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All Journal Agroradix : Jurnal Ilmu Pertanian Lattice Journal : Journal of Mathematics Education and Applied PANDALUNGAN : Jurnal Pengabdian kepada Masyarakat Pentagon: Jurnal Matematika dan Ilmu Pengetahuan Alam
Anwar, Rohimatul
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics

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EKSTRAKSI DAN DETEKSI FITOKIMIA KENIKIR (Cosmos caudatus Kunth.) ASAL PANJANG UTARA, LAMPUNG Susanti, Nida Lidya; Lestari, Devi Eka; Anwar, Rohimatul
AGRORADIX : Jurnal Ilmu Pertanian Vol 8 No 1 (2024): Desember 2024
Publisher : Agroteknologi Fakultas Pertanian Universitas Islam Darul 'Ulum (UNISDA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/agroteknologi.v8i1.8107

Abstract

Kenikir (Cosmos caudatus Kunth.) is a plant species with many benefits. One of the benefits is that the Indonesian citizen uses it as a medicinal ingredient. This study aims to determine the phytochemical content of kenikir leaves (Cosmos caudatus Kunth.) obtained from farmers in Panjang Utara region, Bandar Lampung, Lampung. The method used is maceration and phytochemical testing where the kenikir leaves are sorted and washed then air-dried and homogenized using a homogenizer to become powder. Kenikir leaf powder is extracted using the maceration method with Ethanol 70% and then tested for phytochemical content of saponins, steroids, terpenoids, tannins, alkaloids, flavonoids, and phenolics. The results of the study showed that kenikir leaves do not contain steroid but contain saponin, terpenoid, tannin, alkaloid, flavonoids, and phenolic compounds that have the potential to be used for human health such as anticancer, antioxidant, antibacterial, and anti-inflammatory. The highest phytochemicals in kenikir leaf extract are saponin and flavonoid. Both saponin and flavonoid have the potential as antimicrobials.
Exploring the Potential of Astaxanthin Extracted from Shrimp Shell Waste as a Functional Feed Additive in Duck Nutrition Anwar, Rohimatul; Widyastuti Widyastuti; Annisa Ananda
Pentagon : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 3 No. 2 (2025): JUNI : Pentagon : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/pentagon.v3i2.615

Abstract

Shrimp shell waste is a potential marine biomass resource rich in bioactive compounds such as astaxanthin and chitin, yet remains underutilized in the livestock sector. This study aimed to evaluate the effect of incorporating shrimp shell meal into duck (Anas sp.) feed rations on the yolk color intensity of duck eggs. The experimental design applied a completely randomized design (CRD) with a single factor and four treatments: D0 (100% rice bran, control), A1 (rice bran + 2% shrimp shell meal), A2 (rice bran + 6%), and A3 (rice bran + 10%), with a 21-day observation period. The primary parameter measured was yolk color intensity, assessed visually using a standardized color scale. The results indicated that the addition of shrimp shell meal significantly enhanced yolk color intensity, with the highest pigmentation observed in the A3 treatment. Astaxanthin, functioning as a natural carotenoid pigment, was biologically absorbed and distributed into the yolk via lipophilic pathways, while chitin supported gut health and nutrient absorption efficiency. This study aligns with the principles of the circular economy by valorizing marine processing waste as a functional feed ingredient. A 10% inclusion rate was found to be visually optimal; however, further studies are required to assess its physiological impacts and economic feasibility in broader production contexts.
Analisis Komparasi Model Peramalan Prophet Dan Arima Dalam Memprediksi Harga Saham Penutupan PT ANTM Anwar, Rohimatul; Rassiyanti, Linda
Lattice Journal : Journal of Mathematics Education and Applied Vol. 5 No. 1 (2025): Juni 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/lattice.v5i1.9478

Abstract

PT Aneka Tambang Tbk (ANTM) is a major mining company in Indonesia whose shares are actively traded on the Indonesia Stock Exchange. Its stock price is influenced by both internal and external factors. Time series forecasting methods, such as ARIMA and Prophet, are used to predict future stock movements. ARIMA is known for its flexibility and high prediction accuracy, while Prophet is capable of handling missing values and shifting trends, making it suitable for complex financial data. This study aims to compare the performance of ARIMA and Prophet models in forecasting ANTM stock prices. The dataset consists of monthly closing stock prices from January 2016 to May 2025. The models are evaluated using Mean Absolute Percentage Error (MAPE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The results show that the ARIMA model performs better to predict PT ANTM’s traded than Prophet model, with lower MAPE, AIC, and BIC values of 7.88, 433.24, and 423.63, respectively.   PT Aneka Tambang Tbk (ANTM) adalah perusahaan pertambangan besar di Indonesia yang sahamnya aktif diperdagangkan di Bursa Efek Indonesia. Harga sahamnya dipengaruhi oleh faktor internal dan eksternal.  Memprediksi pergerakan harga saham di masa depan bagi PT ANTM dapat digunakan metode peramalan deret waktu seperti ARIMA dan Prophet. ARIMA dikenal fleksibel dan mampu memberikan hasil prediksi yang akurat. Sementara itu, Prophet unggul dalam menangani data yang memiliki nilai hilang dan tren yang berubah, menjadikannya cocok untuk data pasar keuangan yang dinamis. Penelitian ini bertujuan membandingkan performa model ARIMA dan Prophet dalam memprediksi harga saham ANTM. Data yang digunakan adalah harga penutupan saham bulanan selama periode Januari 2016 hingga Mei 2025. Perbandingan dilakukan berdasarkan nilai Mean Absolute Percentage Error (MAPE), Akaike Information Criterion (AIC), dan Bayesian Information Criterion (BIC). Hasil analisis menunjukkan bahwa model ARIMA memiliki performa lebih baik dengan nilai MAPE 7.88, AIC 433.24, dan BIC 423.63, yang lebih rendah dibandingkan dengan model Prophet.
PELATIHAN DESAIN GRAFIS CANVA UNTUK MENINGKATKAN KREATIVITAS SISWA Anwar, Rohimatul; Anwar, Rosyida Nurul
Pandalungan: Jurnal Pengabdian kepada Masyarakat Vol 4 No 1 (2025): Oktober
Publisher : Universitas Al-Falah As-Sunniyah Kencong Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62097/pandalungan.v4i1.2244

Abstract

This one-group pretest–posttest, service-learning Canva training for Grade VII students at SMPN 2 Wungu aimed to enhance students’ visual creativity and digital literacy. The program followed needs analysis, preparation, delivery, and evaluation within a single intensive session. The primary instruments comprised a poster assessment rubric (four indicators: layout, typography, color, and message clarity; 1–4 scale; two independent raters) and a 10-item perception questionnaire (1–4 scale; internal reliability estimated). The study involved 20 students selected proportionally from several classes. Results show an increase in mean product scores from 1.8 (pre) to 3.0 (post), i.e., Δ≈+1.2 points, with the proportion rated “good–very good” on color and layout reaching ≥75%. Additionally, 85% of respondents rated the training “useful/very useful” for visual and presentation tasks. These findings indicate that a short, structured, template-based workshop can reduce the technical burden of operating the app while directing attention to design problem-solving. Ethical procedures were observed through school approval, data anonymization, and consented documentation. Limitations include the single-session duration and small sample size, therefore 2–3 follow-up sessions with metric monitoring (consistent rubrics, scaffolded tasks) are recommended to provide stronger evidence of creativity gains.
Co-Authors Annisa Ananda Anwar, Rosyida Nurul Lestari, Devi Eka Rassiyanti, Linda Susanti, Nida Lidya Widyastuti Widyastuti