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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) JOIV : International Journal on Informatics Visualization JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Indonesian Journal of Business Intelligence (IJUBI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Information System Journal (INFOS) Journal Automation Computer Information System (JACIS) Abdiformatika: Jurnal Pengabdian Masyarakat Informatika The Indonesian Journal of Computer Science Research JURNAL MULTIDISIPLIN BHATARA
Sri Ngudi Wahyuni, Sri Ngudi
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing

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Implementasi Model Triple Exponential Smoothing Guna Memprediksi Persediaan Produk Berbasis Website Aufa Hanif, Mohammad; Wahyuni, Sri Ngudi
The Indonesian Journal of Computer Science Research Vol. 3 No. 1 (2024): January
Publisher : Hemispheres Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59095/ijcsr.v3i1.86

Abstract

Industri ritel yang terus berkembang dihadapkan pada tantangan signifikan dalam pengelolaan persediaan produk, yang dapat mempengaruhi kinerja bisnis secara keseluruhan. Keterlambatan penyediaan, kekurangan atau kelebihan stok, dan masalah operasional menjadi fokus utama yang membutuhkan solusi efektif. Dalam upaya menghadapi masalah pengelolaan persediaan, penelitian ini mengusulkan pengembangan aplikasi web dengan mengimplementasikan model Triple Exponential Smoothing (TES) guna memprediksi persediaan produk dengan akurat. Metode ini dipilih karena kemampuannya dalam menangani tren non-linier dan komponen musiman, yang sering kali menjadi aspek penting dalam data time-series industri ritel. Hasil model TES berhasil diterapkan untuk menganalisis pola penjualan menggunakan data dari Kaggle, terutama https://www.kaggle.com/datasets/samuelcortinhas/time-series-practice-dataset. Data sampel terbatas pada item nomor 0 dengan store id nomor 0 dari Januari 2010 hingga Desember 2018, membentuk dasar penelitian untuk memberikan analisis mendalam tentang efisiensi penggunaan TES dalam konteks manajemen persediaan. Proses implementasi melibatkan pemilihan parameter optimal (alpha=0.3, beta=0.02, dan gamma=0.3), yang diuji dan dievaluasi menggunakan metrik evaluasi seperti Mean Absolute Percentage Error (MAPE) dan Mean Squared Error (MSE). Hasil pengujian menunjukkan bahwa model TES mampu memberikan prediksi persediaan produk dengan akurat, dengan nilai MAPE sebesar 0.4413 dan MSE sebesar 28147.085. Pada proyeksi data juga menunjukkan kesesuaian yang kuat antara hasil prediksi dan data aktual, menegaskan bahwa model TES dapat mengantisipasi perubahan dan fluktuasi data. hasil ini menunjukkan potensi implementasi model TES dalam industri ritel untuk mencapai persediaan yang optimal dan mengoptimalkan alokasi anggaran. Secara keseluruhan, penelitian ini berhasil mengintegrasikan model TES sebagai alat prediksi penjualan dan memberikan pemangku kepentingan alat pengambilan keputusan yang lebih informasional dan efisien.
Inovasi Digital berbasis Video Dokumenter untuk Mempromosikan Kearifan Lokal Desa Budaya Seyegan Wahyuni, Sri Ngudi; Vijaya, Rosyidah Jayanti; Maemunah, Mei; Daniati, Erna
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 5 No. 2 (2025): November - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v5i2.263

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan mengembangkan video dokumenter sebagai alat promosi bagi Desa Budaya Seyegan. Hal ini disebabkan minimnya kunjungan wisatawan ke Desa Budaya Seyegan ini yang memiliki potensi budaya dan alam yang besar. Topik ini dipilih untuk meningkatkan kesadaran masyarakat dan daya tarik wisatawan, serta memperbaiki kondisi ekonomi lokal. Metode pengabdian masyarakat yang digunakan meliputi kolaborasi antara akademisi dan masyarakat lokal dalam mendokumentasikan tradisi, seni, dan kearifan lokal. Hasil penelitian menunjukkan bahwa video yang dihasilkan berhasil menarik perhatian, hal ini tebukti dengan jumlah viewer 25 view sealam 8 hari di kanal Youtube Pengabdi. Video dokumenter ini difungsikan untuk meningkatkan visibilitas desa, dan mendorong pelestarian budaya dan memperluas jangkauan promosi. Kesimpulannya, inisiatif ini tidak hanya berfungsi sebagai promosi tetapi juga sebagai arsip budaya yang penting, dengan rekomendasi untuk pelatihan pembuatan konten bagi masyarakat lokal guna mendukung pengembangan pariwisata yang berkelanjutan.
K-Means Algorithm Analysis for Election Cluster Prediction Wahyuni, Sri Ngudi; Khanom, Nazmun Nahar; Astuti, Yuli
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1107

Abstract

The general election is a democratic process that is carried out in every country whose system of government is presidential, including Indonesia, which conducts it every five years. In fact, some people abstain, leading to budget wasting and missing target. Thus, it is very important to identify clusters of general election districts and map the number of voters to map the budget for the upcoming election. This process needs prediction to help reduce budgeting risk as an early warning. Based on the latest election data taken from Margokaton, Yogyakarta, Indonesia, many people voted in 2021, but the number of abstainers is high. In this case, cluster prediction is important to identify the election participants in each area. The K-Means algorithm could also predict abstainer areas in election activities to facilitate early mitigation in drafting election budgeting. Therefore, this study aimed to identify the pattern of voters in the election using the K-means algorithm. The data parameters comprised the list of voters, Unused ballot papers, and the sum of abstainers. This study is important because it contributes to reducing the election budget of each area. The data obtained from the Indonesia Ministry of Internal Affairs official website in 2021 were processed using the RapidMiner tool. The results showed more than 11% of the non-voters in cluster 1, 16% in Cluster 2, and 8% in cluster 3. The evaluation of clusters value is 2.04, indicating that the clustering using K-means is suitable, as shown by the DBI value close to 0. The results indicate that testing the cluster optimization of the K-Means algorithm using DBI is highly recommended. Based on this prediction result, the government needs special attention to clusters with many abstainers to decrease the number of abstainers and prevent overbudgeting. These results indicate the need to review the election participant data in 2024. Furthermore, there is a need for continuous socialization and education about election activities to reduce the number of abstainers and prevent overbudgeting.
PERANCANGAN SISTEM PAKAR DIAGNOSA PENYAKIT GIGI MENGGUNAKAN ALGORITMA BAYES Wahyuni, Sri Ngudi; Garjita, Lila
Indonesian Journal of Business Intelligence (IJUBI) Vol 2 No 1 (2019): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v2i1.1020

Abstract

Dental disease is a health problem in Indonesia, many people complain aboutit. In 2013 Indonesia's basic health research that 25.9% of Indonesia'spopulation had dental and mouth problems. The public awareness to maintaindental and oral health is still low at around 13.1%. In addition, there is a lackof a number of dentists, causing the high cost of dental examinations. Theexpert system of Dental Disease Diagnosis System is a solution which can todetect symptoms of dental disease early before go to doctors.The Bayesalgorithm is one of methods which efisien to use in expert system fordeveloping it. The bayes algorithm is accurate to diagnose early dentaldiseases, by entering a diagnosis - an alternative probability value of thedisease and symptoms obtained from an expert.
PENDETEKSIAN MINAT DAN BAKAT MENGGUNAKAN METODE RIASEC Hidayat, Fiyan Kurnia; Wahyuni, Sri Ngudi
Indonesian Journal of Business Intelligence (IJUBI) Vol 2 No 1 (2019): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v2i1.1023

Abstract

The interests are very important to choosing a course and field of work. Good salary, good company is one of goal in our life. One of many way which we can do for choice and mapping it more early is interest detection for detect our school and faculty which suitable with our interest. One of interest detection method use is RIASEC. RIASEC is one method with use probability principles for compute and compare six elements in it. The expensive price for buying a psychology expert is reason for developing this systems. The system can access bay website and which easy way. It will be helping all people for detection their children interest and will can giving best education for them.
PENERAPAN SEARCH ENGINE OPTIMIZATION PADA WEBSITE KURSUS ONLINE ANAKKODING.ID Mulyatun, Sri Mulyatun; Budi, Galang Setia; Rahmawati, Dwi Rahmawati; Wahyuni, Sri Ngudi; Vijaya, Rosyidah Jayanti; Widyawati, Rahma Widyawati
Indonesian Journal of Business Intelligence (IJUBI) Vol 4 No 2 (2021): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v4i2.1952

Abstract

Promosi adalah hal terpenting pada sebuah bisnis. Anakcoding.id adalah salah satu bisnis dibidang pelatihan yang menekankan promosi berbasis digital, yaitu Search Engine Optimization atau SEO. Adapun tujuan penelitian ini adalah pemanfaatan SEO pada website Anakcoding.id agar pengguna google mudah menemukan website Anakcoding.id dengan memasukan kata kunci yang relevan. Adapun metode yang digunakan pada penelitian ini adalah On-Page dan Off-page dengan bantuan analisis keywords dari google keywords planner. Sehingga website anakkoding.id memiliki jangkauan yang luas seiring berjalannya waktu dapat meningkatkan jumlah pengunjung website dan meningkatkan  pemasaran dan pendapatan Anakcoding.id. pada pengembangan SEO ini, digunakan pengujian menggunakan alpha box dan black box test. Kesimpulan penelitian ini adalah metode SEO menggunakan teknik On-Page, Off-page serta Technical SEO sangat memudahkan dan menyempurnakan elemen-elemen website seperti Meta tag untul lebih mudah dibaca oleh search engine.
PENGEMBANGAN IKLAN LAYANAN MASYARAKAT ‘GUNAKAN SELALU MASKER’ MENGGUNAKAN ANIMASI 2D Suyatmi, Suyatmi Suyatmi; Maemunah, Mei Maemunah; Wahyuni, Sri Ngudi
Indonesian Journal of Business Intelligence (IJUBI) Vol 4 No 2 (2021): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v4i2.1953

Abstract

Iklan layanan masyarakat ini bertujuan mengedukasi masyarakat akan pentingnya penggunaan masker saat ini. Situasi pandemi COVID-19 seperti sekarang ini, penggunaan masker sangat penting untuk mengurangi penyebaran COVID-19. Pengembangan video animasi ini akan menjadi salah satu alat edukasi kepada masyarakat untuk turut mencegah penularan penyakit COVID-19 di Indonesia. Pengembangan video animasi ini dilakukan secara bertahap dengan menggunakan beberapa tools antara lain Adobe Photosop Adobe After Effects, Adobe Illustrator, dan Adobe Premiere. Adapun tahapan pengembangan melalui 3 tahap yaitu pra produksi, produksi dan pasca produksi. Pengujian vededo ini menggunakan beta testing dengan alat survey berupa kuesioner yang dibagikan kepada seluruh audience dalam hal ini adalah masyarakat umum. Analisis data menggunakan analisis deskriptif, dengan menggunakan SPSS. Hasil uji menyatakan bahwa video ini baik dan layak digunakan.
Decision Support Systems in Electronic Procurement for Public Sector Procurement: A Systematic Literature Review on Machine Learning Integration Cahyono, Teguh; Muhammad, Alva Hendi; Wahyuni, Sri Ngudi; Al Fatta, Hanif
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5747

Abstract

This study analyzes the evolution of Decision Support Systems (DSS) and Multi-Criteria Decision Making (MCDM) in public sector procurement between 2020 and 2025. Using bibliometric analysis of Scopus and Web of Science articles, the research focuses on themes such as e-procurement, supplier selection, public procurement, and the integration of intelligent technology. Network visualization, overlays, and density mapping were applied to explore keyword relationships, temporal trends, and research intensity. Findings reveal that in 2020, studies concentrated on transparency and digitalization in public e-procurement, with classical MCDA methods, fuzzy TOPSIS, and semantic DSS dominating the approaches. By 2022–2023, the emphasis shifted toward intelligent technologies, including artificial intelligence, neuro-fuzzy systems, and data mining algorithms. These innovations expanded DSS functions from evaluation to predictive analytics and optimization. Core themes such as supplier selection, optimization, and public procurement remained central, while emerging topics like sustainability and clinical decision support systems pointed to new research directions. A significant gap was identified in the university context. Although public sector e-procurement has been widely studied, no research has specifically addressed DSS–MCDM applications in higher education procurement systems. Consequently, future agendas should prioritize adaptive DSS tailored to universities, blockchain integration for transparency, and AI applications in clinical and humanitarian systems.
Co-Authors Abhinaya Sigit Kumara, Yohanes De Deo Achmad Fauzi Alva Hendi Muhammad Andiyoko, Cia Andiyoko, Cia Arbiansyah, Reynaldi Ariaji, Tristanto Aufa Hanif, Mohammad Budi, Galang Setia Dewi Anisa Istiqomah Eko Sediyono Erna Daniati Garjita, Lila Grafvera, Ervira Diva Guji S. U. , Fitra Jibjaya Hanafi Hanafi Hanif Al Fatta Hidayat, Fiyan Kurnia Irwan Sembiring Khanom, Nazmun Nahar Kurnia Rasyid, Muhammad Rum Andri Maemunah, Mei Maemunah, Mei Maemunah Majid, Ammar Waly Muhammad Ikhsan Mulyatun, Sri Mulyatun, Sri Mulyatun Rahmawati, Dwi Rahmawati Rosyidah Jayanti Vijaya, Rosyidah Jayanti Suyatmi, Suyatmi Suyatmi Teguh Cahyono Triwidodo, Ahmad Widowati, Anik Sri Widyawati, Rahma Widyawati, Rahma Widyawati Windarni , Vikky Aprelia Wiratama , Bill Bilal Yuli Astuti