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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal Of Management Science (JMAS) Educator : Directory of Elementary Education Journal Journal of Principles Management and Bussines
Rusdi, Wahyudi
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Arts Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Mathematics Physics Social Sciences

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KEGIATAN EKSTRAKURIKULER PRAMUKA DAN PENGARUHNYA TERHADAP KECERDASAN EMOSIONAL SISWA Dullah, Bayu Saputra; Rusdi, Wahyudi
EDUCATOR (DIRECTORY OF ELEMENTARY EDUCATION JOURNAL) Vol. 2 No. 2 (2021): EDUCATOR (DIRECTORY OF ELEMENTARY EDUCATION JOURNAL)
Publisher : RUMAH JURNAL - LP2M IAIN SULTAN AMAI GORONTALO JURUSAN PENDIDIKAN GURU MADRASAH IBTIDAIYAH (PGMI) FAKULTAS ILMU TERBIYAH DAN KEGURUAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54045/educator.v2i2.414

Abstract

Penelitian ini merupakan penelitian kuantitatif dengan tujuan penelitian Untuk mengetahui apakah terdapat pengaruh signifikan antara Kegiatan Ekstrakurikuler Pramuka terhadap Kecerdasan Emosional siswa di SD Islam Terpadu Lukmanul Hakim Gorontalo dan untuk mengetahui seberapa besar pengaruh kegiatan ekstrakurikuler pramuka terhadap kecerdasan emosional siswa di SD Islam Terpadu Lukmanul Hakim Gorontalo. Dalam penelitian ini peneliti menggunakan angket (kuesioner) dalam mendapatkan dan mengumpulkan data. Terdapat 34 item pertanyaan dalam angket tersebut. Jumlah sampel sebanyak 32 siswa. Dari penelitian ini dapat dilihat Kecerdasan Emosional Siswa dipengaruhi oleh Kegiatan Ekstrakurikuler Pramuka, dengan persamaan regresi yang terdapat pada penelitian ini adalah Y = 30.428 + 0.507 X.. Signifikansinya teriihat dari t hitung sebesar 3.071 dan nilai t tabel (df=32-2) adalh 2.0422 sehingga t hitung > t tabel (3.071>2.0422) dan Sig < 5% (0.005 < 0.05). Melalui uji R2, dapat diketahui Kecerdasan Emosional Siswa di Sekolah Dasar Islam Terpadu Lukmanul Hakim Gorontalo dipengaruh oleh variabel Kegiatan Ekstrakurikuler Pramuka sebesar 23.9%, sedangkan sisanya 76.1% Kecerdasan Emosional Siswa ditentukan oleh faktor lain.
Inovasi Terbuka Pada UKM : Kondisi Saat Ini dan Pengembanganya (Tinjauan Bibliometrik Menggunakan VOSviwer) Rusdi, Wahyudi
Journal of Principles Management and Business Vol. 1 No. 02 (2022): Journal of Principles Management and Bussines
Publisher : Scimadly Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55657/jpmb.v1i02.74

Abstract

The company's open innovation is seen as a result of the availability of complementary resources and transformative capacities that provide critical support. This study aims to systematically analyze the characteristics of the study of open innovation in the scope of SMEs by using data accessed from the Scopus online database by looking at two keywords, namely open innovation and SMEs. This study uses 682 articles and is filtered based on journal requirements between 2008 and 2021 as many as 200 articles. This study answers two critical research questions. First, a bibliometric analysis to answer research questions about how many articles are currently discussing SME Open Innovation Research Trends. This study answers two critical questions in this study. First, bibliometric analysis was used to answer the research question of how many articles currently cover Research Trends in SME Open Innovation. Publications related to open innovation have steadily increased over the past decade. In 2017 and 2021, publications hit a 14-year high. The most cited article is Open Innovation in SMEs: Trends, Motives and Management Challenges by Van de Vrande et al. (2009), with 1,1359 citations. The most influential authors, Van de Vrande et al. (2009), the most influential with 1,359 and followed by Lee et al. (2010) with 886 citations.
Maximizing Returns: The Impact of Key Ratios on Bank Mega Syariah's ROA Najib, Intan Permatasari; Ajuna, Luqmanul Hakiem; Rusdi, Wahyudi; Kadim, Immawan Muhajir
Journal of Principles Management and Business Vol. 3 No. 02 (2024): October 2024
Publisher : Scimadly Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55657/jpmb.v3i02.184

Abstract

This study investigates the factors influencing Return on Assets (ROA) at PT. Bank Mega Syariah, focusing on Non-Performing Financing (NPF), Financing to Deposit Ratio (FDR), and Operating Costs to Operating Income (BOPO). The research utilizes quarterly financial reports from PT. Bank Mega Syariah for the 2016–2023 period and applies a quantitative research approach. Data analysis includes classical assumption testing, multiple linear regression analysis, and hypothesis testing. The classical assumption test confirms that the data meets the requirements for multiple linear regression modeling. The hypothesis testing reveals that NPF has a significant positive effect on ROA, with a p-value of 0.007 (< 0.05) and a t-value of 2.894. Conversely, FDR, with a p-value of 0.308 (> 0.05) and a t-value of 1.038, shows no significant effect on ROA despite its positive direction. BOPO demonstrates a significant negative effect on ROA, with a p-value of 0.000 (< 0.05) and a t-value of -5.374. Additionally, the F-test results indicate a significant simultaneous effect of NPF, FDR, and BOPO on ROA, with a p-value of 0.000 (< 0.05). These findings highlight the importance of efficient cost management and asset quality in enhancing profitability, while FDR requires further exploration for its potential role in financial performance.
Building consumer trust through live streaming: A study of fashion purchase behavior Larasati, Suci; Aisyah, Mitra Riani; Habie, Riska Octavia; Rusdi, Wahyudi
Junal Ilmu Manajemen Vol 8 No 3 (2025): July: Management Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jmas.v8i3.704

Abstract

In recent years, live streaming has emerged as a transformative force in the digital commerce landscape, particularly within the fashion industry. This study aims to analyze the effect of live streaming on consumer purchasing behavior, with trust as a mediating variable. This research uses a quantitative approach, with data collected through questionnaires distributed to 276 respondents in Gorontalo Province, who are active consumers in purchasing fashion products through live streaming services such as Shopee Live and TikTok Live. The analysis was carried out using SmartPLS 3 software to test the validity, reliability, and structural relationships between variables. The results reveal three key findings: (1) live streaming exerts a significant and positive direct influence on purchase decisions; (2) live streaming significantly enhances consumer trust; and (3) trust itself significantly predicts purchase decisions. These findings underscore the dual function of live streaming as both a transactional and relational tool in online shopping contexts. Theoretically, the study enriches the literature by integrating real-time interactive media into trust-based consumer behavior models. Practically, the findings offer strategic insights for digital marketers and e-commerce platforms seeking to optimize live streaming as a trust-building and conversion-enhancing mechanism. These findings strengthen previous literature and emphasize the importance of interaction quality in live streaming-based digital marketing strategies. This research provides strategic implications for fashion businesses to optimize live-streaming features in building customer trust.
Perbandingan ANN, Random Forest, dan XGBoost dalam Klasifikasi Antibiotik dengan Penerapan metode Sampling Saputra Rusdi, Edy; RUSDI, EDY SAPUTRA; Siddik, A. Muh. Amil; Aris, Naimah; Ardiansyah Asrifah, Muhammad; Syahrir, Nur Hilal A.; Rangkuti, Aidawayati; Rusdi, Wahyudi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 4: Agustus 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.124

Abstract

Banyak obat potensial telah ditemukan dari produk alami laut (Marine Natural Product). Hal ini menunjukkan bahwa senyawa laut merupakan sumber penting dalam pengembangan dan penemuan obat. Meskipun banyak senyawa laut yang menunjukkan aktivitas biologis tertentu, hanya sedikit yang tercatat sebagai senyawa antibakteri. Oleh karena itu, menemukan senyawa yang berpotensi sebagai senyawa antibakteri dari organisme laut masih menjadi tantangan. Tujuan dari penelitian ini adalah untuk memanfaatkan pendekatan komputasi untuk menemukan senyawa antibakteri dari produk alami laut yang berpotensi menjadi obat. Penelitian ini berfokus pada penggunaan model Artificial Neural Network (ANN), Random Forest, dan XGBoost untuk melakukan klasifikasi berdasarkan kemiripan kimiawi antara senyawa produk alami laut di Indonesia dengan senyawa antibakteri. Untuk mengatasi ketidakseimbangan data, digunakan teknik resampling berupa SMOTE dan undersampling (US). Hasil penelitian menunjukkan bahwa akurasi XGBoost + SMOTE memiliki nilai yang paling tinggi, yaitu 98.89%, mengungguli model ANN 97.57%, Random Forest  (RF) 97.06%, serta model dengan resampling lain seperti ANN+SMOTE 98.67% dan RF + SMOTE 98.59%. Sementara itu, penerapan teknik undersampling menyebabkan penurunan akurasi secara signifikan, di mana XGBoost + US, RF + US, dan ANN + US masing-masing hanya mencapai 91.12%, 91.59%, dan 87.85%. Dari 73 senyawa biota laut, hanya senyawa yang memiliki CID 101767277 yang diprediksi sebagai senyawa yang potensial sebagai antibakteri.   Abstract Many potential drugs have been discovered from marine natural products. This suggests that marine compounds are essential in drug development and discovery. Although many marine compounds exhibit certain biological activities, only a few have been recorded as antibacterial compounds. Therefore, finding compounds with potential as antibacterial compounds from marine organisms remains a challenge. This paper aims to utilize computational approaches to discover antibacterial compounds from marine natural products that have the potential to become drugs. This research focuses on the use of Artificial Neural Network (ANN), Random Forest (RF), and XGBoost models to perform classification based on chemical similarity between compounds of marine natural products in Indonesia and antibacterial compounds. To overcome data imbalance, resampling techniques such as SMOTE and undersampling (US) were used. The results showed that the accuracy of XGBoost + SMOTE has the highest value, which is 98.89%, outperforming the ANN model 97.57%, Random Forest (RF) 97.06%, as well as models with other resampling such as ANN+SMOTE 98.67% and RF + SMOTE 98.59%. Meanwhile, the application of undersampling techniques caused a significant decrease in accuracy, where XGBoost + US, RF + US, and ANN + US only reached 91.12%, 91.59%, and 87.85%, respectively. Of the 73 marine biota compounds, only compounds that have CID 101767277 are predicted as potential antibacterial compounds.
Co-Authors Aisyah, Mitra Riani Ajuna, Luqmanul Hakiem Aliu, Revaldi Ardiansyah Asrifah, Muhammad Dullah, Bayu Saputra Edy Saputra Rusdi Habie, Riska Octavia Kadim, Immawan Muhajir Larasati, Suci Naimah Aris Najib, Intan Permatasari Rangkuti, Aidawayati Saputra Rusdi, Edy Siddik, A. Muh. Amil Syahrir, Nur Hilal A.