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All Journal TEKNOLOGI INFORMASI Jurnal EECCIS JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Indonesian Journal of Applied Informatics Antivirus : Jurnal Ilmiah Teknik Informatika Industri Inovatif : Jurnal Teknik Industri Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Bumigora Information Technology (BITe) SKANIKA: Sistem Komputer dan Teknik Informatika Darmabakti : Junal Pengabdian dan Pemberdayaan Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) JASTEN (Jurnal Aplikasi Sains Teknologi Nasional
Suryo Adi Wibowo
Institut Teknologi Nasional Malang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Physics Transportation Other

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SIG DENGAN K-MEANS++ UNTUK KLASTERISASI PENGEMBANGAN UMKM KAIN TENUN (STUDI KASUS: KABUPATEN NAGEKEO) Wulang, Maria Yasinta; Wibowo, Suryo Adi; Susanto, Eko Heri
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 9 No 1 (2026): Jurnal SKANIKA Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v9i1.3630

Abstract

The woven cloth Small and Medium Enterprises (SMEs) in Nagekeo Regency possess significant economic and cultural potential; however, the current coaching process is executed uniformly without data-driven analysis, resulting in inefficient allocation of aid. This study aims to map the distribution of woven cloth SMEs, develop a web-based Geographic Information System (GIS) application, and implement the K-Means++ method to cluster the SMEs based on their productivity levels. The system was designed using Laravel and Leaflet.js, incorporating features for data management, interactive maps, and visualization of productivity clusters, which include Medium Productivity (PM), Low Productivity (PR), and Dense/Massive Productivity (PP). The research findings indicate that the system's clustering process achieved 100% accuracy compared to manual calculation using Excel, with a 0% error rate. A lift ratio of 7.69 (>1) signifies a strong relationship between variables and validates the clustering results. The algorithm's computation time was recorded at 0.464 seconds. Black-box and browser compatibility tests confirmed that all features functioned as intended across Chrome, Edge, and Firefox. Furthermore, user testing involving 10 respondents yielded a positive assessment, with percentages of 43% Strongly Agree, 41% Agree, 14.5% Neutral, and 1.5% Disagree. This system is capable of supporting more effective and objective spatial data-driven decision-making
Implementasi Peramalan Penjualan Nasi Kotak Este Catering Berbasis Web dengan Metode Double Exponential Smoothing In'am, Ludytio Akhsanul; Irawan, Joseph Dedy; Wibowo, Suryo Adi
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 1 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i1.95162

Abstract

Abstrak:Penelitian ini bertujuan untuk menghadirkan solusi teknologi informasi yang inovatif dalam bentuk peramalan penjualan nasi kotak eSTe Catering dengan menggunakan metode Double Exponential Smoothing berbasis website, guna meningkatkan efisiensi dan efektivitas dalam melakukan peramalan penjualan pada usaha eSTe Catering. Diharapkan melalui penelitian ini, penjualan lebih terukur dan pemilik usaha mudah untuk memonitoring penjualan dalam usaha catering nasi kotaknya. Melalui metode Double Exponential Smoothing, peramalan penjualan nasi kotak dilakukan perhitngan peramalan dalam perbulan, yang membantu meningkatkan efektivitas penjualan. Pengujian menggunakan metode blackbox menunjukkan bahwa sistem berfungsi sesuai ekspektasi dan dapat diandalkan dalam meminimalisir error serta meningkatkan kualitas peramalan. Hasil penelitian ini menunjukkan bahwa aplikasi berbasis web ini efektif dalam mendukung peramalan nasi kotak dan disarankan untuk dikembangkan lebih lanjut menjadi aplikasi berbasis mobile untuk meningkatkan fleksibilitas, aksesibilitas dan efisiensi.===================================================Abstract:This research aims to present innovative information technology solutions in the form of forecasting sales of eSTe Catering boxed rice using the website-based Double Exponential Smoothing method, in order to increase efficiency and effectiveness in forecasting sales at eSTe Catering business. It is hoped that through this research, sales are more measurable and business owners are easy to monitor sales in their boxed rice catering business. Through the Double Exponential Smoothing method, forecasting of boxed rice sales is done monthly, which helps increase sales effectiveness. Testing using the blackbox method shows that the system functions as expected and is reliable in minimizing errors and improving forecasting quality. The results of this study indicate that this web-based application is effective in supporting the forecasting of boxed rice and it is recommended to be further developed into a mobile-based application to improve flexibility, accessibility and efficiency.
Sistem Peramalan Penjualan Laptop Menggunakan Metode Weighted Moving Average (Studi Kasus Toko Markas Laptop) Surya, Bagas Anardi; Mahmudi, Ali; Wibowo, Suryo Adi
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.95711

Abstract

Abstrak : Penelitian ini bertujuan untuk mengembangkan sebuah solusi teknologi informasi inovatif berupa sistem peramalan penjualan Laptop pada Toko Markas Laptop dengan menggunakan metode Weighted Moving Average berbasis website, sistem ini dirancang untuk meningkatkan efisiensi dan efektivitas proses peramalan penjualan, sehingga pemilik usaha dapat memantau penjualan dengan lebih mudah dan akurat. Melalui penerapan metode weighted moving average, peramalan penjualan dilakukan dengan memberikan bobot yang lebih besar pada data penjualan terbaru, sehingga hasil prediksi menjadi lebih sensitif terhadap tren terbaru yang diharapkan mampu mendukung pengelolaan usaha. Hasil penelitian ini menunjukkan bahwa aplikasi berbasis web ini memiliki Tingkat akurasi baik karena memiliki nilai Mean Absolute Percentage Error (MAPE) sebesar 28%, menunjukkan bahwa metode Weighted Moving Average dapat memberikan prediksi yang cukup andal untuk membantu pengambilan keputusan strategis terkait pengelolaan stok dan perencanaan penjualan.===================================================Abstract :This study aims to develop an innovative information technology solution in the form of a Laptop sales forecasting system at the Laptop Markas Shop using the website-based Weighted Moving Average method, this system is designed to improve the efficiency and effectiveness of the sales forecasting process, so that business owners can monitor sales more easily and accurately. Through the application of the weighted moving average method, sales forecasting is carried out by giving greater weight to the latest sales data, so that the prediction results become more sensitive to the latest trends which are expected to support business management. The results of this study show that this web-based application has a good level of accuracy because it has a Mean Absolute Percentage Error (MAPE) value of 28%, indicating that the Weighted Moving Average method can provide predictions that are reliable enough to help make strategic decisions related to stock management and sales planning.
Pengembangan Chatbot Penyakit Ringan Menggunakan Metode Long Short-Term Memory Mahardika, Esa Arya; Mahmudi, Ali; Wibowo, Suryo Adi
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.95564

Abstract

Abstrak : Penyakit merupakan salah satu masalah bagi manusia baik penyakit ringan lebih-lebih penyakit kronis. Manusia telah mempelajari tentang bagaimana menangani permasalahan penyakit dari zaman ke-zaman demi kesejahteraan manusia. Seiring waktu populasi manusia bertambah dan penyakit semakin banyak baik yang dapat diobati maupun tidak sehingga manusia membangun fasilitas-fasilitas kesehatan. Tujuan penelitian ini supaya dapat memaksimalkan pelayanan IKS An-Nur II di luar jam kerja dokter. Penulis menggunakan AI Project Cycle untuk proses pembuatan chatbot, menggunakan pendekatan Natural Language Processing untuk interaksi dengan pengguna, dan algoritma Long Short-Term Memory untuk membuat model dengan melibatkan pengembangan melalui framework Flask. Hasil evaluasi menunjukkan bahwa model yang dihasilkan memiliki nilai training loss sebesar 12,35%, yang mengindikasikan tingkat error yang rendah pada data pelatihan, serta training accuracy sebesar 100%, menandakan model telah belajar pola data pelatihan dengan sangat baik. Pada data validasi, model mencapai validation loss sebesar 42,44% dan validation accuracy sebesar 94,44%. Nilai validation accuracy yang tinggi menunjukkan kemampuan model dalam menghasilkan respons yang relevan terhadap data baru. Hasil akurasi yang tinggi menjadikan chatbot mampu menjawab pertanyaan dengan akurasi cukup baik.====================================================Abstract :Disease is one of the problems for humans, whether it is a mild disease or a chronic disease. Humans have learned about how to deal with disease problems from time to time for the sake of human welfare. Over time the human population increases and more and more diseases both treatable and not so humans build health facilities. The purpose of this research is to maximize the services of IKS An-Nur II outside of doctor's working hours. The author uses the AI Project Cycle for the chatbot creation process, using the Natural Language Processing approach for interaction with users, and the Long Short-Term Memory algorithm to create models by involving development through the Flask framework. The evaluation results show that the resulting model has a training loss of 12.35%, indicating a low error rate in the training data, and a training accuracy of 100%, indicating that the model has learned the training data patterns very well. On the validation data, the model achieved a validation loss of 42.44% and a validation accuracy of 94.44%. High validation accuracy scores indicate the model's ability to generate relevant responses to new data. The high accuracy results make the chatbot capable of answering user questions with high accuracy.
Co-Authors Ababil, Oliver Januardi Abdul Wahid Achmad Fauzi Adi Prasetyo, Guntur Adi Saputra, Yoga Aeni Fahila, Nur Agung Panji Sasmito Ahmad Fahrudi Setiawan AHMAD FAISOL Airi Mundzilin, Difania Aktafi, Billah Alfina, Alfina Ali Mahmudi Andriano Frans, Jemmy Anshor Taufikurrahman, Muhammad ARI, DANIEL Ariwibisono, Ariwibisono Ariwibisono, F.X Arjunastya Miftaharif, Rayhan Armedianto Putro, Bima Aulia, Lalu Muhammad Fatwa Ayutantri, Dik Ajeng Benjamin Maahury, David Budi Raharjo, Piter cahya ardi wahana, zakiey Cahya Kusuma, Firdaus Dwi Deddy Rudhistiar Deswandi Yahya, Raflizar Dibrayogasta, Nandaka Dwi Lukas Saputro, Ardana Dwi Sasmita, Sudrajad Dyah Agustin, Praditasari Dzulhijjah, Dwi Ahmad Erwinda, Gesha Warilotte Fadly, Erviansyah Fahrul Taufiqurrohman, Achmat Farabi Phasa, Fianda Febriana Santi Wahyuni Febrianti, Fitri Fikar Mu'afi, Arya Firdanu, Rizha Garinanto, Budi Guntur Adi Prasetyo Hani Zulfia Zahro Hernoko, Marvelina Gracia Ilham Ali, Muhammad In'am, Ludytio Akhsanul Irma Sari, Ramandani Joas, Kirene Wardaini Joseph Dedy Irawan Joyo Sentoso, Lukas Kalimatullah, Moh. Teguh Karina Auliasari kartiko Kartiko Ardi Widodo Kharisma, Dandy Kurnia Sella, Fernanda Kurniawan, William Lalo Nusa, Faustino M. Julius Maarif, Shohibul Mahardika, Esa Arya Mahdi, Moh Maulidin Mahesa Ramadhan, Deo Manusiwa, Mizaell Mira Orisa Misbachul Munir, Muhammat Moh. Miftakhur Rokhman Moh. Miftakhur Rokhman, Moh. Miftakhur Mucthar, Firmanda Muttakin, Muhammad Yoga Adliyani Nelly Budiharti Nurlaily Vendyansyah Ompusunggu, Andry Pambudi, Yitno Prameswara P., Renaldi Pranata, Krish Prasetiyo, Agung Sugih Prasetyo, Sony Prastya Bayu Pasifik, Rizka Pratama Irianto, Mario Pratama, Irgi Yoga Pratama, Wahyu Tedy Priga Putra, Angga Pratama Primaswara P, Renaldi Primaswara P., Renaldi Putra Snyders, Saveraga Qulub, Hizbul Rachmad Agung Laksono Raden Mohamad Herdian Bhakti Renaldi Primaswara Prasetya Renaldi, Bima Reynaldi Prayoga, Thomas Rismayanti, Sintiya Riyan Wicaksono Riziq Gyfari, Aghisna Rizka Fitriandra, Zeylla Rohman, Moh Miftakhur Roy Mahendra Pedro Pratama Safitra, Wahyu Saiqul Umam, Muhamad Sakrani, Fikriadi Satwikayana, Sujud Sentot Achmadi Setyo Aji, Bayu Sholihin, Mukhlis Sonny Prasetio Sonny Prasetio, Sonny Surya, Bagas Anardi susanto, eko heri Tejasukmana Putra, Rehadian Vito Eka Perdana Putra, Alfonsus Wahyudi, Desvianty Ayu Wijono Wijono Wulang, Maria Yasinta Xaverius Ariwibisono, Franciscus Xaverius Ariwibisono, Fransiscus Yoga Tama, Prastyo Yogi Ainur Rofiq Anggara Yosep Agus Pranoto Yuris Wijayanto, Fajar Zahro, Hani Zulfia Zidan Rusminto, Muhammad Zidan, Rifqi Zulfia Zahro’ , Hani Zulfia Zahro’, Hani