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All Journal AL-USWAH: Jurnal Riset dan Kajian Pendidikan Agama Islam AGARICUS: Advances Agriculture Science & Farming SmartComp
Ma'ruf, Imam
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Agriculture, Biological Sciences & Forestry Computer Science & IT Education Electrical & Electronics Engineering

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Pengaruh Intensitas Bermain Game Online Terhadap Hasil Belajar PAI Peserta Didik Generasi Milenial di SMP Nurul Amal Palembang Ma'ruf, Imam; Tauhid, Imam; Hasanah, Laila Rahmi; Purnomo, Mulyadi Eko; Oviyanti, Fitri
AL-USWAH: Jurnal Riset dan Kajian Pendidikan Agama Islam Vol 7, No 2 (2024): JULI-DESEMBER 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/au.v7i2.35466

Abstract

Online games which are currently popular have indirectly made students focus more on online games or games on their smartphones compared to studying, and this is a concern because it can affect student learning outcomes. This research aims to find out and analyze how much intensity students play online games and to find out the effect of the intensity of playing online games on student learning outcomes at SMP Nurul Amal Palembang. This research is a quantitative research type with a sample size of 57 students. The results of the research that has been conducted obtained data that the intensity of playing online games as many as 1 person or 2% got the high category, 53 people or 90% got the medium category and 4 people or 8% got the low category. then the final semester grades in the Islamic Religious Education subject that got the high category were 2 people or 4%, those who got the medium category were 48 people or 84% and those who got the low category were 7 people or 12%. So it can be concluded that the intensity of playing online games has a significant influence on the learning outcomes of millennial generation students of SMP Nurul Amal Palembang. 147
Organoleptic Test of Chicken Sausage Made from Mocaf with The Addition of Moringa Leaves (Moringa oleifera) Ma'ruf, Imam; Chusnah, MIftachul; Hartanti, Dyah Ayu Sri
AGARICUS: Advances Agriculture Science & Farming Vol. 5 No. 2 (2025): October
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/agaricus.v5i2.6045

Abstract

This study aims to analyze the effect of adding moringa leaf extract (Moringa oleifera) on the organoleptic characteristics of chicken sausages based on mocaf flour (Modified Cassava Flour). The research design used was a Completely Randomized Design (CRD) with three treatments: the addition of 5 gr (P1), 10 gr (P2), and 15 gr (P3) of moringa leaf extract, each with three replications. The research method used in this study was descriptive qualitative which was continued with ANOVA test and 5% BNT test. The results showed that treatment P2 (10 gr) produced the highest score on all organoleptic parameters. The color of the sausage looks more attractive, the aroma is fresher, the most preferred taste, and the texture is chewy and soft. Meanwhile, P3 produces a color that is too thick and the aroma tends to be unpleasant so it is less preferred. P1 showed quite good results but not optimal. Based on these results, the addition of 10 gr of moringa leaf extract is the best formulation to improve the sensory quality of mocaf chicken sausages and has the potential as an innovation in functional food products accepted by consumers.
Implementasi Algoritma Support Vector Machine dan Randoom Forest Terhadap Analisis Sentimen Masyarakat Dalam Penggunaan Aplikasi Tiket.com, Traveloka, dan Agoda Pada Google Playstore Prabowo, Calleb Bhaskoro; Hermanto, Teguh Iman; Ma'ruf, Imam
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 13, No 1 (2024): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v13i1.5378

Abstract

Internet hadir sebagai elemen penting dalam menyokong perkembangan teknologi dan informasi dalam segala sektor aktifitas manusia. Pada sektor perdagangan dan pariwisata contohnya, aplikasi Tiket.com, Traveloka, dan Agoda menjadi aplikasi yang paling diminati masyrakat Indonesia saat ini. Ulasan atau review yang disematkan oleh para pengguna merupakan hal penting bagi pihak perusahaan untuk mengetahui kepuasan pelanggan yang nantinya digunakan untuk meningkatkan kualitas dalam segi pelayanan. Proses menganalisis ulasan komentar memiliki beberapa tahapan karena memiliki data yang jumlahnya tidak sedikit. Penggunaan suatu metode membantu dalam melakukan proses klasifikasi komentar yang bersifat positif atau negatif. Ulasan pengguna aplikasi yang diproses diambil dari platform layanan penyedia aplikasi Google Playstore, lalu menarik data yang diinginkan dengan mamasukan library Google Scraper pada Python. Data yang sudah ditarik selanjutnya diberi label untuk memisahkan ulasan yang bersifat positif dan negatif hal ini bertujuan untuk mepermudah proses klasifikasi dengan menggunakan metode Support Vector Machine (SVM) dan Random Forest. Hasil yang didapatkan nantinya merupakan tingkat akurasi dari dua metode yang digunakan berdasarkan pengolahan data yang sudah dilakukan pada masing-masing ulasan yang menjadi data set pada setiap aplikasi. Support Vector Machine memiliki akurasi yang lebih baik dibandingkan dengan Random Forest dengan rincian 85,5%, 87%, dan 88,7% pada urutan aplikasi Tiket.com, Traveloka, dan Agoda. Sedangkan Random Forest memiliki akurasi 84.7%, 84.7%, dan 88.2% dengan urutan aplikasi yang sama.
Co-Authors Chusnah, Miftachul Fitri Oviyanti Hartanti, Dyah Ayu Sri Hasanah, Laila Rahmi Hermanto, Teguh Iman Mulyadi Eko Purnomo, Mulyadi Eko Prabowo, Calleb Bhaskoro Tauhid, Imam