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All Journal International Journal of Electrical and Computer Engineering Jurnal INKOM Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Sistemasi: Jurnal Sistem Informasi International Journal of Artificial Intelligence Research Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Jurnal Penelitian Pendidikan IPA (JPPIPA) MUST: Journal of Mathematics Education, Science and Technology Techno Nusa Mandiri : Journal of Computing and Information Technology Techne : Jurnal Ilmiah Elektroteknika Jurnal Pertanian Agros Jurnal Informatika Universitas Pamulang Indonesian Physical Review INTI Nusa Mandiri JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Pengabdian kepada Masyarakat Nusantara Insyst : Journal of Intelligent System and Computation Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Agus Subekti
Balai Pengkajian Teknologi Pertanian Kalimantan Barat Jalan Budi Utomo No. 45, Siantan Hulu, Kotak Pos 6150, Pontianak 78061, Kalimantan Barat, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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Perancangan Sistem Informasi Pengolahan Data Pegawai Pada Agency Andalus Institute Berbasis Java Subekti, Agus; Kusmayadi, Kusmayadi; Aditya, Dedy Yusuf
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 5, No 1 (2021): SEMNAS RISTEK 2021
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v5i1.5170

Abstract

Agency andalus institute adalah perusahaan yang bergerak di bidang properti. Dalam pengelolaan data pegawai perusahaan masih dilakukan secara manual yaitu dengan memasukan data pada microsoft exel. Dalam pengolahan data pegawai yang masih manual, mengakibatkan timbul sebuah masalah yang muncul yaitu kendala dalam efektivitas dan keamanan pada saat mengelola data pegawai, oleh karena itu maka perusahaan membutuhkan sistem yang efisien dan aman. Tujuan dari penelitian ini adalah merancang aplikasi untuk menunjang pengolahan data pegawai pada bidang usaha property Agency andalus institute dan diharapkan agar bermanfaat nantinya. Dalam perancangan aplikasi pengolahan data pegawai, menggunakan bahasa pemrograman java dengan pemodelan prototipe. Terdapat beberapa tahapan dalam pembuatan prototipe seperti identifikasi kebutuhan, membangun prototipe, evaluasi prototipe, mengkodekan sistem, evaluasi sistem, menggunakan sistem. Dalam hasil penelitian yang di lakukan maka dibuatlah aplikasi pengolahan data pegawai, agar dapat membantu kebutuhan perusahaan agar lebih efisien dan aman khususnya dalam pengolahan data pegawai.
OPTIMIZING ELECTRON DIFFUSION, TEMPERATURE, AND PHOTOANODE THICKNESS FOR ENHANCED PHOTOVOLTAIC EFFICIENCY IN TiOâ‚‚/CuS DYE-SENSITIZED SOLAR CELLS (DSSCs) Muhammad, Nawafil; Supriyanto, Edy; Prasetya, Dwi Sabda Budi; Setyaningsih, Emy; Subekti, Agus
Indonesian Physical Review Vol. 8 No. 1 (2025)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ipr.v8i1.413

Abstract

This study addresses a critical gap in optimizing electron diffusion, operational temperature, and photoanode thickness to enhance the photovoltaic efficiency of TiO₂/CuS-doped dye-sensitized solar cells (DSSCs). While previous studies have investigated individual parameters affecting DSSC performance, limited research examines their combined effects on charge transport and recombination rates. Through computational modeling, we evaluated photoanode thicknesses from 1 µm to 100 µm and operational temperatures from 260 K to 350 K, analyzing their influence on electron mobility, recombination rates, and overall efficiency. Results show that the electron diffusion coefficient increases with temperature, reaching a maximum of 1.626 × 10⁻⁶ cm²/s at 350 K, thereby enhancing electron transport and reducing recombination losses. An optimal photoanode thickness of 3 µm was identified, yielding the highest efficiency of 17.28% across the temperature range. Efficiency declines at thicknesses exceeding 3 µm due to extended electron diffusion paths and higher recombination rates. These findings underscore the importance of balancing temperature and structural parameters to improve charge transport and minimize losses, particularly for DSSC applications in warm environments.
KERAGAAN ENAM VARIETAS UNGGUL BARU PADI KHUSUS PADA LAHAN SUB OPTIMAL DI KALIMANTAN BARAT Subekti, Agus; Umar, Abdullah
Agros Journal of Agriculture Science Vol 25, No 1 (2023): edisi JANUARI
Publisher : Fakultas Pertanian, Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jpa.v25i1.2426

Abstract

Kebutuhan beras nasional terus mengalami peningkatan seiring dengan pertambahan jumlah penduduk. Selain berfungsi sebagai sumber utama karbohidrat, beras juga menjadi makanan dengan fungsi khusus terutama untuk kesehatan. Konsumsi beras yang memiliki Indeks Glikemik (IG) rendah sebagai makanan pokok dipercaya baik bagi penderita diabetes. Selain itu beras yang memiliki kandungan seng (Zn) dan antioksidan yang tinggi sangat berguna bagi penderita stunting dan gizi buruk. Beberapa varietas unggul baru (VUB) padi khusus hasil inovasi Badan Litbang Pertanian memiliki keunggulan dalam hal aroma, warna, atau kandungan nutrisi untuk mengatasi atau melengkapi kekurangan zat tertentu dalam tubuh. Dengan mempertimbangkan manfaat padi khusus bagi kesehatan, maka perlu dilakukan uji coba VUB padi khusus di Kalimantan Barat. Uji coba ini bertujuan untuk mengidentifikasi keragaan agronomi dan hasil VUB padi khusus pada lahan sub optimal. Metode penelitian menggunakan rancangan acak kelompok, dengan perlakuan berupa enam VUB padi khusus yaitu Arumba, Jeliteng, Baroma, Tarabas, Inpago 13 fortiz, dan Inpari IR Nutri Zinc, dengan lima ulangan. Uji coba Penelitian ini dilaksanakan di Desa Pal IX, Kecamatan Sungai Kakap, Kabupaten Kubu Raya, Kalimantan Barat, dengan jenis tanah Aluvial. Hasil uji coba  menunjukkan bahwa VUB padi khusus Inpari IR Nutri Zinc memiliki produktivitas 4,5 t/ha, produktivitas ini lebih tinggi dan berbeda nyata dibandingkan VUB padi khusus lainnya. VUB padi khusus Inpari IR Nutri Zinc cocok untuk dikembangkan pada lahan sub optimal pasang surut di Kalimantan Barat.
Texture Features of Aglaonema Leaves with Local Binary Pattern Code Nugroho, Agung Tjahjo; Nursulistyono, Yuda; Cahyono, Bowo Eko; Subekti, Agus
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4180

Abstract

The Aglaonema type and quality is difficult to identify due to leaf pattern variety. For this reason, a technique is developed to classify Aglaonema types from leaf images. The Aglaonema is identified using the Local Binary Pattern (LBP) technique. The LBP recognizes objects in the form of pixel neighbor patterns in binary code, which is sensitive to the radius (R) and the number of neighbors (P) pixels. In this article we will study the appropriate radius and number of neighbors so that the LBP code becomes an accurate abject texture attribute. Experimentally, R is varied from 1 to 5 while P is varied from 4 to 24 pixels. Two types of Aglaonema with two varieties taken from each type were used to test the accuracy of the LBP code. The accuracy of the classification results is carried out with the help of K-Nearest Neighbors (KNN). The results show that the greater the number of neighbors in determining the LBP code, the more accurate the classification results. Neighbors with a total of 18 have a stable accuracy reaching a total of 79%. Increasing the number of neighbors does not significantly affect accuracy. The neighbor radius affects the batik type of Aglaonema, the wider the neighbor area, the accuracy increases up to 84%, but for the Lipstick type, the best accuracy is obtained when R=3. By choosing the right R and P, the types of Aglaonema batik and Lipstick can be differentiated well.
Simulasi Komputasional untuk Meningkatkan Efisiensi DSSC Berbasis TiO₂/Cu: Studi Ketebalan dan Suhu Fotoanoda Setyawati, Yuyun; Supriyanto, Edy; Nawafil, Moh.; Subekti, Agus
Jurnal Penelitian Pendidikan IPA Vol 11 No 4 (2025): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i4.10397

Abstract

In order to address the growing energy demands in Indonesia, this study investigates the enhancement of TiO₂/Cu-based Dye-Sensitized Solar Cells (DSSCs) efficiency through computational simulation. The research focuses on the influence of photoanode thickness and operational temperature on the device’s performance. The simulation results revealed that an optimal photoanode thickness of 2.60 μm achieved the highest efficiency of 8.493%, balancing light absorption and electron transport. Additionally, an operational temperature of 350 K was found to yield the maximum efficiency of 9.376%, as higher temperatures reduce electrolyte viscosity, improve ion mobility, and minimize charge recombination. Validation of the simulation model was conducted by comparing it with experimental data from prior studies, ensuring its reliability in representing charge transport phenomena in DSSCs. These findings offer crucial insights for designing cost-effective, efficient, and sustainable DSSCs suitable for Indonesia’s abundant solar energy resources. Further research is recommended to explore the interaction of additional components and external factors to enable commercial scalability of this technology.
VISUAL HISTORICAL DATA-BASED TRAFFIC MOVEMENT AND DENSITY PATTERN EXTRACTION FOR ADAPTIVE PATTERN DETECTION BASE ON VEHICLE TYPE Angellia, Filda; Merlina, Nita; Subekti, Agus; Handayanto, Rahmadya Trias
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1570

Abstract

Traffic congestion in urban areas has become a crucial issue, impacting time efficiency, energy consumption, and quality of life. One of the main causes of difficulties in traffic management is the lack of optimal predictive systems capable of detecting and adaptively responding to vehicle movement patterns. This study proposes a historical digital image-based approach to extract traffic movement patterns and density based on vehicle type and dimensions. The developed model utilizes historical traffic video footage from CCTV systems as a visual data source, which is then processed using the YOLOv5 algorithm to detect the number, size, and type of vehicles. After the detection process, vehicle information is converted into a sequential format that reflects vehicle movement in the temporal dimension. This data is then analyzed using a Long Short-Term Memory (LSTM) model to generate traffic density prediction patterns. This study also compares the performance of LSTM with other algorithms such as Random Forest and XGBoost in terms of prediction accuracy. Model evaluation is conducted using MSE and RMSE metrics to measure accuracy against actual data.The research results show that the integration of dimension-based vehicle detection with a visual historical data-driven prediction approach can improve the accuracy and flexibility of modeling future traffic conditions. This approach significantly contributes to the development of intelligent transportation systems that can adapt to dynamic environmental conditions and traffic patterns
Evaluasi Kinerja Model Machine Learning dalam Cross-Project Defect Prediction Menggunakan Library PyCaret Hidayat, Rian; Subekti, Agus
Techné : Jurnal Ilmiah Elektroteknika Vol. 24 No. 2 (2025)
Publisher : Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31358/techne.v24i2.603

Abstract

Cross Project Defect Prediction (CPDP) is used to overcome the limitation of training data on new projects. This study tests the performance of machine learning models (Random Forest, CatBoost, Logistic Regression, KNN, SVM) in a CPDP scenario with the AEEEM dataset, comparing results before and after hyperparameter adjustment. Models were tested using a one-to-many CPDP architecture, with evaluation metrics of Accuracy, AUC, Recall, Precision, and F1-Score. As a result, Random Forest excels in 9 out of 20 prediction combinations, followed by CatBoost which is best in 4 combinations after tuning. KNN and SVM won in 3 and 2 combinations respectively, while Logistic Regression only excelled in 2 combinations. Hyperparameter tuning improved the performance of all models except Logistic Regression, with SVM improving most significantly (6.39%), followed by KNN (3.94%), RF (5.14%), and CatBoost (1.4%). Project combinations such as LC ? EQ, ML ? EQ, and PDE ? EQ performed well, demonstrating the effectiveness of CPDP when projects are similar. In contrast, combinations such as EQ ? ML and ML ? LC performed poorly due to differences in data distribution. This study concludes that CPDP is effective for software defect prediction when local data is limited, and can be the basis for further research such as transfer learning or project selection based on semantic similarity.
Co-Authors A.A. Ketut Agung Cahyawan W Abdullah Umar, Abdullah Aditya, Dedy Yusuf Agung Tjahjo Nugroho Akhmad Syukron Andra, Muhammad Bagus Ari Setiawan Arumjeni Mitayani Aryono Adhi, Aryono Cahyono, Bowo Eko Devi Wulandari Diantika, Sri Edy Supriyanto Emy Setyaningsih Eni Heni Hermaliani, Eni Heni Faisal, Anas Fatah, Haerul Filda Angellia Heriyani, Novia Hidayat Teguh Wiyono Hiya Nalatissifa Indriyanti Indriyanti, Indriyanti Kahar Muzakhar Khultsum, Umi Kirso, Kirso Kusmayadi, Kusmayadi Kusumah, Maulana S. Lukman, Arif M. Rangga Ramadhan Saelan Mareanus Lase Marta Dinata, Mochamad Mardi MUHAMMAD HARIS Muhammad, Nawafil Nawafil, Moh. Nita Merlina, Nita Nufus, Fina Sifaul Nursulistyono, Yuda Nurul Priyantari Prasetya, Dwi Sabda Budi Purwoko Adhi Rahmadya Trias Handayanto Rian Hidayat Satyawan, Arief Suryadi Setiawan, Boy Setyawati, Yuyun Siti Helmyati Sugara, Bayu Supriyadi Supriyadi Suryanto, Wiwit Wahyudi Wahyudi Winarsa, Rudju