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All Journal JURNAL ILMU PERTANIAN INFOKUM Journal of Computer Networks, Architecture and High Performance Computing
Leni Marlina
Universitas Pembangunan Panca Budi
Agriculture, Biological Sciences & Forestry Computer Science & IT Education

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Respon Pemberian Ekoenzim dan Pupuk Organik Cair Terhadap Pertumbuhan dan Produksi Bawang merah (Allium ascalonicum L) Najla Lubis; M. Wasito; Leni Marlina; Rosmaria Girsang; Hasril Wahyudi
AGRIUM: Jurnal Ilmu Pertanian Vol 25, No 2 (2022)
Publisher : UNIVERSITAS MUHAMMADIYAH SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/agrium.v25i2.10354

Abstract

Tujuan penelitian ini adalah untuk mengetahui respon akibat pemberian Ekoenzim (EE) dan pupuk organik cair (POC) terhadap pertumbuhan dan produksi bawang merah (Allium ascalonicum L.). Metode penelitian ini menggunakan Rancangan Acak Kelompok (RAK) faktorial terdiri dari 2 faktor. Faktor pertama adalah pemberian ekoenzim (EE) yang terbagi menjadi 4 taraf yaitu E0= (kontrol), E1 = 1%, E2= 2%, E3 = 3%. Faktor kedua adalah pemberian POC buah-buahan yang terbagi menjadi 4 taraf yaitu B0 = (kontrol), B1 = 1%; B2 = 2%, B3 = 3%. Parameter pengamatan adalah tinggi tanaman (cm), jumlah daun (helai), jumlah anakan, berat basah umbi per plot, berat kering Umbi per plot. Hasil penelitian menunjukkan bahwa pemberian EE berpengaruh tidak nyata pada semua parameter yang diamati, dimana perlakuan terbaik pada E1 = 1%. Pemberian POC buah-buahan berpengaruh tidak nyata pada parameter tinggi tanaman (cm), jumlah daun (helai), namun berpengaruh sangat nyata pada parameter jumlah anakan, berat basah umbi per plot (g) dan berat kering umbi per plot (g), dimana perlakuan terbaik pada pemberian B3 = 3%. Interaksi antara pemberian Eco enzyme dan POC Buah-buahan berpengaruh tidak nyata pada semua parameter yang diamati.
AN IMPLEMENTATION OF RECOGNITION LETTER AND NUMBER BASED ON MOBILE FOR EARLY CHILDHOOD KINDERGARTEN IT-AL FATIH Heni Wulandari; Suherman Suherman; Leni Marlina
INFOKUM Vol. 10 No. 5 (2022): December, Computer and Communication
Publisher : Sean Institute

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Abstract

An Early childhood education could be defined as all efforts in facilitated a development and learning of children from birth to six years of age through provision of various experiences and stimuli that are developing. Kindergarten (TK) IT AL Fatih is one of schools that educates early childhood, where the school is located at Pelaksanaan I street No.02 steet IV. At the school there is no means of learning children through interactive learning media, in learning to recognize letters and numbers the teacher still uses the lecture method so that the learning process to children can cause boredom and boredom. Interactive learning in the form of audio visual using mobile-learning technology is a learning system needed by early childhood to be responsive and encourage the emergence of teacher innovation and creativity in creating and developing a conducive educational climate in kindergarten IT AL Fatih. The implementation of activities uses an approach method by conducting direct socialization and explaining to teachers and children how the application of letter and number recognition in mobile-based early childhood can increase teacher productivity and increase children's interest in learning. The results of the evaluation during the activity process received very good responses, as evidenced by the questionnaire evaluation, 75% of which stated strongly agree (SS) and 25% stated agree (S).
Utilization of Data Analytics to Enhance Operational Efficiency in Manufacturing Companies Rendi Aprijal; Iqbal Wiranata Siregar; Andysah Putera Utama Siahaan; Leni Marlina
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 2 (2024): Articles Research Volume 6 Issue 2, April 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i2.3723

Abstract

In the digital era, manufacturing industries confront challenges like heightened global competition and intricate production processes, urging them to boost efficiency and productivity. Amidst these circumstances, Big Data emerges as a pivotal opportunity to enhance manufacturing performance. Big Data, characterized by vast volumes of data, utilizes advanced data mining to machine learning techniques for analysis. Data analytics, an interdisciplinary field, profoundly impacts manufacturing operations, enabling deeper insights into production processes. By analyzing production data, companies identify inefficiencies, streamline workflows, and enhance operational efficiency and productivity. Predictive maintenance through sensor data analysis prevents machine failures, while logistics data analysis optimizes supply chains and inventory management, reducing costs and enhancing competitiveness. However, implementing Big Data analytics presents challenges such as rapid data growth, diverse data sources, real-time insights, skill shortages, and data fragmentation. Overcoming these hurdles requires robust technology, skilled personnel, and effective data management strategies. Examples of Big Data analytics applications include customer behavior analysis by Amazon and Netflix, fraud detection in insurance, and urban mobility optimization. Success factors in data analytics implementation include effective data-driven communication, technology integration, and skill enhancement. In conclusion, implementing Big Data Analytics in manufacturing promises significant benefits in operational efficiency, product quality, and competitiveness. Overcoming challenges necessitates robust strategies and consideration of ethical and security issues, ensuring responsible data usage. With a deep understanding of Big Data Analytics, manufacturing companies can leverage this technology to achieve higher efficiency and competitiveness in the global market.
Co-Authors Andysah Putera Utama Siahaan Hasril Wahyudi Heni Wulandari Iqbal Wiranata Siregar M. Wasito Najla Lubis Rendi Aprijal Rosmaria Girsang Suherman Suherman