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PENGARUH PENAMBAHAN ABU SEKAM PADI TERHADAP SEMEN PADA PEMBUATAN BATA BETON PEJAL (STUDI KASUS 0%; 0,5%; 1%; DAN 1,5%) Roy, Roy; Hernadi, Ahmad
Civil Engineering Scientific Journal Vol 3, No 3 (2024): Civil Engineering Scientific Journal
Publisher : Jurusan Teknik Sipil, Fakultas Teknik, Universitas Borneo Tarakan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35334/cesj.v3i3.6196

Abstract

ABSTRACT : Rice husk ash is a waste product obtained from the combustion of rice husk. It contains carbon and silica compounds that influence the strength of concrete. The natural combustion process of rice husk produces active carbon compounds with an amorphous structure and extremely small pore spaces, which can form elongated gaps capable of binding free lime during the cement hydration process. This study aims to investigate the effect of adding rice husk ash as an additive on the compressive strength of solid concrete blocks. The mixture ratio used was 1 part cement to 6 parts sand, with varying proportions of rice husk ash added at 0%, 0.5%, 1%, and 1.5% by cement weight. A total of 120 samples were tested, with 30 samples for each variable. The results show that the average compressive strength of solid concrete blocks (SCB) with 0% rice husk ash is 70.31 kg/cm², classified as quality class II; SCB with 0.5% rice husk ash is 84.97 kg/cm², classified as quality class II; SCB with 1% rice husk ash is 70.32 kg/cm², classified as quality class II; and SCB with 1.5% rice husk ash is 67.57 kg/cm², classified as quality class III. The optimum variation among the mixtures for solid concrete block production is found at 0.5% rice husk ash, achieving a compressive strength of 84.97 kg/cm².Kata kunci : Rich Husk Ash, Solid Concrete Blocks, Compressive Strength ABSTRAK : Abu sekam padi merupakan limbah yang diperoleh dari hasil pembakaran sekam padi. Abu sekam padi mengandung senyawa karbon dan silika yang berpengaruh terhadap kekuatan beton, hasil pembakaran senyawa sekam padi yang alami mengandung senyawa karbon aktif memiliki struktur amorf dan ruang pori yang berukuran sangat kecil dan dapat berbentuk seperti celah panjang yang dapat mengikat kapur bebas pada saat proses hidrasi semen. Penelitian ini bertujuan untuk mengetahui bagaimana pengaruh penambahan abu sekam padi sebagai bahan tambah terhadap kuat tekan bata beton pejal. Perbandingan campuran yang digunakan ialah 1 semen : 6 pasir dengan penambahan variasi presentasi campuran abu sekam padi yaitu 0%; 0,5%; 1%; dan 1,5% terhadap berat semen. Dengan total benda uji sebanyak 120 sampel, dengan setiap variabel sampel masing-masing berjumlah sebanyak 30 sampel. Hasil penelitian ini memperoleh nilai rata-rata kuat tekan BBP 0% sebesar 70,31 kg/cm2 klasifikasi mutu II, BBP 0,5% sebesar 84,97 kg/cm2 klasifikasi mutu II, BBP 1% sebesar 70,32 kg/cm2 klasifikasi mutu II, BBP 1,5% sebesar 67,57 kg/cm2 klasifikasi mutu III. Variasi optimum pada campuran diantara BBP 0%; 0,5%; 1%; dan 1,5% pada pembuatan bata beton pejal yaitu BBP 0,5% dengan nilai kuat tekan sebesar 84,97 Kg/cm².Kata Kunci : Abu Sekam Padi, Bata Beton Pejal, Kuat Tekan
Peran Generative Artificial Intelligence dalam Meningkatkan Efisiensi Proses Pembelajaran di Tingkat Tinggi Wincent Wisely; Aurich Thedis; Roy, Roy; Alkaffy Kaffy Ramba; Evander Banjarnahor
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 6 No. 1 (2026): April 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v6i1.7542

Abstract

The development of Generative Artificial Intelligence (Gen AI) has significantly transformed the learning process, particularly in improving task completion efficiency. This study aims to analyze the effect of Gen AI usage on learning efficiency among high school students and university students. A quantitative approach was employed using a survey of 83 respondents. The variables examined include frequency of use, duration of use, and learning efficiency, which is measured based on task completion time. The results indicate that the level of Gen AI usage is relatively high, with a mean frequency of 3.51 and a mean duration of 3.53, while efficiency shows the highest mean value of 3.94. Regression analysis reveals that the model is statistically significant (p-value < 0.05) with a coefficient of determination of , indicating that 61.18% of the variance in learning efficiency is explained by the model. Partially, frequency of use has a positive and significant effect on efficiency ( ; p-value < 0.05), whereas duration of use is not statistically significant ( ; p-value > 0.05). These findings suggest that usage intensity plays a more critical role than usage duration. Overall, Gen AI is shown to enhance learning efficiency; however, its effectiveness depends on how users actively and appropriately engage with the technology.