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All Journal Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Responsif : Riset Sains dan Informatika Bulletin of Information Technology (BIT) Coreid Journal Journal of Elektronik Sistem InformasI Software Engineering in Computing Systems
Popon Dauni
Universitas Kebangsaan Republik Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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PEMETAAN KEBERLANGSUNGAN HIDUP UMKM GUNA OPTIMALISASI BANTUAN KREDIT MENGGUNAKAN ALGORITMA FUZZY C-MEANS Popon Dauni; Pratiwi Pratiwi; Rizki Tri Prasetio
Jurnal Responsif : Riset Sains dan Informatika Vol 5 No 1 (2023): Jurnal Responsif : Riset Sains dan Informatika
Publisher : LPPM Universitas Adhirajasa Reswara Sanjaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51977/jti.v5i1.1051

Abstract

Dinamika perekonomian Indonesia mengalami kontraksi semenjak pandemi Coronavirus Disease (COVID-19) mulai menyebar awal tahun 2020. Pembatasan sosial dan terbatasnya kegiatan masyarakat serta larangan beroperasinya usaha yang dapat menimbulkan kerumunan menyebabkan melemahnya ekonomi usaha mikro, kecil dan menengah (UMKM) bahkan hingga terancam menutup usahanya. Padahal UMKM merupakan penyumbang produk domestik bruto (PDB) nasional terbesar. Pemerintah melalui kementerian terkait telah meluncurkan berbagai program bantuan guna menyelamatkan UMKM dari krisis permodalan. Dalam upaya optimalisasi program pemerintah, maka diperlukan sebuah kelompok atau tingkatan yang dapat digunakan untuk menentukan prioritas bantuan pemerintah bagi UMKM agar program bantuan tersebut tepat sasaran. Untuk mengelompokan UMKM digunakan teknik data mining yakni, clustering. Partitive clustering digunakan sebagai pendekatan karena dinilai cocok dengan masalah yang dihadapi karena dapat mengelompokan berdasarkan kemiripan atau kedekatan antar data, sesuai dengan tujuan untuk mengelompokan UMKM berdasarkan kesamaan kondisi yang saat ini sedang dihadapi. Algoritma partitive clustering akan digunakan pada penelitian ini yakni algoritma fuzzy-c-means. Metode penelitian yang digunakan adalah cross industry standard process for data mining (CRISP-DM) yang merupakan standar model penelitian lintas industri untuk pemrosesan data yang memiliki enam tahapan penelitian diantaranya, pemahaman bisnis, pemahaman, penyiapan, pemodelan, evaluasi hingga implementasi. Penelitian ini menghasilkan 2 kelompok tingkatan UMKM yaitu kelompok keberlangsungan hidup kuat dan lemah. UMKM kuat memiliki kriteria omset yang besar dengan perbandingan jumlah karyawan terhadap omsetnya seimbang, sementara UMKM lemah memiliki kriteria omset yang relatif besar namun dengan perbandingan jumlah karyawan terhadap omsetnya tidak seimbang. Kualitas pengelompokan yang dihasilkan pun cukup baik ditandai dengan nilai Davies-Bouldin Index sebesar 0.75.
Implementasi Metode ROC dan WP Dalam Sistem Pendukung Keputusan Terhadap Calon Penerima Pinjaman Koperasi Karya Suhada; Dede Hendrik; Andriyana; Evi Isnandar; Popon Dauni
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2446

Abstract

Cooperatives are financial institutions that play a vital role in the economy, especially in developing countries. They provide various financial services to their members, including loans with relatively lower interest rates compared to commercial financial institutions. This study aims to develop and implement a Decision Support System (DSS) using the Rank Order Centroid (ROC) and Weighted Product (WP) methods for selecting cooperative loan recipients. Cooperatives often face challenges in determining eligible loan recipients to minimize default risk. The ROC method is used to objectively determine the criteria weights, while the WP method integrates these weights with the performance values of each candidate. By combining these two methods, it is expected to produce more accurate and fair decisions. The study was conducted in Asahan with data collected from various official sources. The criteria used include age, monthly income, employment status, credit history, and income stability. The results show that the combination of ROC and WP methods can improve the accuracy and efficiency of the cooperative loan recipient selection process and minimize the risk of default. This study contributes significantly to the field of DSS and can serve as a reference for developing decision-making methods in other fields requiring multi-criteria analysis. The findings also can be used by cooperatives to enhance the loan granting process, ensuring financial health, and member welfare. The implementation results indicate that the selected cooperative loan recipient is alternative A6, Fitriani Sari, with a score of 0.1257.
Mendesain Antarmuka Pengguna Sistem Informasi Manajemen Aset TI menggunakan Pendekatan Desain Berpikir Yogi Saputra; Agung Pratama; Nana Suryana; Popon Dauni; Novianti Indah Putri
JESII: Journal of Elektronik Sistem InformasI Vol 4 No 1 (2026): Journal of Elektronik Sistem InformasI - JESII (DECEMBER)
Publisher : Departement Information Systems Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/jesii.v4i1.4798

Abstract

It is crucial to create an information system, especially for asset management, to design a good user interface (UI). The purpose of this study is to test the application of the Design Thinking method in the UI design process for the IT Asset Management Information System at PT Niaga Handal Cemerlang located in Bandung City. The Design Thinking method was chosen because of its user-focused approach, which allows for the creation of a functional and easy-to-use interface. Empathy, problem definition, ideation, prototyping, and testing are the steps in this study. This study found that applying Design Thinking can improve the quality of the user interface, which impacts how efficient the company's asset management is. These results support that a user-oriented approach is crucial when building complex information systems.
Global Trends and Framework Development of AI and IoT Integrated Waste Automation for Emerging Economies Sri Erina Damayanti; Brian Damastu Ridho Hutama; Popon Dauni; Jack Febrian Rusli
Software Engineering in Computing Systems Vol. 1 No. 2 (2026): May: Software Engineering in Computing Systems
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/secons.v1i2.444

Abstract

Waste management in Indonesia faces extreme regional disparities, ranging from critical waste accumulation zones and circular economy transition zones to specific material deficit zones. The primary problem lies in the inability of conventional systems to process heterogeneous waste efficiently, which leads to the failure of sustainable environmental conservation. An intelligent solution is required to integrate physical technology with an adaptive policy evaluation system. This research develops a systematic framework for the development and evaluation of waste processing automation technology. The research stages begin with a Bibliometric Analysis and Systematic Literature Review (SLR) using metadata from Scopus and Web of Science to identify global trends via VOSviewer. Furthermore, this study integrates AI and IoT as primary instruments for nature conservation. Through the processing of large data volumes (Big Data) from IoT sensors, AI (such as Multi-Criteria Decision Making) performs predictive analysis to automatically evaluate three regional conditions. AI plays a crucial role in determining corrective actions, including optimizing the use of oxy-hydrogen (HHO) fuel in incinerators to suppress emissions and managing cross-regional waste logistics, thereby ensuring natural resources are preserved through precise and low-pollution waste elimination processes. This research generates intelligent governance patterns and actionable insights to guide system users, particularly local governments and industrial managers, in implementing appropriate waste processing technologies. This solution provides automated operational guidance that ensures energy efficiency and economic sustainability while maintaining ecosystem preservation through standardized waste processing based on the specific regional characteristics in Indonesia.
Implementasi Framework COBIT 2019 Pada Audit Sistem Informasi Akademik Universitas Kebangsaan Republik Indonesia Fachrully Adira Muhammad; Yogi Saputra; Novianti Indah Putri; Erwin Teguh Arujisaputra; Adam Husain; Popon Dauni
TEMATIK Vol. 12 No. 2 (2025): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Desember 2025
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v12i2.2618

Abstract

Transformasi digital pada pendidikan tinggi menuntut tata kelola sistem akademik yang terstandar dan terukur, namun banyak institusi menhadapi tantangan dalam dokumentasi formal dan standarisasi proses teknologi informasi. Penelitian ini bertujuan untuk mengaudit Sistem Informasi Akademik (SIAKAD) Universitas Kebangsaan Republik Indonesia (UKRI) menggunakan framework COBIT 2019 guna mengidentifikasi kesenjangan kapabilitas dan strategi perbaikan terstruktur. Penelitian menggunakan pendekatan kuantitatif dengan metode triangulasi, seperti observasi, wawancara, dan kuesioner, yang melibatkan 23 responden, diantaranya 4 internal stakeholder dan 19 mahasiswa. Berfokus pada enam subdomain, yaitu APO02, APO05, APO12, DSS04, MEA01, dan MEA03. Penilaian capability level menunjukkan seluruh subdomain berada pada level 1 – performed process dengan nilai rata-rata berkisar 3,4-4,0 dalam skala Likert (1-5), yang setelah triangulasi data mengonfirmasi proses telah berjalan namun belum terdokumentasi formal. Analisis gap menunjukkan kesenjangan 3 level antara kondisi aktual (level 1) dan target (level 4 – predictable process). Penelitian menghasilkan rekomendasi perbaikan komprehensif yang meliputi penyusunan dokumentasi formal, pembentukan sistem pengelolaan terstruktur, dan implementasi pengukuran kinerja berbasis data. Roadmap pengembangan lima tahun (2026-2030) dirancang melalui lima fase, yaitu Assessment dan Awareness, Dokumentasi dan Integrasi, Implementasi dan Uji Proses, Penetapan dan Integrasi Audit, serta Standarisasi dan Prediktabilitas. System blueprint memetakan transformasi dari kondisi as-is menuju kondisi to-be dengan strategi perbaikan spesifik untuk setiap subdomain. Penelitian ini memberikan kontribusi praktis berupa panduan terstruktur untuk meningkatkan kapabilitas SIAKAD UKRI dari level 1 ke level 4 dalam periode lima tahun, sekaligus menyediakan instrumen audit yang dapat direplikasi oleh institusi pendidikan tinggi lain untuk mewujudkan tata kelola sistem informasi akademik yang berkelanjutan dan terukur.
Natural Language Processing and Random Forest for Mental Health Symptom Identification Using Social Media Data Sigit Sugara; Popon Dauni; Novianti Indah Putri; Yogi Saputra; Nana Suryana
CoreID Journal Vol. 3 No. 3 (2025): November 2025
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v3i3.145

Abstract

This study explores the implementation of machine learning models, specifically Natural Language Processing (NLP) and Random Forest, for detecting mental health symptoms based on text analysis of web-sourced data. The research addresses the challenges of analyzing highly subjective and dynamic text in social media content to identify patterns associated with anxiety, depression, and stress. The methodology involves several preprocessing steps including case folding, cleansing, language normalization, negation conversion, stopword removal, and tokenization, followed by TF-IDF weighting and Random Forest classification. The model evaluation revealed a high accuracy rate of approximately 80%, although achieving a confidence level of 75% proved challenging. This research demonstrates that despite the inherent difficulties in predicting subjectively variable text, the machine learning approaches employed show satisfactory performance in identifying mental health symptoms, offering potential for early detection and intervention systems.
Co-Authors Adam Husain Agung Pratama Andriyana Brian Damastu Ridho Hutama Dede Hendrik Erwin Teguh Arujisaputra Evi Isnandar Fachrully Adira Muhammad Jack Febrian Rusli Karya Suhada Nana Suryana Novianti Indah Putri Pratiwi Pratiwi Rizki Tri Prasetio, Rizki Tri Sigit Sugara Sri Erina Damayanti Yogi Saputra Yogi Saputra