Articles
<![CDATA[The Effectiveness of Probiotics to Increase the Growth of Freshwater Barramundi (Lates Calcarifer) Seeds ]]>
<![CDATA[Ranim, Yenfi Riza]]>;
<![CDATA[Salamah, Salamah]]>;
<![CDATA[Rusydi, Rachmawati]]>;
<![CDATA[Mahdaliana, Mahdaliana]]>;
<![CDATA[Mainisa, Mainisa]]>
<![CDATA[ Jurnal Ilmiah Samudra Akuatika Vol 6 No 2 (2022): Jurnal Ilmiah Samudra Akuatika ]]>
Publisher : <![CDATA[Fakultas Pertanian Universitas Samudra ]]>
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DOI: 10.33059/jisa.v6i2.7323
<![CDATA[This study aims to determine the effect of the effectiveness of giving probiotic for increasing the growth and digestibility of freshwater barramundi seed feed. The research was conducted on January 29 - February 28 2022 at the Kembang Tani Farm Lancang Barat Hacthery, North Aceh. The experimental research method used a non-factorial Completely Randomized Design (CRD) with 4 treatments with 3 replications, namely Treatment A: Probiotic EM4 0 ml/kg feed, Treatment B: 9 ml/kg feed, Treatment C 12 ml/kg feed and Treatment D: 15 ml/kg feed. The best length gain was found in treatment D 2.36 cm. The best weight gain in treatment D was 1.91 grams. The best FCR in treatment D 1.5. Best survival in treatment D 86.67%.]]>
<![CDATA[The Addition of Lamtoro Leaf Fermented (Leucaena leucocephala) in Artificial Feed Against the Growth of Milkfish (Chanos chanos) ]]>
<![CDATA[Harefa, Fendi Saputra]]>;
<![CDATA[Khalil, Munawwar]]>;
<![CDATA[Salamah, Salamah]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Mahdaliana, Mahdaliana]]>
<![CDATA[ Jurnal Ilmiah Samudra Akuatika Vol 7 No 2 (2023): Jurnal Ilmiah Samudra Akuatika ]]>
Publisher : <![CDATA[Fakultas Pertanian Universitas Samudra ]]>
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DOI: 10.33059/jisa.v7i2.8956
<![CDATA[Milkfish is a leading commodity for Indonesian mariculture which is quite promising, so milkfish productivity must be increased. The problematic factor in cultivating milkfish is feed. Lamtoro leaves (Leucaena leucocephala) are a potential biological resource and have high protein content as a raw material for making feed. However, lamtoro has a high fiber content which can be reduced by fermenting using bio intan tani and attractants to cover the aroma of lamtoro which fish do not like. This research aims to test the effect of adding fermented lamtoro leaves to artificial feed on the growth of milkfish. The research was carried out on March 22 - April 22 2022 at Kembang Tani Farm Lancang Barat, North Aceh, Aceh. The research used a non-factorial Completely Randomized Design (CRD) consisting of 4 treatments and 3 replications, Treatments A, B, C and D with concentrations of 0%, 15%, 20% and 25% respectively. Based on the F test analysis (ANOVA), the results gave a significant effect on feed response, weight gain, length increase, aroma with a Sig value < 0.05 and gave results that had no real effect on survival rate and feed conversion value with a Sig value > 0. 05.]]>
<![CDATA[Penggunaan Triptofan dalam Pakan untuk Menurunkan Kanibalisme Ikan Kakap Putih (Lates calcarifer) ]]>
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Juliana, Juliana]]>;
<![CDATA[Khalil, Munawwar]]>;
<![CDATA[Mahdaliana, Mahdaliana]]>;
<![CDATA[Salamah, Salamah]]>
<![CDATA[ Jurnal Laot Ilmu Kelautan Vol 6, No 1 (2024): Jurnal Laot Ilmu Kelautan ]]>
Publisher : <![CDATA[Universitas Teuku Umar ]]>
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DOI: 10.35308/jlik.v6i1.9561
<![CDATA[White snapper (Lates calcarifer) is one of the leading marineculture commodities in Indonesia, snapper has a relatively faster growth and has high economic value. One of the factors that cause failure in snapper cultivation in Indonesia is the high level of cannibalism in fish fry. The purpose of this study was the addition of tryptophan to feed whether it affected the level of cannibalism, growth and survival of white snapper. This study used a non-factorial completely randomized design (CRD) method consisting of 4 treatments and 3 replications. The treatments used were Treatment A (control), B (Tryptophan 1%/kg feed), C (Tryptophan 1.5 %/kg feed), D (Tryptophan 2%/kg feed. The lowest cannibalism of snapper was found in treatment B (Tryptophan 1%/kg of feed) with a cannibalism rate of 35.7% and a survival rate of 56.67%.]]>
<![CDATA[Strategi Pemasaran Pakan Ikan Buatan Berbahan Baku Lokal Daun Kelor Di Gampong Reuleut Timur Kecamatan Muara Batu ]]>
<![CDATA[Riani, Riani]]>;
<![CDATA[Rusydi, Rachmawati]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Salamah, Salamah]]>;
<![CDATA[Adhar, Saiful]]>
<![CDATA[ Jurnal Pengabdian Masyarakat: Darma Bakti Teuku Umar Vol 4, No 2 (2022): Juli-Desember ]]>
Publisher : <![CDATA[Universitas Teuku Umar ]]>
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DOI: 10.35308/baktiku.v4i2.5642
<![CDATA[Moringa leaf-based fish feed is feed that is processed by pond farmers in Gampong Reuleut Timur, Muara Batu District, North Aceh, using Moringa leaf raw materials that have good nutritional content and are in accordance with fish needs. This feed is relatively cheap with protein content that meets the needs of fish. However, the feed has not been able to reach a wide market. This is due to the lack of knowledge of farmers about marketing strategies. The service team, through community service activities, aims to provide counseling about marketing strategies for artificial fish feed. Service activities were carried out in Gampong Reuleut Timur, Muara Batu District, North Aceh Regency. Extension activities were carried out by presenting material on the 4P marketing strategy, namely product, price, place, and promotion, and distributing questionnaires to participants to evaluate their understanding of the material. The result of this activity is the increased understanding and knowledge of partners about the 4P marketing strategy, with the hope that later it will be applied to the business that has been occupied in order to obtain maximum profit.<img 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]]>
<![CDATA[Pelatihan Penulisan Brosur Promosi Wisata dalam Bahasa Inggris untuk Siswa SMK Negeri 1 Takengon, Aceh Tengah ]]>
<![CDATA[Rizki, Dini]]>;
<![CDATA[Al Usrah, Cut Rizka]]>;
<![CDATA[Kurniawati, Kurniawati]]>;
<![CDATA[Muarif, Agam]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Sari, Dewi Kumala]]>;
<![CDATA[Fariadi, Dedi]]>;
<![CDATA[Kamil, Ade Ikhsan]]>;
<![CDATA[Mujiburrahman, Mujiburrahman]]>
<![CDATA[ Jurnal Solusi Masyarakat (JSM) Vol 2, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Malikussaleh ]]>
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DOI: 10.29103/jsm.v2i1.13541
<![CDATA[Kota Takengon merupakan salah satu kota destinasi wisata yang ada di Provinsi Aceh. Pariwisata yang dikembangkan di kota Takengon meliputi wisata alam Danau Lut Tawar dan agrowisata. Saat ini, Kota Takengon memiliki banyak pengunjung yang bertujuan untuk menikmati panorama alam dan hasil perkebunan kopi dan buah-buahan di Kota Takengon. Namun, banyaknya jumlah wisatawan yang berkunjung ke kota wisata ini masih didominasi oleh wisatawan lokal dan nasional. Jika dibandingkan dengan beberapa Kota dan Kabupaten lain di Aceh yang juga merupakan destinasi wisata, Kota Takengon masih memiliki jumlah kunjungan wisatawan mancanegara yang relatif sedikit. Kesiapan masyarakat dan pelaku usaha pariwisata di Kota Takengon untuk melakukan promosi dan menerima wisatawan mancanegara masih perlu dtingkatkan, baik dari aspek kemampuan berkomunikasi dalam bahasa asing, maupun standar pelayanan. SMKN 1 Takengon merupakan salah satu SMK di Kota Takengon Kabupaten Aceh Tengah yang memiliki Program Keahlian Usaha Perjalanan Wisata. SMK N 1 Takengon diharapkan dapat menghasilkan sumber daya manusia yang kompeten dalam bidang pariwisata yang nantinya akan berkontribusi pada peningkatan jumlah wisatawan yang datang ke kabupaten Aceh Tengah melalui penyebaran informasi wisata. Pengabdian ini bertujuan untuk dapat memberikan pelatihan penguatan kemampuan dan kecakapan komunikasi pariwiatsa dalam Bahasa Inggris khususnya pada aspek komunikasi promosi wisata dalam Bahasa Inggris yang disampaikan melalui media brosur/flyer objek wisata.]]>
<![CDATA[Model of nitrogen-phosphorus ratio and phytoplankton relationship in lake Laut Tawar, Indonesia ]]>
<![CDATA[Adhar, Saiful]]>;
<![CDATA[Khalil, Munawwar]]>;
<![CDATA[Erlangga, Erlangga]]>;
<![CDATA[Muliani, Muliani]]>;
<![CDATA[Rusydi, Rachmawati]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Imanullah, Imanullah]]>;
<![CDATA[Andika, Yudho]]>
<![CDATA[ Depik Vol 12, No 3 (2023): DECEMBER 2023 ]]>
Publisher : <![CDATA[Faculty of Marine and Fisheries, Universitas Syiah Kuala ]]>
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DOI: 10.13170/depik.12.3.33935
<![CDATA[Phytoplankton blooms in the lake cause ecological, economic, health, energy, and aesthetic losses. It reduces water quality and biota diversity, creates toxins in the waters, and changes the structures and functions of the ecosystem. The essential nutrients for the growth of phytoplankton are nitrogen and phosphorus. Controlling phytoplankton growth can be managed by controlling the limiting nutrient input. This study aims to identify the limiting nutrient, analyze variations in TN:TP ratio spatially and temporally, and model TN:TP ratio and chlorophyll-a relationship. This study used secondary data from previous studies, namely TN, TP, and chlorophyll-a observed monthly in seven stations purposively during a year. Rainfall data was also obtained from the previous study. Limiting nutrients were determined by Redfield theory, and data were analyzed by Spearman correlation, One-way ANOVA, Kruskal-Wallis, and regression analysis. The results showed phosphorus was a limiting nutrient for phytoplankton growth in Lake Laut Tawar. TN:TP ratio and chlorophyll-a did not vary spatially, indicating the lake surface waters were evenly mixed. The parameters varied temporally, expressing the influence of hydroclimatological factors, especially rainfall. Rainfall increases nutrient input to the lake, but only rain below 200 mm/month causes an increase in the concentration of nutrients in the lake. The rainfall above 200 mm/month increases lake water volume significantly, thereby reducing nutrient concentrations. TN:TP ratio and chlorophyll-a related negatively and formed a non-linear relationship with an empirical model Chlorophyll-a = 2770.285 (TN/TP)-1.871. Eutrophication of Lake Laut Tawar should be anticipated by controlling the anthropogenic phosphorus input.Keywords:AnthropogenicChlorophyll-aEutrophication,Limiting nutrientRainfall]]>
<![CDATA[DATA PROCESSING TRAINING USING MICROSOFT EXCEL FOR STUDENTS OF THE FACULTY OF AGRICULTURE, MALIKUSSALEH UNIVERSITY ]]>
<![CDATA[Rusydi, Rachmawati]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Mahdaliana, Mahdaliana]]>;
<![CDATA[Hatta, Muhammad]]>;
<![CDATA[Ayuzar, Eva]]>;
<![CDATA[Salamah, Salamah]]>
<![CDATA[ ABDIMU: Jurnal Pengabdian Muhammadiyah Vol 3, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Aceh ]]>
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DOI: 10.37598/abdimu.v3i2.1711
<![CDATA[Data processing is part of the statistics used for drawing conclusions on the data analyzed using various statistical softwares. One of the softwares for simple data processing is Microsoft Excel. However, the use of Microsoft Excel for statistical analysis by students of the Agriculture Faculty, Malikussaleh University is not optimal compared to some other software. The purpose of this training activity is to provide data processing knowledge and skills to students of the Agriculture Faculty, Malikussaleh University using Microsoft Excel on data analysis. The community service activities were carried out at the Statistics Laboratory of the Agriculture Faculty, Malikussaleh University in March 2023. The method applied was training on data analysis through data analysis microsoft excel. Evaluation of community service activities was carried out through a survey using an online questionnaire on the Google form. Data processing training activities using Microsoft Excel for students of the Faculty of Agriculture, Malikussaleh University provided increased knowledge and skills. Students assessed that the use of Microsoft Excel in data processing was important and necessary in addition to other software. Furthermore, the training activities were considered very good, in terms of delivery, materials, and discussion time. Keywords: Data Processing; Microsoft Excel, Student, Agriculture]]>
<![CDATA[Model of nitrogen-phosphorus ratio and phytoplankton relationship in lake Laut Tawar, Indonesia ]]>
<![CDATA[Adhar, Saiful]]>;
<![CDATA[Khalil, Munawwar]]>;
<![CDATA[Erlangga, Erlangga]]>;
<![CDATA[Muliani, Muliani]]>;
<![CDATA[Rusydi, Rachmawati]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Imanullah, Imanullah]]>;
<![CDATA[Andika, Yudho]]>
<![CDATA[ Depik Vol 12, No 3 (2023): DECEMBER 2023 ]]>
Publisher : <![CDATA[Faculty of Marine and Fisheries, Universitas Syiah Kuala ]]>
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DOI: 10.13170/depik.12.3.33935
<![CDATA[Phytoplankton blooms in the lake cause ecological, economic, health, energy, and aesthetic losses. It reduces water quality and biota diversity, creates toxins in the waters, and changes the structures and functions of the ecosystem. The essential nutrients for the growth of phytoplankton are nitrogen and phosphorus. Controlling phytoplankton growth can be managed by controlling the limiting nutrient input. This study aims to identify the limiting nutrient, analyze variations in TN:TP ratio spatially and temporally, and model TN:TP ratio and chlorophyll-a relationship. This study used secondary data from previous studies, namely TN, TP, and chlorophyll-a observed monthly in seven stations purposively during a year. Rainfall data was also obtained from the previous study. Limiting nutrients were determined by Redfield theory, and data were analyzed by Spearman correlation, One-way ANOVA, Kruskal-Wallis, and regression analysis. The results showed phosphorus was a limiting nutrient for phytoplankton growth in Lake Laut Tawar. TN:TP ratio and chlorophyll-a did not vary spatially, indicating the lake surface waters were evenly mixed. The parameters varied temporally, expressing the influence of hydroclimatological factors, especially rainfall. Rainfall increases nutrient input to the lake, but only rain below 200 mm/month causes an increase in the concentration of nutrients in the lake. The rainfall above 200 mm/month increases lake water volume significantly, thereby reducing nutrient concentrations. TN:TP ratio and chlorophyll-a related negatively and formed a non-linear relationship with an empirical model Chlorophyll-a = 2770.285 (TN/TP)-1.871. Eutrophication of Lake Laut Tawar should be anticipated by controlling the anthropogenic phosphorus input.Keywords:AnthropogenicChlorophyll-aEutrophication,Limiting nutrientRainfall]]>
<![CDATA[Optimalisasi Lahan Pekarangan Melalui Budidaya Lobster Air Tawar dengan Penerapan Kolom Vertikultur ]]>
<![CDATA[Anshar, Khairul]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Amri, Amri]]>;
<![CDATA[Muarif, Agam]]>;
<![CDATA[Mulyawan, Rizka]]>;
<![CDATA[Razi, Ar]]>
<![CDATA[ Jurnal Malikussaleh Mengabdi Vol. 4 No. 1 (2025): Jurnal Malikussaleh Mengabdi, April 2025 ]]>
Publisher : <![CDATA[LPPM Universitas Malikussaleh ]]>
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DOI: 10.29103/jmm.v4i1.18735
<![CDATA[Pertanian memanfaatkan lahan pekarangan telah menjadi alternatif dalam memenuhi kebutuhan pangan lokal, terutama di lingkungan perkotaan yang memiliki keterbatasan lahan. Dengan memanfaatkan lahan pekarangan, masyarakat dapat menghasilkan berbagai jenis tanaman dan hewan ternak untuk kebutuhan konsumsi sendiri serta sebagai sumber pendapatan tambahan. Budidaya lobster air tawar telah menjadi salah satu potensi pengembangan yang menjanjikan dalam meningkatkan pendapatan. Lobster air tawar memiliki nilai ekonomi yang tinggi dan permintaan yang terus meningkat baik di pasar lokal maupun internasional. Namun, budidaya lobster air tawar masih belum banyak dilakukan secara luas di Indonesia karena kurangnya pengetahuan dan keterampilan teknis petani, serta keterbatasan lahan yang tersedia untuk budidaya. Melalui kegiatan pengabdian ini akan dilakukan proses budidaya lobster air tawar dengan menerapkan konsep kolom bertingkat atau vertikultur, kami berharap dapat memanfaatkan lahan pekarangan secara lebih efisien untuk budidaya lobster air tawar, sehingga dapat meningkatkan pendapatan petani dan kesejahteraan masyarakat. Program ini juga akan melibatkan program kemitraan dengan pihak ketiga yang siap menerima hasil panen budidaya lobster air tawar sehingga masyarakat tidak perlu khawatir dan memusingkan diri untuk menjual atau memasarkan lobster air tawar. Dengan demikian, diharapkan program ini tidak hanya akan meningkatkan produktivitas lahan pekarangan dan pendapatan masyarakat, tetapi juga akan memberdayakan mereka dengan pengetahuan dan keterampilan baru dalam pertanian modern. Disisi lain, program ini diharapkan, dapat menciptakan solusi yang holistik dalam menghadapi tantangan pertanian dan ketahanan pangan di tingkat lokal, sambil juga berkontribusi pada pembangunan ekonomi dan sosial masyarakat setempat.]]>
<![CDATA[Penguatan Karakter Pancasila Generasi Z: Literasi Digital dan Etika Bermedia Sosial untuk Siswa SMA ]]>
<![CDATA[Rahman, Arief]]>;
<![CDATA[Mainisa, Mainisa]]>;
<![CDATA[Yurni, Irma]]>;
<![CDATA[Syamni, Ghazali]]>;
<![CDATA[Zulkifli, Zulkifli]]>;
<![CDATA[Rasyid, Laila M]]>
<![CDATA[ Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 8 (2025): Oktober ]]>
Publisher : <![CDATA[Amirul Bangun Bangsa ]]>
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DOI: 10.59837/jpmba.v3i8.3266
<![CDATA[Perkembangan teknologi digital telah membawa tantangan baru bagi generasi muda, khususnya siswa SMA yang merupakan bagian dari Generasi Z. Tingginya intensitas penggunaan media sosial membuat siswa rentan terhadap penyebaran hoaks, ujaran kebencian, dan perilaku tidak etis dalam ruang digital. Kondisi ini menunjukkan pentingnya pembekalan literasi digital yang tidak hanya berfokus pada keterampilan teknis, tetapi juga menanamkan nilai-nilai Pancasila sebagai landasan etika bermedia sosial. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk menguatkan karakter Pancasila generasi muda melalui pelatihan literasi digital dan etika bermedia sosial. Metode yang digunakan meliputi presentasi interaktif, diskusi kelompok, simulasi fact-checking, serta praktik pembuatan konten digital yang bertanggung jawab. Hasil pelaksanaan menunjukkan adanya peningkatan pemahaman siswa, partisipasi aktif dalam praktik literasi digital, serta tumbuhnya kesadaran etis dalam bermedia sosial. Kegiatan ini membuktikan bahwa pelatihan literasi digital berbasis nilai-nilai Pancasila efektif dalam membentuk sikap kritis, etis, dan bertanggung jawab pada pelajar SMA, sekaligus memperkuat karakter kebangsaan.]]>
