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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Pengabdian Masyarakat Indonesia Sejahtera Teknomatika: Jurnal Informatika dan Komputer International Journal of Technology and Education Research Asian Journal of Management, Entrepreneurship and Social Science
Puguh Jayadi
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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PENGEMBANGAN MODEL RENCANA STRATEGI TEKNOLOGI INFORMASI UNTUK USAHA MIKRO KECIL DAN MENENGAH (UMKM) Puguh Jayadi; Melgisaputra Dwi Nanda; Puji Sarwono
Jurnal Teknomatika Vol 11 No 2 (2019): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

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Abstract

Semakin banyaknya kompetisi didunia bisnis dan sejalan dengan berkembangnya teknologi informasi, mulai banyak unit usaha yang mengembangkan tujuan bisnisnya dengan bantuan Teknologi Informasi (TI). Dukungan TI pada bisnis tidak hanya pada penggunaan infrastruktur hardware atau software, namun juga dengan framework dalam tata kelola TI khususnya rencana strategi TI. Beberapa framework atau petunjuk dalam rencana strategi TI dikembangkan begitu lengkap dan kompleks karena ditujukan untuk perusahaan besar dalam mencapai tujuan bisnisnya dengan memanfaatkan TI. Namun cakupan framework tata kelola TI yang sudah ada terlalu besar dari segi persiapan maupun penerapannya serta terlalu kompleks jika harus digunakan pada unit bisnis kecil seperti UMKM (Usaha Mikro, Kecil dan Menengah). Penelitian yang akan dilakukan adalah mengembangkan suatu model perencanaan strategi TI berangkat dari hasil penelitian sebelumnya. Model yang dikembangkan dapat diimplementasikan dengan memprioritaskan pada faktor penentu (core factor) dan faktor sekunder (faktor pendukung) sehingga memudahkan dalam menyesuaikan dengan kondisi, keadaan dan ukuran bisnis kecil (UMKM).
Pemanfaatan Website Profile Sebagai Sarana Informasi dan Promosi Usaha Porang Agrotanijaya Pacitan Sri Anardani; Puguh Jayadi; Latjuba Sofyana STT; Gilang Romadhon
Jurnal Pengabdian Masyarakat Indonesia Sejahtera Vol. 4 No. 3 (2025): September: Jurnal Pengabdian Masyarakat Indonesia Sejahtera
Publisher : STAI YPIQ BAUBAU, SULAWESI TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59059/jpmis.v4i3.774

Abstract

The Agrotanijaya porang business is a porang tuber processing business located in Kebondalem Village, Tegalombo District, Pacitan Regency. Currently, the marketing process for Agrotanijaya's processed products is conventional, namely entrusting it to food stalls, depots and grocery stores. The marketing system currently implemented has the problem that Agrotanijaya products are less widely known. The solution offered is the development of a website portal as an internet media facility which can display profile information from Agrotanijaya. The activity method begins with the preliminary study, implementation and evaluation stages. Based on the evaluation results, it shows that on average over 80% of participants are able to use the features on the website independently.
Enhancing Linear Regression with Forward Selection in Software Effort Estimation Puguh Jayadi; Yessi Yunitasari
Asian Journal of Management, Entrepreneurship and Social Science Vol. 4 No. 04 (2024): Upcoming issues, Asian Journal of Management Entrepreneurship and Social Scien
Publisher : Cita Konsultindo Research Center

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Software effort estimation is one of the critical aspects of software project management, but it often faces accuracy issues. Although statistical methods such as Linear Regression have been used, previous research has shown that these models are often inefficient because they involve many variables that may not be relevant. This study aims to improve the performance of Linear Regression models in software effort estimation using Forward Selection feature selection techniques. Two models were compared: the conventional Linear Regression model and the model with Forward Selection. Evaluation metrics include Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Square Error (RMSE), and coefficient of determination (R2). Results show significant improvements in all performance metrics on models with Forward Selection. Notably, the MSE increased from 1.0 to 0, suggesting that this model is more effective in explaining data variability. The use of Forward Selection in Linear Regression models for software effort estimation shows significant performance improvements and is worthy of consideration for further industry research and practice.
Analysis Design of E-IM3 Information System with Object Oriented Design Sri Anardani; Puguh Jayadi; Wasilatul Murtafiah; Rischa Pramudia Trisnani
International Journal of Technology and Education Research Vol. 3 No. 02 (2025): April - June, International Journal of Technology and Education Research (IJET
Publisher : International journal of technology and education research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63922/ijeter.v3i02.1698

Abstract

This research aims to analyse and design an information system based on the E-IM3 model using the Object-Oriented Design (OOD) approach to support the digital learning and decision-making process, especially for students with slow learning needs. The E-IM3 model, which consists of the stages of Identifying Problems, Building Ideas, Clarifying Ideas, and Assessing the Feasibility of Ideas, serves as a foundation to foster students' critical and reflective thinking. In Indonesian, E-IM3 is electronic based Identifikasi masalah, Membangun ide, Mengklarifikasi ide, dan Menilai kewajaran ide. Utilizing the System Development Life Cycle (SDLC), this research applies Object Oriented Analysis (OOA) and OOD to translate pedagogical needs into a technically robust system. The system design involves UML modelling elements starting from activity diagrams to user interfaces. Each component of the system was organized into boundary, control, and entity classes, reflecting a modular, maintainable, and user-cantered design. The user interface was developed to be intuitive and inclusive, facilitating gradual student engagement in decision-making tasks. The results show that the E-IM3 based system effectively supports personalized learning pathways and encourages high-level cognitive engagement through technology integration. This research contributes to the development of adaptive educational technologies aligned with technical and pedagogical standards in the digital age.
ANALYZING CLIMATE IMPACTS ON RICE PRODUCTION IN SUMATRA THROUGH SPATIOTEMPORAL MACHINE LEARNING MODELS Zaqi Kurniawan; Rizka Tiaharyadini; Puguh Jayadi; Windhy widhyanty
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7344

Abstract

Climate variability poses a major challenge to rice production in Sumatra, a key contributor to Indonesia’s food security. This study aims to analyze spatiotemporal climate impacts on rice yields by integrating climatic, geographical, and agricultural datasets. Historical records from 1993–2024, including rainfall, temperature, humidity, and rice production statistics, were collected from BMKG, BPS, and the Ministry of Agriculture. After preprocessing and feature selection, six machine learning algorithms—Linear Regression, Random Forest, Gradient Boosting, Support Vector Regression, Decision Tree, and K-Nearest Neighbors—were evaluated for predictive performance. Results show significant spatial heterogeneity: rainfall strongly affects yields in Aceh and North Sumatra, while temperature stress is critical in southern provinces. Among the tested models, Random Forest achieved the best accuracy (R² = 0.985), outperforming other algorithms. These findings highlight the importance of localized adaptation strategies and demonstrate the potential of ensemble machine learning to support climate-resilient rice production.
Co-Authors Anardani, Sri Gilang Romadhon Latjuba Sofyana STT Melgisaputra Dwi Nanda Puji Sarwono Rischa Pramudia Trisnani, Rischa Pramudia Rizka Tiaharyadini Sri Anardani Wasilatul Murtafiah Windhy Widhyanty Yessi Yunitasari Zaqi Kurniawan