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All Journal Jurnal Media Infotama Sistemasi: Jurnal Sistem Informasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Menara Ilmu JATI (Jurnal Mahasiswa Teknik Informatika) Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Bulletin of Computer Science Research Journal of Education Research Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Sains dan Teknologi Jurnal Sains Informatika Terapan (JSIT) Jurnal Komtekinfo Indonesian Research Journal on Education Indo Green Journal Jurnal Quancom: Jurnal Quantum Komputer Journal of Information System and Education Development Jurnal Pengabdian Masyarakat Bangsa Indo Green Journal Jurnal TAM (Technology Acceptance Model) Journal of Computer Science Advancements
Hendrik, Billy
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Journal : JOURNAL OF SCIENCE AND SOCIAL RESEARCH

 1 
DAMPAK TEKNOLOGI INFORMASI TERHADAP KECERDASAN EMOSIONAL SISWA SMP: STUDI PERBANDINGAN TAHUN 2016 DAN 2024 Sani, Fadhila Putri; Hendrik, Billy
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3156

Abstract

Abstract: Information technology (IT) has experienced rapid development in recent years, significantly impacting various aspects of life, including education and students' emotional development. This study aims to compare the impact of information technology on the emotional intelligence of Junior High School (SMP) students in 2016 and 2024. This research employs a quantitative method with a survey approach involving 400 junior high school students from the two periods. The findings indicate significant differences in self-awareness, emotion management, empathy, and social skills between the two periods. Although IT has provided benefits in enhancing access to information and communication skills, negative impacts such as reduced direct social interaction and increased digital stress were also identified. This study highlights the importance of adaptive educational strategies to optimize the role of IT in students' emotional intelligence development. Keyword: Information Technology; Emotional Intelligence; Junior High School Students; Comparison of 2016 and 2024 Abstrak: Teknologi informasi (TI) telah mengalami perkembangan pesat dalam beberapa tahun terakhir, memberikan pengaruh yang signifikan terhadap berbagai aspek kehidupan, termasuk pendidikan dan perkembangan emosional siswa. Studi ini bertujuan untuk membandingkan dampak teknologi informasi terhadap kecerdasan emosional siswa Sekolah Menengah Pertama (SMP) pada tahun 2016 dan 2024. Penelitian ini menggunakan metode kuantitatif dengan pendekatan survei terhadap 400 siswa SMP dari dua periode waktu tersebut. Hasil penelitian menunjukkan bahwa terdapat perbedaan signifikan dalam aspek kesadaran diri, manajemen emosi, empati, dan keterampilan sosial siswa antara kedua periode tersebut. Meskipun TI memberikan manfaat dalam meningkatkan akses informasi dan keterampilan komunikasi, dampak negatif seperti penurunan interaksi sosial langsung dan peningkatan stres digital juga teridentifikasi. Studi ini menyoroti pentingnya strategi pendidikan yang adaptif untuk mengoptimalkan peran TI dalam perkembangan kecerdasan emosional siswa. Kata kunci: Teknologi Informasi; Kecerdasan Emosional; Siswa SMP; Perbandingan 2016 dan 2024
PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK SEGMENTASI BERDASARKAN KESIAPAN SELEKSI: SYSTEMATIC LITERATUR REVIEW Muhammad, Imam Fakhri; Hendrik, Billy
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3153

Abstract

Abstract: The application of the K-means clustering algorithm as an innovative method for readiness segmentation, enabling the grouping of individuals based on their preparedness in the selection process. With the background issue of the lack of systematic methods to identify individual readiness, this study aims to develop an effective segmentation model using K-Means. The research method involves collecting relevant data and applying the K-Means algorithm to identify optimal clusters. The results show that the K-Means algorithm successfully grouped individuals into clusters according to their selection readiness, providing strategic insights for decision-makers in conducting a more accurate and efficient selection process. This study makes a significant contribution to the development of more targeted and effective selection strategies. Keyword: Selection Strategy; Readiness-Based Grouping; Data Clustering. Abstrak: Penerapan algoritma K-means clustering sebagai metode inovatif untuk segmentasi kesiapan seleksi, yang memungkinkan pengelompokan individu berdasarkan kesiapan mereka dalam proses seleksi. Dengan latar belakang permasalahan kurangnya metode sistematis untuk mengidentifikasi kesiapan individu, penelitian ini bertujuan untuk mengembangkan model segmentasi yang efektif menggunakan K-Means. Metode penelitian melibatkan pengumpulan data relevan dan penerapan algoritma K-Means untuk mengidentifikasi cluster yang optimal. Hasil penelitian menunjukkan bahwa algoritma K-Means berhasil mengelompokkan individu ke dalam cluster yang sesuai dengan kesiapan seleksi mereka, memberikan wawasan strategis bagi pengambil keputusan dalam proses seleksi yang lebih akurat dan efisien. Penelitian ini memberikan kontribusi signifikan dalam pengembangan strategi seleksi yang lebih tepat sasaran dan efektif. Kata kunci: Strategi Seleksi; Pengelompokan Berdasarkan Kesiapan; Klasterisasi Data. 
PREDIKSI PRODUKTIVITAS LAHAN KELAPA SAWIT PASCA PEREMAJAAN MENGGUNAKAN ALGORITMA MACHINE LEARNING Sukardi, Sukardi; Hendrik, Billy
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3279

Abstract

Abstract: Oil palm land rejuvenation is an essential step in maintaining long-term productivity. However, uncertainty about post-rejuvenation productivity poses a significant challenge for farmers and plantation managers. This study aims to develop a predictive model for oil palm land productivity after rejuvenation using machine learning algorithms. The methods used include historical production data collection, environmental factors, and plant characteristics. The tested algorithms include Linear Regression, Random Forest, and Artificial Neural Network (ANN). The results indicate that the Random Forest model has the highest accuracy in predicting productivity with an R-squared value of 0.87. Implementing this model is expected to support more accurate decision-making in oil palm plantation management. Keyword: Oil Palm; Rejuvenation; Productivity Prediction; Machine Learning Abstrak: Peremajaan lahan kelapa sawit merupakan langkah penting dalam mempertahankan produktivitas jangka panjang. Namun, ketidakpastian mengenai produktivitas pasca peremajaan menjadi tantangan utama bagi para petani dan pengelola perkebunan. Studi ini bertujuan untuk mengembangkan model prediksi produktivitas lahan kelapa sawit pasca peremajaan dengan menggunakan algoritma machine learning. Metode yang digunakan mencakup pengumpulan data historis produksi, faktor lingkungan, serta karakteristik tanaman. Algoritma yang diuji meliputi Regresi Linear, Random Forest, dan Artificial Neural Network (ANN). Hasil penelitian menunjukkan bahwa model Random Forest memiliki akurasi tertinggi dalam memprediksi produktivitas dengan nilai R-squared sebesar 0,87. Implementasi model ini diharapkan dapat membantu pengambilan keputusan yang lebih akurat dalam manajemen perkebunan kelapa sawit. Kata kunci: Kelapa Sawit; Peremajaan; Prediksi Produktivitas; Machine Learning
Co-Authors A'yuni, Qurrata Abdi Juliantho, Dwana Abdi Julianto, Dwana Ade saputra Akbar, Syifa Chairunnissa Deliva Amin Amirul Mukminin, Andi Amri, Yassirli Andi, Muhammad Yusril Haffandi Arby, Willya Aswandi, Nopan Awal, Hasri Budiantoro, Hendro Deti Karmanita Dian Maharani, Dian Febby Olivia, Ladyka Firdaus Firdaus Gevindo, Aprilian Gunadi Widi Nurcahyo Haffandi, Muhammad Yusril Hasibuan, Elpina Sari Dewi Ikhlas, Ariza Indhira, Sonia Karseno, Doni Lubis, Fitri Amelia Sari Lubis, Siti Sahara Mardhiah Masril Muhammad, Imam Fakhri Nasution, Ayu Lestiani Nugraha, Fajri Olivia, Ladyka Febby Raharjo, Tio Doli Resnawita Ridwan, Ridwan Ritna Wahyuni Ruri Hartika Zain Rusydi, Rezki Sahara Lubis, Siti Sani, Fadhila Putri Sari, Ade Puspita Sarjon Defit Sonia Indhira Sovia, Rini Subarja, Roy Efendi Sukardi Sukardi Sumijan Supperianto, Bambang Suri, Melati Rahma Sutri, Ridwan Syafri Arlis Tamin, Zulfiqar Vidyanti, Angela Waruwu, Kalfinus Wira, M Wira Sanjaya Wirdawati, Wira Yuhandri Yuhandri, Y