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All Journal Jurnal Ilmiah Kursor Edu Komputika Journal Sistemasi: Jurnal Sistem Informasi SMARTICS Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Applied Information System and Management MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer J-Dinamika: Jurnal Pengabdian Kepada Masyarakat EDUMATIC: Jurnal Pendidikan Informatika Abdi Dosen : Jurnal Pengabdian Pada Masyarakat JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pengabdian Kepada Masyarakat Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Kepada Masyarakat
Ahmadi Yuli Ananta
Politeknik Negeri Malang
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Implementasi Website Profil Sebagai Strategi Peningkatan Penjualan Di Toko Kue Macaron Tuffero Ahmadi Yuli Ananta; Rudy Ariyanto; Rakhmat Arianto; Imam Fahrur Rozi; Erfan Rohadi; Farida Ulfa
KOMUNITA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 5 No 1 (2026): Februari
Publisher : PELITA NUSA TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60004/komunita.v5i1.394

Abstract

This community service activity was carried out with the aim of enhancing the competitiveness and brand image of Macaron Tuffero through the development of a Profile Website as an effective and sustainable digital promotion medium. The partner of this program is the Macaron Tuffero SME, which operates in the production of cakes and desserts, located in Dau District, Malang Regency. The activity involved the business owner and staff as primary participants who collaborated actively with the community service team from Politeknik Negeri Malang. The main problem faced by the partner was the limited use of digital promotion media and the absence of an official platform to professionally present the business profile. To address this issue, the activity was implemented through five main stages: needs analysis, website design and architecture planning, system development and implementation, testing, and website usage training. The website was developed using the WordPress platform with the WooCommerce plugin to facilitate product catalogs and online ordering features. The results show that the developed website functions properly, consistently presents the business’s visual identity, and integrates with various social media and marketplace platforms. The website also provides convenience for the business owner to independently update content. Overall, this community service program successfully delivered a practical digital solution that contributes to marketing capacity enhancement and supports digital transformation among SMEs in the technology-based economy era.
Logistic Regression-Based Classification of Food Security Vulnerability in East Java Districts Ahmadi Yuli Ananta; Rudy Ariyanto; Rakhmat Arianto; Imam Fahrur Rozi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 3 (2026)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i3.6002

Abstract

The problem addressed in this study is the limited capacity of district-level food-security monitoring in Indonesia to anticipate deterioration in the following year, particularly when prediction relies on short longitudinal histories and must account for repeated observations, class imbalance, temporal change, and regional variation. The method involved constructing 2,056 temporally ordered prediction instances from Food Security Index data covering 514 Indonesian districts and cities during 2019–2024, representing six regional indicators through their current values and annual changes, and evaluating Logistic Regression, Random Forest, and eXtreme Gradient Boosting through district-grouped crossvalidation, alternative imbalance treatments, and an untouched 2023–2024 out-of-time test; temporal ablation, cluster-robust Logistic Regression, SHapley Additive exPlanations, sensitivity analysis, anddirect assessment in East Java were subsequently conducted. The result showed that Logistic Regression achieved the strongest screening-oriented performance, with a recall of 0.690, an F1-score of 0.450, a Receiver Operating Characteristic Area Under the Curve of 0.615, and a Precision–Recall Area Under the Curve of 0.404, while annual-change features improved F1-score and Precision–Recall Area Under the Curve across all three classifiers. However, performance declined in East Java, where two of four deterioration cases were detected, and 22 false-positive warnings were generated. The implication is that parsimonious temporal features provide useful predictive information beyond current regional conditions, although the model is more appropriate for screening and prioritization than for autonomous administrative classification, while operational use requires local calibration, longitudinal data auditing, threshold assessment, and validation across additional provinces and later annual transitions.
Genetic Algorithm–Optimized Clustering for University Promotion Target Recommendation Ulla Delfana Rosiani; Clauria Dwi Putri Nabillah; M. Hasan Basri; Ahmadi Yuli Ananta; Yushintia Pramitarini
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i1.50061

Abstract

Competition among higher education institutions demands promotional strategies that are more targeted and data-driven. This study proposes a clustering-based recommendation model for determining university promotion targets by integrating Genetic Algorithm (GA) optimization into three clustering methods: K-means, Fuzzy C-means (FCM), and K-medoids. The dataset consists of 925 student records (cohorts 2021–2023) from the Information Technology Department, with the selected attributes including school origin, NPSN, school location (city and province), and GPA. Clustering performance was evaluated using the Davis-Bouldin Index (DBI) and the Silhouette Coefficient as primary metrics, with intra- and inter-cluster distances as supporting indicators. The results show that GA-K-means achieves the best performance at K = 3, with a DBI of 1.2792 and a Silhouette Coefficient of 0.2876, and the improvement is statistically significant (p < 0.05). GA optimization also improves FCM performance but does not significantly improve K-medoids performance. Although the GA increases computational time by approximately two to three times, the improvement in clustering quality justifies its use in non-real-time decision-support scenarios. The proposed model enables universities to determine promotion targets in a more objective, adaptive, and data-driven manner, supporting strategic decision-making in higher education promotion.
Co-Authors -, Ervin Vidi Wicahya Achmad Zaini Ade Ismail Ahmad Nova Rifki Wildani Alfian Karunyan Syah Amalia, Astrifidha Rahma Arin Kistia Nugraeni Astrifidha Rahma Amalia Atiqah Nurul Asri Batubulan, Kadek Suarjuna Budiarti, Arry Clauria Dwi Putri Nabillah Danang Eko Novianto Darwis, Muhammad Robbi Darwis Diana Eka Poernamawati Dika Rizky Yunianto Dimas Wahyu Wibowo Doddy Maulana Dwi puspitasari DWI PUSPITASARI Eka Larasati Amalia Elok Nur Hamdana Endah Septa Sintiya Erfan Rohad Erfan Rohadi Ervin Vidi Wicahya Farida Ulfa Farida Ulfa Gusedy, Nura Ursula Herwandi Herwandi Imam Fahrur Rozi Imam Fahrur Rozi Imam Saukani Irawan, Ferry Buyung Bakhtiar Irsyadha Alfyrdhousi Redhysyahputra Ivan Abdurrafie M. Hasan Basri Mamluatul Hani’ah Maulidia, Irma Meuti Zari Annisa Muhammad Robbi Darwis Darwis Muhammad Shulhan Khairy Mustika Mentari Noprianto, Noprianto Novianto, Danang Eko Nugraeni, Arin Kistia Rahmad, Cahya Rahmanto, Anugrah Nur Rakhmat Arianto Rakhmat Arianto Ratih Indri Hapsari Riatma, Galih Putra Rudy Ariyanto Saputra, Zainal Ulu Prima Septian Enggar Sukmana Setiawan, Budhy Sholiha, Afifah Sidik Nurcahyo Sofyan Noor Arief Syah, Alfian Karunyan Ulla Delfana Rosiani Usman Nurhasan Vivi Nur Wijayaningrum Widito, Sasmojo Wildani, Ahmad Nova Rifki Yuri Ariyanto Yuri Ariyanto Yuri Ariyanto Yushintia Pramitarini Zakaria, Arief Syukron Zubaidi Zubaidi