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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%.
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.
Optimization of principal component analysis and k-nearest neighbors in cultivation area classification red onion Arif Ridho Lubis; Purwa Hasan Putra; Fahdi Saidi Lubis
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 6: December 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i6.27103

Abstract

This research aims to increase the effectiveness in classifying shallot cultivation areas through the combined application of principal component analysis (PCA) and k-nearest neighbors (KNN) methods. Shallot is an important agricultural commodity, and identification of optimal areas for its cultivation is essential to support food self-sufficiency. Onion cultivation is generally done in the highlands. One of the areas with shallot cultivation in North Sumatra Province is Berastagi, Karo Regency. This research was conducted by determining the spatial extent of upland land. In the use of data there are 2 types of data that will be used: land suitability dataset and land condition dataset for each region. The PCA method is utilized to simplify the data structure by reducing the number of dimensions and removing insignificant attributes, while KNN was used to classify regions based on their suitability for shallot cultivation. This research produces a classification map that can be used to identify the most optimal areas for shallot cultivation. The test results with the regional spatial dataset using precision, recall and fi-score testing accuracy value 0.92%, and macro avg value 0.94%, weighted avg value 0.93%.
PKM DIGITALISASI SISTEM PRESENSI SISWA MELALUI APLIKASI DI MADRASAH ALIYAH SUNGGAL DESA TANJUNG GUSTA KEC SUNGGAL KAB DELI SERDANG SUMATERA UTARA Purwa Hasan Putra; Julham Julham; Arif Ridho Lubis; Virdyra Tasril; Mayang Mughnyanti; Desilia Selvida
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 5 No. 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5385

Abstract

Abstract: The Community Service Activity of Digitalizing Student Attendance System through Application was carried out at Sunggal Islamic High School, Tanjung Gusta Village, Sunggal District, Deli Serdang Regency, North Sumatra as an effort to improve the efficiency and accuracy of student attendance recording which was previously still done manually. The web-based digital attendance system developed by the PKM team from Medan State Polytechnic allows teachers and administrative staff to record student attendance quickly, securely, and can be accessed in real-time. The recording process which previously took 7 minutes per class can be cut to 2 minutes per class. The implementation method of the activity includes observing school needs, designing and developing the application, training for teachers and staff, and mentoring during implementation. The results of the activity show that this system not only improves work efficiency but also helps improve the digital literacy of teachers and school staff. Keyword: Digitalization, Attendance, Students, MAS Aliyah Sunggal Abstrak: Kegiatan Pengabdian Kepada Masyarakat Digitalisasi Sistem Absensi Siswa Melalui Aplikasi dilaksanakan di SMA Islam Sunggal, Desa Tanjung Gusta, Kecamatan Sunggal, Kabupaten Deli Serdang, Sumatera Utara sebagai upaya untuk meningkatkan efisiensi dan akurasi pencatatan kehadiran siswa yang sebelumnya masih dilakukan secara manual. Sistem absensi digital berbasis web yang dikembangkan oleh tim PKM dari Politeknik Negeri Medan ini memungkinkan guru dan tenaga administrasi untuk mencatat kehadiran siswa secara cepat, aman, dan dapat diakses secara real-time. Proses pencatatan yang sebelumnya membutuhkan waktu 7 menit per kelas dapat dipangkas menjadi 2 menit per kelas. Metode pelaksanaan kegiatan meliputi observasi kebutuhan sekolah, perancangan dan pengembangan aplikasi, pelatihan bagi guru dan tenaga kependidikan, serta pendampingan selama pelaksanaan. Hasil kegiatan menunjukkan bahwa sistem ini tidak hanya meningkatkan efisiensi kerja tetapi juga membantu meningkatkan literasi digital guru dan tenaga kependidikan sekolah. Kata kunci: Digitalisasi, Absensi, Siswa, MAS Aliyah Sunggal 
Optimization Performance of Extreme Gradient Boosting and Random Forest for Child Stunting Classification Based on Economic Factors Lase, Yuyun Yusnida; Putra, Purwa Hasan; Lubis, Arif Ridho; Prayudani, Santi
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.
INOVASI SMART FARMING OPTIMALISASI BAWANG MERAH HIDROPONIK BERBASIS IOT DAN MACHINE LEARNING Purwa Hasan Putra; Julham Julham; Nurlinda Nurlinda; Indri Dhitisari
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2330

Abstract

Desa Berastagi memiliki potensi sumber daya alam yang luar biasa, dan masyarakatnya terdiri dari mayoritas petani dan didukung oleh BUMD. Namun, desa ini masih menerapkan pertanian konvensional dan belum menerapkan teknologi seperti IOT untuk meningkatkan produksi hasil pertanian dan ketersediaan pangan lokal untuk menggantikan komoditas pangan impor dengan usaha pertanian cerdas atau smart farming 4.0. Dalam penelitian ini, target yang diharapkan dari M&A adalah untuk menghasilkan lebih banyak hasil pertanian lokal Melalui penggunaan teknologi modern, kualitas dan kuantitas hasil panen ditingkatkan. Selain itu, teknologi ini dapat mengubah pertanian, menghasilkan sistem pertanian pintar. Pertanian cerdas menggabungkan kekuatan perangkat Internet of Things (IoT), sensor, analisis data, dan pembelajaran mesin. Selanjutnya, penulis menganalisis algoritma pembelajaran yang diawasi dengan K-Nearest neighbor digunakan dalam layanan web karena mengungguli algoritma lainnya dengan akurasi 94% dan AUC Score 0,90
OPTIMALISASI PERHITUNGAN HARGA POKOK PRODUK MELALUI PENGGUNAAN APLIKASI HPPPRO Nurlinda Nurlinda; Azzanuddin Azzanuddin; Vivianti Novita; Purwa Hasan Putra; Nirmadarningsih Hiya
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 1 (2025): February 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i1.2759

Abstract

Abstract: This study aims to produce an application to help MSMEs in calculating the cost of goods produced, predicting selling prices with competitive margin levels and producing financial reports that can be used as supporting data in making business decisions. The cost of goods is urgently studied because the determination of the wrong cost of goods and not in accordance with the business carried out by MSME entrepreneurs will have an impact on the selling price set. This research is a qualitative study. Data collection techniques are carried out using a combination of Observation, interviews, surveys and FGDs and data analysis using full costing, and descriptive analysis. User satisfaction is measured using webqual 4.0. The results of the study produce an application for cost of goods, contribution margins and selling price projections. Keywords: Cost Price, Selling Price, Application Utilization, MSMEs Abstrak: Penelitian ini bertujuan untuk menghasilkan apalikasi  untuk membantu UMKM dalam menghitung harga pokok barang yang dihasilkan, memprediksi harga jual dengan tingkat margin yang kompetitiv serta menghasilkan laporan keuangan yang dapat digunakan sebagai data dukung dalam pengambilan keputusan bisnis. Harga pokok menjadi urgen diteliti karena penetapan harga pokok yang salah dan tidak sesuai dengan bisnis yang dilakukan oleh pengusaha UMKM akan berdampak pada harga jual yang ditetapkan. Penelitian ini merupakan penelitian kualitatif. Teknik pengumpulan data dilakukan menggunakan kombinasi Observasi, wawancara, survei dan FGD serta analisis data menggunakan full costing, dan analisis deskripsi. Kepuasan pengguna diukur menggunakan webqual 4.0. Hasil penelitian menghasilkan aplikasi harga pokok, margin kontribusi dan proyeksi harga jual. Kata kunci: Harga Pokok, Harga Jual, Pemanfaatan Aplikasi, UMKM
PENGEMBANGAN APLIKASI BASIS INFORMASI PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT PADA P3M POLITEKNIK NEGERI MEDAN Purwa Hasan Putra; Yuyun Yusnida Lase; Wira Bayu Asmara
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
ANALISIS DAN OPTIMASI PREDIKSI RISIKO PENYAKIT JANTUNG MENGGUNAKAN RANDOM FOREST DAN XGBOOST BERBASIS FEATURE SELECTION Herwin Simanjuntak; Juni Santo Sihotang; Purwa Hasan Putra
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 4 (2026): August 2026 (1)
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i4.7214

Abstract

Abstract: This study aims to analyze and optimize heart disease risk prediction using Random Forest and XGBoost algorithms combined with feature selection. The dataset used is the Cleveland Heart Disease Dataset, comprising 303 patient records, 13 predictor features, and a target variable converted into a binary classification. The research stages include preprocessing, data splitting using a stratified train-test split, feature selection, hyperparameter tuning, and evaluation based on accuracy, precision, recall, F1-score, and ROC-AUC. Feature selection yielded eight selected features—thal, cp, thalach, ca, oldpeak, exang, chol, and slope—resulting in a 38.46% reduction in the total number of features. Test results indicate that the Optimized Random Forest model combined with feature selection achieved the best performance, with an accuracy of 91.80%, precision of 89.66%, recall of 92.86%, F1-score of 91.23%, and ROC-AUC of 95.67%. Keywords: Heart Disease, Random Forest, XGBoost, Feature Selection, Hyperparameter Tuning.   Abstrak: Penelitian ini bertujuan menganalisis dan mengoptimalkan prediksi risiko penyakit jantung menggunakan algoritma Random Forest dan XGBoost berbasis feature selection. Dataset yang digunakan adalah Cleveland Heart Disease Dataset yang terdiri atas 303 data pasien, 13 fitur prediktor, dan satu target yang dikonversi menjadi klasifikasi biner. Tahapan penelitian meliputi preprocessing, pembagian data menggunakan stratified train-test split, feature selection, hyperparameter tuning, serta evaluasi menggunakan accuracy, precision, recall, F1-score, dan ROC-AUC. Feature selection menghasilkan 8 fitur terpilih, yaitu thal, cp, thalach, ca, oldpeak, exang, chol, dan slope, sehingga jumlah fitur berkurang sebesar 38,46%. Hasil pengujian menunjukkan bahwa Optimized Random Forest + Feature Selection memberikan performa terbaik dengan accuracy 91,80%, precision 89,66%, recall 92,86%, F1-score 91,23%, dan ROC-AUC 95,67%. Kata Kunci: Penyakit Jantung, Random Forest, XGBoost, Feature Selection, Hyperparameter Tuning.
Co-Authors A, Azanuddin Ade Maulana Alfiansyah Hasibuan Asmara, Wira Bayu Azzanuddin Azzanuddin Azzanuddin, Azzanuddin Dalimunthe, Yulia Agustina Desilia Selvida Dhitisari, Indri Efni Siregar & Vivianti Novita - F. Friendly Fahdi Saidi Lubis Fawwaz, Insidini Friendly, Friendly Harizahayu, Harizahayu Hasibuan, Alfiansyah Hasnita, Ulfa Herwin Simanjuntak Hiya, Nirmadarningsih Indri Dhitisari Julham Julham Julham Julham Julham Juni Santo Sihotang Lavenia Ulandari Lubis, Arif Ridho Marpaung, Effenril Agung Mayang Mughnyanti 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 Nirmadarningsih Hiya Nugroho Syahputra Nurlinda Nurlinda Nurlinda Nurlinda, Nurlinda Nurrahmadayeni, Nurrahmadayeni Pranata, Ardianto Prayudani, Santi Purba, Bister Rahmat Widia Sembiring - Ramli, Muslim Roslina Roslina, Roslina Silalahi, Oktavia Ully Artha Tasril, Virdyra Virdyra Tasril Wira Bayu Asmara Wiwin Sry Adinda Banjarnahor Yudhistira Adhitya Pratama Yusoff, Marina Yuyun Yusnida Lase Zulfahmi Syahputra