Claim Missing Document
Check
Articles

Found 16 Documents
Search

Kinerja Produksi Ikan Nila Salin dengan Sistem Budidaya Bioflok pada Kolam Terpal di Daerah Istimewa Yogyakarta Muktitama, Asih Makarti; Hendra, Diduk Kristina; Kusuma, Yoga Feri; Lazuardi, Bimastya; Kuswandi, Agasthya; Nugrahawati, Anis; Taufik, Imam; Kurniawan, Arga
Jurnal Salamata Vol 7, No 1 (2025): Juni 2025
Publisher : Politeknik Kelautan dan Perikanan Bone

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/salamata.v7i1.15424

Abstract

Penelitian ini bertujuan untuk menganalisis kinerja pertumbuhan ikan nila salin yang dibudidaya dengan sistem bioflok. Karena sistem bioflok dinilai dapat menghemat penggunaan pakan, meningkatkan produktivitas budidaya, menghemat penggunaan air, dan dapat dilakukan dengan menggunakan kolam terpal atau kolam bulat. Ikan nila salin yang digunakan memiliki bobot rata-rata 10,6±0,48 gram. Penelitian ini dilakukan selama 90 hari. Penelitian ini dilakukan dengan 2 perlakuan, yaitu perlakuan A (pemeliharaan nila salin dengan sistem bioflok) dan perlakuan B (pemeliharaan nila salin tanpa sistem bioflok). Masing masing perlakuan memiliki 7 ulangan. Data yang diperoleh selama penelitian selanjutnya diuji statistika mengunakan SPSS versi 16.1 sedangkan uji T-Test digunakan untuk mengetahui apakah terdapat pengaruh antara perlakuan yang diberikan. Berdasarkan uji statisika diketahui bahwa laju pertumbuhan bobot rata-rata ikan antara perlakuan A dan B adalah tidak berbeda nyata. Sedangkan untuk rasio konversi pakan dan tingkat kelangsungan hidup memiliki hasil yang bebeda nyata, dimana perlakuan A lebih baik dari pada perlakuan B dengan nilai rasio konversi pakan perlakuan A sebesar 1,06 dan tingkat kelangsungan hidup 98%. Berdasarkan hasil penelitian ini maka budidaya nila salin sebaiknya dilakukan dengan sistem bioflok agar dapat menghemat pengunaan pakan dan tingkat kelangsungan hidup yang lebih baik.This study aims to analyze the growth performance of saline tilapia fish cultivated with the biofloc system. Because the biofloc system is considered to be able to save feed usage, increase cultivation productivity, save water usage, and can be done using tarpaulin ponds/circular ponds. The saline tilapia fish used had an average weight of 10.6 ± 0.48 grams. This study was conducted for 90 days. This study was conducted with 2 treatments, namely treatment A (maintenance of saline tilapia fish with a biofloc system) and treatment B (maintenance of saline tilapia fish without a biofloc system). Each treatment has 7 replications. The data obtained during the study were then tested statistically using SPSS version 16.1, while the T-Test was used to determine whether there was an effect between the treatments. This indicates that the growth performance of saline tilapia fish in treatment A and treatment B was not significantly different. Meanwhile, for the feed conversion ratio and survival rate, the results were significantly different, where treatment A was better than treatment B with a feed conversion ratio value of treatment A of 1.06 and a survival rate of 98%. Based on the results of this study, saline tilapia cultivation should be carried out with a biofloc system to save feed usage and achieve a better survival rate.
IMPROVING THE QUALITY OF EDUCATION THROUGH TEACHER COMPETENCY DEVELOPMENT: A COMPARATIVE STUDY IN INDONESIA AND MALAYSIA Taufik, Imam; Hidayatulloh, Hidayatulloh; Rindaningsih, Ida; Zuhro, Sofiatuz; Mahmud, Wan Marfazila Wan; Hairani, Ezza
Academic Journal Research Vol. 3 No. 2 (2025): Academic Journal Research
Publisher : Antis Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/acjoure.v3i2.374

Abstract

Objective: This study aims to conduct a comparative analysis of teacher competency development policies in both Indonesia and Malaysia and identify challenges and supporting factors for their implementation. Method: The method used is a literature review, analyzing policy documents, scientific journals, and official reports. Results: The results indicate that Indonesia emphasizes a decentralized approach through the Merdeka Belajar program and teacher certification, but still faces challenges in access to training and quality equity. Meanwhile, Malaysia implements a centralized approach through the Institut Pendidikan Guru (IPG) and the Program Pembangunan Profesional Berterusan (CPD), with systematic support for technology integration. Both countries face similar challenges, such as infrastructure limitations in remote areas. Novelty: This study recommends strengthening regional cooperation, exchanging best practices, and increasing policy flexibility to address local needs.
Rancang Bangun Aplikasi (Point of Sales) Berbasis Website Menggunakan Framework Laravel dengan Metode Menggunakan Prototype Taufik, Imam; Ichwani, Arief
Majalah Ilmiah METHODA Vol. 14 No. 2 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No2.pp261-267

Abstract

BO'Coffee is a business in the culinary sector where every day there are buying and selling transactions which of course record all types of sales transactions. The operational system used still uses manual methods which are considered vulnerable to errors in ordering and payment. This research uses the Laravel framework based on the prototype method. The aim is to increase operational efficiency through digitizing transaction processes and stock management. The prototype method was chosen because of its ability to develop iteratively and be responsive to user needs. The designed application offers convenience in managing transactions, monitoring inventory and real-time financial reporting. Test results show significant improvements in transaction time efficiency and data accuracy, supporting more effective decision making, the application functions well in all aspects tested, and all expected features can operate in accordance with the design and specifications that have been determined.
Tren yang Muncul dalam Analisis Big Data: Peluang untuk Intelijen Bisnis Laksono, Agung; Taufik, Imam; Andana, Erie Kresna; Setiawan, Heri Aji; Hadityo, Catur Hendro
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 3 No. 3 (2022)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v3i3.2891

Abstract

Analisis Big Data telah menjadi fokus utama dalam dunia bisnis untuk mengungkap pola, tren, dan wawasan yang berharga dari jumlah data yang besar dan kompleks. Artikel ini bertujuan untuk mengeksplorasi tren yang muncul dalam analisis Big Data serta peluang yang dihadirkannya bagi intelijen bisnis. Metode kualitatif digunakan untuk menelaah dan menganalisis studi literatur melalui library research. Hasil penelitian menunjukkan bahwa terdapat beberapa tren yang muncul dalam analisis Big Data, termasuk penggunaan teknik analisis data canggih seperti machine learning dan data mining, integrasi sumber data yang beragam, dan peningkatan fokus pada analisis real-time. Selain itu, artikel ini juga mengidentifikasi berbagai peluang yang ditawarkan oleh analisis Big Data dalam konteks intelijen bisnis, seperti kemampuan untuk meramalkan tren pasar, mendeteksi anomali, dan meningkatkan pengambilan keputusan berbasis data. Dengan memanfaatkan tren ini, perusahaan dapat mengoptimalkan strategi bisnis mereka, meningkatkan efisiensi operasional, dan menciptakan nilai tambah bagi pelanggan mereka. Namun, tantangan seperti privasi data, keamanan informasi, dan keterbatasan infrastruktur teknologi juga perlu diatasi agar implementasi analisis Big Data dapat sukses.
Analisis kinerja algoritma keamanan pada jaringan komputer (Studi kasus: SMK YP 17-1 Malang) Tridianto, Angga; Taufik, Imam; Izzati, Afifah Nurul; Adipradana, Candra
Ruang Cendekia : Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 1 (2025): Ruang Cendekia : Jurnal Pengabdian Kepada Masyarakat
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/yst5jq80

Abstract

Penelitian ini bertujuan untuk menganalisis kinerja algoritma keamanan pada jaringan komputer, dengan fokus pada efektivitas deteksi dan pencegahan serangan flooding menggunakan Intrusion Detection System (IDS) berbasis Snort. Penelitian dilaksanakan di Laboratorium Jaringan Komputer SMK YP 17-1 Malang, yang kerap mengalami ancaman keamanan nyata. Metode yang digunakan adalah eksperimen kuantitatif dengan simulasi serangan flooding terhadap server web dalam jaringan lokal tertutup. Data dikumpulkan melalui observasi langsung, pencatatan log Snort, dan analisis paket menggunakan Wireshark. Hasil penelitian menunjukkan bahwa Snort efektif mendeteksi serangan dengan tingkat akurasi tinggi, mampu membedakan lalu lintas normal dan anomali, serta mempertahankan stabilitas server di bawah tekanan serangan. Faktor-faktor seperti konfigurasi jaringan, pemilihan algoritma kriptografi (RSA, AES, dan DES), serta efisiensi penggunaan sumber daya berpengaruh signifikan terhadap performa sistem. Rekomendasi pengembangan mencakup pembaruan rules IDS secara berkala dan penerapan machine learning untuk meningkatkan deteksi ancaman. Penelitian ini diharapkan menjadi referensi dalam memperkuat keamanan jaringan terhadap ancaman siber yang semakin kompleks.
Exploring Multimodal AI Frameworks for Real‑Time Decision Making in Edge Devices Darmin, Darmin; Taufik, Imam; Miswadi, Miswadi; Kustiyono, Kustiyono; Saleh, Sahlan M.
Jurnal Ar Ro'is Mandalika (Armada) Vol. 6 No. 2 (2026): JURNAL AR RO'IS MANDALIKA (ARMADA)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/armada.v6i2.6057

Abstract

The rapid advancement of Artificial Intelligence (AI) and edge computing has driven the demand for intelligent systems capable of real-time decision making under limited computational resources. In particular, multimodal AI, which integrates heterogeneous data sources such as visual, audio, and sensor signals, plays a crucial role in enhancing contextual awareness and decision accuracy at the edge. This study aims to explore and conceptualize a multimodal AI framework that supports real-time decision making on edge devices while addressing challenges related to resource constraints, data privacy, and decision transparency. The research adopts a qualitative literature review approach, employing a Systematic Literature Review (SLR) method to analyze relevant studies published between 2018 and 2025. Data were collected from reputable academic databases and analyzed using thematic content analysis to identify key architectural components, fusion strategies, optimization techniques, and privacy-preserving mechanisms. The findings indicate that hybrid multimodal fusion, combined with model compression, dynamic inference, and federated learning, significantly improves efficiency, privacy protection, and explainability in edge-based AI systems. This study contributes a comprehensive conceptual framework that can guide future development and deployment of adaptive, efficient, and trustworthy multimodal AI solutions for real-time edge intelligence applications.