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Putra, Purwa Hasan
Politeknik Negeri Medan, Medan, Indonesia
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PENGEMBANGAN APLIKASI BASIS INFORMASI PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT PADA P3M POLITEKNIK NEGERI MEDAN Putra, Purwa Hasan; Lase, Yuyun Yusnida; Asmara, Wira Bayu
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5832

Abstract

Abstract: This study aims to analyze the utilization of the Simlibtamas system in managing research proposal submissions at the Medan State Polytechnic. Based on observations on the system dashboard, there are 1,299 registered users, 21 of whom are active, who have submitted proposals, and a total of 800 proposals that have been processed. This system is able to display information in a structured manner through a submission table containing the name of the proposer, the proposal title, the original scheme, document files, assessments, and the amount of proposed and recommended funding. In addition, a recapitulation graph of the amount of funding shows the existence of funding submissions within a certain time period, reflecting the dynamics of research activity. The results show that the Simlibtamas system has functioned well in supporting the administration and evaluation process of research proposals. However, the involvement of proposer users still needs to be improved for more optimal system utilization. In conclusion, Simlibtamas is able to facilitate monitoring, transparency, and management of research, and can be further developed to increase participation and effectiveness of research fund distribution. Keywords: Information Systems, Applications, Simlibtimnas, Research, Community Service Abstrak: Penelitian ini bertujuan untuk menganalisis pemanfaatan sistem Simlibtamas dalam pengelolaan pengajuan proposal penelitian di Politeknik Negeri Medan. Berdasarkan hasil pengamatan pada dashboard sistem, tercatat sebanyak 1299 pengguna terdaftar dengan 21 pengguna aktif yang mengajukan proposal, serta total 800 proposal yang telah diproses. Sistem ini mampu menampilkan informasi secara terstruktur melalui tabel pengajuan yang memuat nama pengusul, judul proposal, skema pendanaan, file dokumen, penilaian, serta jumlah dana yang diusulkan dan direkomendasikan. Selain itu, grafik rekapitulasi jumlah dana menunjukkan adanya fluktuasi pengajuan dana dalam rentang waktu tertentu, yang mencerminkan dinamika aktivitas penelitian. Hasil penelitian menunjukkan bahwa sistem Simlibtamas telah berfungsi dengan baik dalam mendukung proses administrasi dan evaluasi proposal penelitian. Namun, keterlibatan pengguna pengusul masih perlu ditingkatkan agar pemanfaatan sistem menjadi lebih optimal. Kesimpulannya, Simlibtamas mampu memudahkan monitoring, transparansi, dan pengelolaan penelitian, serta dapat dikembangkan lebih lanjut untuk meningkatkan partisipasi dan efektivitas distribusi dana penelitian. Kata kunci: Sistem Informasi, Aplikasi, Simlibtimnas, Penelitian, Pengabdian
Pemanfaatan Canny Edge Detection untuk Pembacaan OMR Survey 7 Kebiasaan Anak Indonesia Hebat Friendly Friendly; Harizahayu Harizahayu; Purwa Hasan Putra
INSOLOGI: Jurnal Sains dan Teknologi Vol. 5 No. 1 (2026): Februari 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v5i1.6705

Abstract

The 7 Kebiasaan Anak Indonesia Hebat program is one of the priority program of the Ministry of Primary and Secondary Education of the Republic of Indonesia. It aims to develop students with strong academic ability, good behavior, and strong character. The program is implemented in all primary and secondary schools, and thus large amounts of data must be summarized for monthly reports. Urban schools often use Google Forms or digital applications to record students’ activities, while schools in smaller towns or rural areas still rely on paper forms. Limited access to smartphones and internet connections among parents makes online data collection difficult. Consequently, teachers must manually summarize data using spreadsheet applications, increasing their workload—especially when managing many students. This study proposes the use of Canny Edge Detection to automate data processing from OMR (Optical Mark Recognition) sheets. By scanning or photographing filled OMR sheets, the system can accurately read and convert students’ responses into digital data. This method allows teachers to digitize the reporting process and reduce manual work. Using this method, the accuracy of reading the OMR sheets can reach 81% while the need of informing the parents to fill the form correctly since some tested data shown recall data reached 68%.
Optimization Performance of Extreme Gradient Boosting and Random Forest for Child Stunting Classification Based on Economic Factors Yuyun Yusnida Lase; Purwa Hasan Putra; Arif Ridho Lubis; Santi Prayudani
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5864

Abstract

Stunting remains a major health concern in Indonesia due to its impact on children’s physical growth and cognitive development. One of the factors influencing the incidence of stunting is family economic status, which is linked to access to nutrition, sanitation, and a healthy environment. This study aims to optimize the performance of the XGBoost and Random Forest algorithms in classifying stunting in children based on economic factors and to compare the performance of the two models. The methods used in this study involve a machine learning approach, including data preprocessing, model training, hyperparameter optimization, and performance evaluation using a confusion matrix, accuracy, precision, recall, F1-score, and ROC-AUC curves. The results indicate that both algorithms perform well in classification, with an accuracy rate of approximately 70%. The Random Forest model demonstrated better performance than XGBoost with an AUC value of 0.7655, while XGBoost had an AUC value of 0.75. Additionally, the feature importance results indicated that economic and environmental factors, such as housing conditions and sanitation, have a significant influence on the incidence of stunting.
Application of Apriori Algorithm in Data Mining to Find Consumer Purchasing Patterns in Supermarkets Purwa Hasan Putra; Desilia Selvida; Muhammad Syahputra Novelan
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 1 (2025): Juni 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i1.392

Abstract

The development of information technology has encouraged the use of transaction data in the retail world to gain deeper business insights. One method used in data mining is the Apriori algorithm, which is able to identify consumer purchasing patterns through association analysis between products. This study aims to apply the Apriori algorithm in finding product combination patterns that are often purchased together by consumers in supermarkets. The data used are sales transactions that have gone through a preprocessing process, including product category classification and transformation into a basket format. The results of the analysis show that products such as biscuits, detergents, and household appliances have the highest support values ​​individually, while product combinations such as (milk, drinks, soap & shampoo, cosmetics) also appear consistently in transactions. The application of the Apriori algorithm with a certain minimum support threshold is able to produce frequent itemsets that represent consumer shopping habits. These findings can be used to develop promotional strategies, product arrangement, and category-based recommendation systems. Thus, this study proves that the Apriori algorithm can be used effectively in the context of data mining to support business decision making in the retail sector, especially supermarkets.
Co-Authors A, Azanuddin Ade Maulana Adhitya Pratama, Yudhistira Alfiansyah Hasibuan Arif Ridho Lubis Asmara, Wira Bayu Azzanuddin, Azzanuddin Dalimunthe, Yulia Agustina Dhitisari, Indri Efni Siregar & Vivianti Novita - F. Friendly Friendly, Friendly Harizahayu, Harizahayu Hasibuan, Alfiansyah Hasnita, Ulfa Hiya, Nirmadarningsih Insidini Fawwaz Julham Julham Julham Lavenia Ulandari Lubis, Arif Ridho Marpaung, Effenril Agung Medi Hermanto Tinambunan Mohamad Zain, Jasni Bt Mughnyanti, Mayang Muhammad Rizki Muhammad Rusdi dan Afritha Amelia - Muhammad Syahputra Novelan Nababan, Adli Abdillah Nababan, Arif Hamied Ningtyas, Alyiza Dwi Nugroho Syahputra Nurlinda Nurlinda Nurlinda, Nurlinda Nurrahmadayeni, Nurrahmadayeni Pranata, Ardianto Prayudani, Santi Purba, Bister Rahmat Widia Sembiring - Ramli, Muslim Roslina Roslina, Roslina Santi Prayudani Selvida, Desilia Silalahi, Oktavia Ully Artha Tasril, Virdyra Wiwin Sry Adinda Banjarnahor Yusoff, Marina Yuyun Yusnida Lase Yuyun Yusnida Lase Zulfahmi Syahputra Zulfahmi Syahputra