek. Kinerja model dievaluasi berdasarkan metrik presisi (P), recall (R), mean Average Precision (mAP) pada threshold 50% (mAP50), dan mAP50-95. YOLOv8 bertujuan untuk mendeteksi objek dengan 7 sampel kelas objek yaitu: botol, kursi, manusia, pot, galon, tong sampah, dan ember. Hasil evaluasi menunjukkan bahwa model YOLOv8 memberikan kinerja yang sangat baik dengan presisi dan recall mendekati 1 untuk semua kelas objek. Secara khusus, kursi, manusia, dan tong sampah mencapai nilai P dan R sebesar 0.994 atau lebih, dengan mAP50-95 masing-masing sebesar 0.891, 0.874, dan 0.894. Botol dan ember juga menunjukkan hasil yang baik dengan mAP50-95 masing-masing sebesar 0.857 dan 0.905. Sementara itu, galon dan pot masing-masing memiliki mAP50-95 sebesar 0.908 dan 0.705.
Social Media Marketing Maintains Business Existence Wiwik Handayani; Andreas Nugroho Sihananto
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3312

Abstract

The purpose of a business is to show and maintain the company's existence in the long term. Efforts to maintain business continuity and existence in the competition are by adopting the latest technological developments. The development of the online business world, of course, impacts new differentiation to create and market a product of goods and services. The use of social media as a digital communication channel is every day among Indonesians. Social media is developing into the most popular communication media for now. Besides being used as a communication medium, social media is also used by business people to promote a product/service that is produced. In the current era, the use of social media has transformed into digital marketing tools and digital selling. This article aims to understand the relationship between social media marketing and maintaining a business's existence. The method used in this study is a literature review or literature review. Social media marketing is essential in overhauling business and communication through social media and networking, which is the fastest way to grow a business entity. In addition, social media marketing aims to increase product, brand, and even business awareness by using social websites, such as social networking, microblogging, and content sharing. The advantage of the development of social media-based information technology is that it helps business people achieve goals and maintain business existence in the era of industry 4.0. Social media can also grow the company's reputation in the long term and increase customer loyalty to the company. The study of social media marketing is significant because it maintains the company's sustainable growth.
E-commerce Web-Based Application for Excellent Service Agency (ESA) Hospitality Training Center, Malang Ratna Yulistiani; Andreas Nugroho Sihananto; Kartini; M. Arif Mardhavi; Edi Sugiyanto; Muhammad Afifudin
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3333

Abstract

Excellent Service Agency (ESA) is a hospitality industry training center located in Malang City, East Java, Indonesia. This training center provides decent training for people who want to work in the hospitality industries such as hotels and restaurants. The one which makes a difference between ESA and its competitors is their commitment to providing training that is equivalent to other hospitality industry training institutions but at very affordable costs and they always channel students directly into the workplace market until their students land their first job. However, until now, ESA does not have an official website or e-commerce website to offer its services, so the ESA’s brand usually is only known by word of mouth. This ESA e-commerce website was developed with the CodeIgniter framework and MySQL Maria DB 5.0 database. The result is a company profile website that doubles as an e-commerce web ready to be used for ESA branding and marketing purposes.
Classification of Covid-19 RT-PCR Test Results Using Auto-encoder And Random Forest Andreas Nugroho Sihananto; Eristya Maya Safitri; Arif Widiasan Subagio; Muhammad Dafa Ardiansyah; Aditya Primayudha
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3338

Abstract

Corona Virus Disease (COVID-19) is a new type of virus that emerged at the end of 2019. COVID-19 has become a pandemic due to the increase in the number of cases taking place very quickly and has spread to all corners of the world. The World Health Organization (WHO) recommends the use of the Reverse Transcription-Polymerase Chain Reaction (RT-PCR) method as a way to test the diagnosis of COVID-19 infection. This study builds a classification system for the COVID-19 RT-PCR test results by applying the Auto-encoder algorithm and the Random Forest classification. The dataset used is the result of the RT-PCR test from one of the hospitals in Brazil. The method used is the Auto-encoder to process the dataset features first and the Random Forest algorithm to classify the RT-PCR test results that have positive and negative labels. From this process, it can be seen that the Auto-encoder model can process datasets well and the classification carried out using Random Forest can classify with an accuracy of 87.2%.
Application of Google Data Studio for Data Visualization at SMK Tunas Bangsa Malang Trimono; Andreas Nugroho Sihananto; Muhammad Muharrom Al Haromainy; Edi Sugiyanto; Farkhan
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.33107

Abstract

The Department of Office Automation and Governance (OTKP) is one of the Vocational High School’s majors in Indonesia that focuses on office operations and information processing. One of the popular skill in information processing lately is data processing and visualization. In response of this trend, we propose a Google Data Studio training for Tunas Bangsa Vocational High School’s students from OTKP Majors. Google Data Studio is a free data analysis tool from Google. With this tool, users can not only display data with attractive and easy-to-understand visuals but also can process data from various sources on one worksheet. This service is mostly free, not limited to Google services such as Google Sheets but can be linked to other platforms, such as websites, applications or third party services. By the end of the training all participants have been able to use Google Data Studio for data visualization needed for offices in general.
Wayang’s Images Recognition using Vision Transformer Sihananto, Andreas Nugroho; Al Haromainy , Muhammad Muharrom; Fauzi, Zaky Ahmad; Reza, Reno Alfa; Putra, Gredy Christian Hendrawan; Christianty, Theressa Marry
IJDASEA (International Journal of Data Science, Engineering, and Analytics) Vol. 4 No. 2 (2024): International Journal of Data Science, Engineering, and Analytics Vol 4, No 2,
Publisher : Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijdasea.v4i2.24

Abstract

Due to its complex nature and outdated perception, Wayang is a traditional Indonesian art form influenced by Hindu-Buddhism. However, it is difficult for the younger generation to recognize the various types of Wayang. In an effort to preserve Wayang culture, this study evaluates the performance of four deep learning models in recognizing types of Wayang namely, Vision Transformer (ViT), ResNet34, YOLOv5-cls, and YOLOv8-cls. These models were trained and assessed using a dataset of 232 images representing six Wayang types and using matrix such as accuracy, recall, precision, and F1 score. ViT demonstrated efficiency and adaptability despite high computational requirements, achieving the best accuracy (91.3%), showing high adaptability despite substantial computational requirements. Meanwhile, YOLOv5-cls and YOLOv8-cls offered a good balance betwwen accuracy and efficiency. This study suggest that deep learning models can play an essentialrole in Wayang by enhancing recognition accessibility, thus helping younger generations appreciate this tradisional art form.
Co-Authors Abdul Rezha Efrat Najaf Abdurrahman, Nizar Achmad Junaidi Aditya Primayudha Aditya Rizqi Ardhana Afifudin, Muhammad Afriani, Regita Agung Mustika Rizki, Agung Mustika Agussalim, Agussalim Alifah, Nurul Aini Amalia, Nadhia Rizqy Amri Muhaimin Anggraini PS Anggraini Puspita Sari Ani Dijah, Rahajoe Ar Romandhon, Mitzaqon Gholizhan Ardiansyah, Muhammad Dafa Arif Widiasan Subagio Basuki Rahmat Masdi Siduppa Christianty, Theressa Marry Dwi Arman Prasetya Edi Sugiyanto Edi Sugiyanto Eristya Maya Safitri Fakhruddin, Fikri Farkhan Fauzi, Zaky Ahmad Fetty Tri Anggraeny Gusti Ahmad Fanshuri Alfarisy, Gusti Ahmad Fanshuri Izzatul Fithriyah Kartini Kartini Kartini Lesmana, Benedictus Rafael M Shochibul Burhan, M Shochibul M. Arif Mardhavi M. Shochibul Burhan Mardhavi, Arif Marselina, Anif Fitria Dewi Maulana, Hendra Maulana, Yoga Mohammad, Farrel Adel Muhammad Afifudin Muhammad Dafa Ardiansyah Muhammad Muharrom Al Haromainy Naila, Amelia Maslaqun Nurhaliza, Risma Nurlaili, Afina Lina Octaviani, Vincentia Indri Pangestu, Arif Fajar Parlika, Rizky Pradana, Ilham Akbar Prami, Made Hanindia Putra, Chrystia Aji Putra, Gredy Christian Hendrawan Putra, Raditya Lungguk Satya Ramadhan, Dimas Dharu Rasjid, Azka Avicenna Ratna Yulistiani Retno Mumpuni Reza, Reno Alfa Safitri, Erista Maya Santosa, Mochammad Kevin Saputra, Dewa Raka Krisna Saputri, Asih Sebrina, Aida Fitriya Shahab, Muhammad Syaugi Suryandari, Sabrina Heryanti Taufiqurrahman, Rahmadany Fahreza Tirana Noor Fatyanosa, Tirana Noor Trianingsih, Arini Trimono, Trimono Wayan Firdaus Mahmudy Wiwik Handayani Yisti Vita Via Yudistira, Mochammad Ervinda Yulianto, Rusman