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All Journal Jurnal Transformatika JATI (Jurnal Mahasiswa Teknik Informatika) LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Kecerdasan Buatan dan Teknologi Informasi
Purnomo Putro, Dwi
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Transportation Other

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PERANCANGAN SISTEM INFORMASI B2B UNTUK MENINGKATKAN EFISIENSI OPERASIONAL DI CV. X Solikin, Mokhamad; Muhammad Jogo Samodro, Maulana; Purnomo Putro, Dwi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13542

Abstract

Persaingan bisnis yang semakin ketat menuntut perusahaan untuk memiliki sistem informasi yang cepat, akurat, dan efisien. CV. X, sebagai badan usaha yang bekerja sama dengan berbagai distributor, masih menggunakan pencatatan manual dalam pengelolaan transaksi, sehingga berisiko tinggi terhadap kesalahan data dan ketidakefisienan operasional. Permasalahan tersebut dapat diatasi menggunakan perancangan sistem informasi berbasis Business-to-Business (B2B) dengan pendekatan Entity-Relationship Diagram (ERD) dan Data Flow Diagram (DFD). ERD digunakan untuk memodelkan struktur data, sementara DFD digunakan untuk memvisualisasikan aliran data dalam sistem. Implementasi sistem ini dikembangkan menggunakan teknologi PHP, MySQL, dan framework CodeIgniter. Pengujian dilakukan dengan metode Black Box Testing dan Alpha Testing untuk memastikan sistem berfungsi dengan baik dan sesuai dengan kebutuhan pengguna. Hasil pengujian menunjukkan bahwa sistem yang dirancang mampu meningkatkan efisiensi operasional, meminimalkan kesalahan pencatatan, serta memberikan fleksibilitas dalam pengelolaan data transaksi. Berdasarkan hasil tersebut diharapakan penerapan sistem informasi berbasis B2B dapat mendukung CV. X dalam meningkatkan kinerja bisnis serta memperkuat hubungan dengan mitra usahanya
Komparasi AHP, SAW, TOPSIS, VIKOR, dan MABAC pada Sistem Pengambilan Keputusan Pemilihan Supplier Obat Purnomo Putro, Dwi; Eka Suryani, Puput; Amri, Saeful
Jurnal Transformatika Vol. 23 No. 1 (2025): July 2025
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i1.12220

Abstract

The selection of pharmaceutical suppliers is crucial for ensuring consistent drug availability and maintaining service quality in healthcare facilities. This study offers a comparative analysis of five Multi Criteria Decision Making methods (AHP, SAW, TOPSIS, VIKOR, and MABAC) applied to supplier evaluation based on four key criteria: price, delivery time, receipt accuracy, and product quality. Unlike previous studies that employed individual or dual methods, this research evaluates all five methods using the same dataset to assess consistency, sensitivity, and decision reliability. The results show strong ranking consistency across methods, with AHP and SAW producing identical outputs. TOPSIS and VIKOR offer similar outcomes based on proximity and compromise analysis, while MABAC demonstrates high discrimination power for mid-ranked suppliers. Sensitivity tests confirm ranking stability under moderate weight variations. This study provides practical recommendations for selecting appropriate decision methods in pharmaceutical procurement systems based on operational context and desired decision accuracy.
Implementasi Sistem Rekomendasi Mitigasi Layanan Sertifikasi Produk Halal Berbasis Blockchain pada LP UMKM Muhammadiyah Kota Semarang Amri, Saeful; M. Al Haris; Purnomo Putro, Dwi; Mandala Adikara Sencoko
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2025): Desember 2025
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v7i2.521

Abstract

The Muhammadiyah Regional Leadership (PDM) of Semarang City has an MSME Development Institute (LP). This institution has a specific mission in developing MSMEs in growing, mobilizing, improving and empowering the potential of MSMEs in the national and global business arena. This community service activity is to implement a distributed system to develop the creative industry and encourage entrepreneurship in the field of digital technology and innovation and can increase responsible consumption and production in terms of halal consumer products for Muhammadiyah MSMEs in Semarang City. This activity includes socialization, training on system operation, implementation, mentoring and monitoring. The results show that the implementation of the system can document the data of MSMEs well by 75%, halal product certification for MSMEs increased by 80%, and skills in operating the system are increasing, based on the satisfaction level reaching 91% after the activity. This program proves that utilizing technology can provide convenience in verifying data for the halal certification process and increase security and reduce the risk of data loss.
THE USE OF EXPLAINABLE AI FOR ANALYZING SOCIOECONOMIC DETERMINANTS OF THE HUMAN DEVELOPMENT INDEX IN INDONESIA BASED ON REGRESSION MODELS Istikomah, Sintha; Purnomo Putro, Dwi
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 3 (2025): September 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i3.456

Abstract

The Human Development Index (HDI) is a key indicator of quality of life, reflecting achievements in health, education, and a decent standard of living. Significant regional disparities in Indonesia highlight the need to analyze its determinants for effective policy formulation. This study examines the simultaneous influence of socioeconomic factors—poverty rate, GRDP per capita, life expectancy, mean years of schooling, and expenditure per capita—on HDI across 514 regencies/cities using machine learning and Explainable AI (XAI). Secondary data from the Indonesian Central Bureau of Statistics (BPS) in 2021 were utilized. The target variable (IPM_score) was constructed through feature engineering. Linear Regression, Random Forest, and XGBoost models were trained using an 80:20 split and evaluated with Mean Squared Error (MSE) and R². SHAP was applied to interpret feature contributions. Results show XGBoost achieved the best performance (R² = 0.987), outperforming Random Forest (R² = 0.974), while Linear Regression achieved R² = 1.000 due to perfect linearity. SHAP analysis identified expenditure per capita as the most dominant factor (r = 0.9996), followed by mean years of schooling (r = 0.667), while poverty showed a strong negative effect (r = -0.638). These findings emphasize that purchasing power and education are critical drivers of HDI. The use of XAI enhances model transparency and supports evidence-based policy, particularly in integrating poverty reduction with improvements in education and economic capacity.
Co-Authors Amri, Saeful Eka Suryani, Puput Istikomah, Sintha M. Al Haris Mandala Adikara Sencoko Maulana Muhammad Jogo Samudro Solikin, Mokhamad