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Peningkatan Kualitas Produk Keripik Kentang pada Industri Rumah Tangga (IRT) Tooop Rasa, Sokaraja, Kabupaten Banyumas Melalui Pelatihan CPPOB dan Bahan Pangan Halal Mulia, Dini Siswani; Wati, Ratna Kartika; Suwarsito, Suwarsito; Wahyuni, Sri; Darmawan, Akhmad; Susylowati, Dewi; Saputra, Eqwar
Jurnal SOLMA Vol. 14 No. 3 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i3.17181

Abstract

Background: Industri Rumah Tangga (IRT) Tooop Rasa merupakan IRT yang memiliki berbagai usaha produksi olahan pangan, salah satunya adalah keripik kentang. Produk ini termasuk produk unggulan dengan bahan baku yang melimpah dan kontinu. Namun, pembuatan keripik kentang belum mengaplikasikan prinsip Cara Produksi Pangan Olahan yang Baik (CPPOB) dan produk belum bersertifikat halal. Kegiatan pembinaan IRT ini bertujuan untuk memberikan edukasi atau pelatihan CPPOB dan bahan pangan halal agar produk berkualitas baik dan dapat meningkatkan daya saing. Metode: Kegiatan pengabdian dilakukan dengan metode pendekatan partisipatoris dengan tahap kegiatan meliputi sosialisasi, pelatihan, pendampingan, dan evaluasi. Tingkat keberhasilan program diukur dengan metode one group pre-test and post-test. Hasil: Hasil kegiatan menunjukkan 87,50% anggota mitra memahami dan mampu mengimplementasikan CPPOB, dan 85,00% anggota mitra memahami dan mampu mengimplementasikan tentang bahan pangan halal. Produk keripik kentang telah didampingi dalam pengajuan sertifikasi halal. Kesimpulan: Kegiatan pengabdian telah berhasil memberikan edukasi atau pelatihan CPPOB dan bahan pangan halal yang berimplikasi positif terhadap peningkatan pemahaman dan keterampilan mitra. Produk keripik kentang yang dihasilkan berkualitas baik dan memenuhi kriteria sesuai SNI 4031:2018, yaitu bau, rasa, tekstur, dan penampakan normal, salah satunya ditandai dengan warna kuning merata dan tekstur renyah. Selain itu, mitra telah berhasil mendapatkan sertifikat halal sehingga dapat meningkatkan daya saing.
PENGELOLAAN LAHAN DAN AIR DI AREA PASANG SURUTESA LOSARI LOR KECAMATAN LOSARI KABUPATEN BREBES Suwarno; Suwarsito; Fathurnnadi Shalihati
JURNAL ILMIAH ULTRAS BREBES Vol 3 No No. 2 (2020): Jurnal Ilmiah Ultras Brebes
Publisher : Badan Perencanaan Pembangunan, Riset dan Inovasi Daerah Kabupaten Brebes

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

 Kondisi lahan pertanian di areal pasang surut Desa Losari Lor saat ini sering mengalamigagal panen, diakibatkan oleh air pasang dari laut yang masuk melalui saluran drainaseatau luapan air sungai Cisanggarung yang menggenangi lahan. Tujuan penelitian untukmengetahui permasalahan dan hambatan teknis dan non teknis (sosial masyarakat) terkaitpengelolaan air dan tanah di lahan pasang surut tersebut. Menggunakan metode surveylapangan dan observasi., survey lapangan untuk mengetahui tipologi lahan dan penggunaanlahan, observasi dilakukan untuk menghimpun data tinggi muka air genangan, jaringanirigasi, tinggi muka air tanah, kualitas air (pH, kadar Fe, dan salinitas), jenis tanah, teksturtanah, kualitas tanah (pH, salinitas, dan kadar Fe), dan kedalaman air tanah. Analisa datamenggunakan analisis deskriptif kualitatif untuk menjelaskan permasalahan dan hambatanteknis dan non teknis terkait pengelolaan air dan tanah di lahan pasang surut, sedangkananalisis data tinggi air genangan dilakukan secara deskriptif kuantitatif untuk menentukantipe luapan air laut. Analisis data juga didukung menggunakan ArcGIS dan model builderuntuk menghasilkan peta tematik. Hasil menunjukkan 1) permasalahan teknis disebabkankondisi hidrografi dan jaringan tata air irigasi yang kurang baik sehingga menyebabkanbanjir dan kekeringan di lahan pertanian, 2) permasalahan non teknis berupa lemahnyapenguasaan teknologi oleh petani dan mahalnya biaya produksi pertanian, 3) hambatanteknis berupa kondisi kualitas tanah termasuk tanah masam dan salin dengan kadar Feyang tinggi serta hambatan keterbatasan modal para petani, 4) hambatan non teknismeliputi pola pikir petani yang pasrah menerima keadaan, kurang inovatif dan tidak beranimengambil risiko serta hambatan kelembagaan. 
Local Wisdom Value in Implementing of Merdeka Belajar Kampus Merdeka in Era Digital Rifari Baron; Suwarsito Suwarsito; Chodidjah Chodidjah; Vivian Lisma Lestari
AL-ISHLAH: Jurnal Pendidikan Vol 14, No 4 (2022): AL-ISHLAH: Jurnal Pendidikan
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v14i4.2048

Abstract

The study's purpose was to obtain the concept of the value of local wisdom in the digital era with the existence of an independent learning policy on an independent campus. This study analyzed all research data related to the value of local wisdom and MBKM that has been carried out by previous researchers. This study was a literature review research through a qualitative approach. The research data was taken from research results that have been published in national and international journals in the period 2010-2022. The data analysis stage used in this study was a qualitative approach which includes: data reduction, data presentation, and conclusion. The results of this study resulted in the concept of applying local wisdom values that were compatible with the application of the MBKM policy and were also related to advances in digital technology with all the demands for quality human resources. Educators and educational institutions must work together to develop local wisdom values in MBKM policy-based learning. Educators can use the results of this research as theoretical input for developing learning facilities
Mapping the Readiness and Challenges of the MBKM Policy Implementation: A Systematic Literature Review of Micro and Macro Educational Perspectives : Penelitian Suwarsito, Suwarsito; Lestari, Viviana Lisma; Faiza, Childa
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.4562

Abstract

The Merdeka Belajar–Kampus Merdeka (MBKM) policy introduced by Indonesia’s Ministry of Education in 2020 seeks to transform higher education by promoting flexible, student-centered learning through internships, community service, and research. However, its implementation faces significant disparities in institutional readiness and ongoing challenges. This systematic literature review (SLR) examines 20 studies to explore both micro- and macro-level perspectives on MBKM implementation. Findings reveal gaps in educator preparedness, student awareness, institutional policy alignment, and infrastructure support. At the macro level, systemic resistance and limited stakeholder engagement hinder policy uptake. This review proposes a comprehensive framework integrating these perspectives to guide more effective implementation strategies and support national education reform goals.
Inovasi Produk Sambal Ikan Nila Sebagai Strategi Pemanfaatan Hasil Perikanan Desa Kumejing Meilani, Alen Fadila; Hilmi, Mukhamad Rizal; Istiqomah, Adilah Al; Putri, Nadia Khasanah; Pambudi, Asidqo Kurnia Luhur; Aulia, Safira; Yuda, Sabik Husni Maula; Pradita, Mufidah Putri; Fajriati, Hevi Hanifah; Yuniarista, Lulu Dwi; Afiani, Indri; Darmono, Darmono; Kurniawan, Rahmat Adi; Pribadi, Teguh; Suwarsito, Suwarsito
Jurnal SOLMA Vol. 15 No. 1 (2026)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v15i1.21087

Abstract

Pendahuluan: Inovasi dalam pemanfaatan hasil perikanan menjadi salah satu strategi penting dalam meningkatkan nilai tambah produk perikanan bagi masyarakat pedesaan. Desa Kumejing memiliki potensi besar dalam produksi ikan nila, namun belum dimanfaatkan secara optimal, sehingga diperlukan strategi inovatif untuk meningkatkan kesejahteraan masyarakat. Studi ini bertujuan untuk memperkenalkan dan mengembangkan produk inovatif berupa sambal ikan nila sebagai solusi diversifikasi produk perikanan yang bernilai ekonomi tinggi. Metode: Pelatihan dan pendampingan pembuatan sambal ikan nila. Produk yang dihasilkan kemudian dipamerkan dan dipasarkan sebagai ajang promosi. Hasil: Adanya peningkatan pengetahuan dan keterampilan masyarakat dalam mengolah ikan nila menjadi produk bernilai jual tinggi. Peserta berminat mengembangkan produksi sambal ikan nila sebagai sumber penghasilan rumah tangga nelayan. Dimana produk ini sambal memiliki daya tarik tinggi dan prospek bisnis yang bagus. Kesimpulan: Pengembangan produk sambal ikan nila di Desa Kumejing dapat dilanjutkan sebagai salah satu produk gastronomi khas dan unggulan desa dalam rangka mendukung desa wisata.
Freshwater Fish Classification Based on Image Representation Using K-Nearest Neighbor Method Suwarsito Suwarsito; Hindayati Mustafidah; Tito Pinandita; Purnomo Purnomo
JUITA: Jurnal Informatika JUITA Vol. 10 No. 2, November 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v10i2.15471

Abstract

Indonesia is a maritime and agricultural country with enormous world fishery potential. The large variety of fish is often confusing for ordinary people in recognizing types of fish, especially freshwater fish. It was stated that the types of freshwater fish often consumed by the Indonesian people are bawal (pomfret), betutu, gabus (cork), gurame (carp), mas (goldfish), lele (catfish), mujaer (tilapia), patin (asian catfish), tawes, and nila (tilapia nilotica). Some fish types have similar shapes, so it is tricky to tell them apart. Meanwhile, in the digitalization era today, Artificial Intelligence (AI)-based technology has become a demand in all areas of life. It is overgrowing, not apart from the fisheries sector. Therefore, in this study, the K-Nearest Neighbor (KNN) method was applied as one of the methods in AI to identify and classify freshwater fish species based on their images. The KNN method classifies new data into specific classes based on the distance between the new data and the closest k data through the learning process. This KNN model is built by preparing the dataset stages, separating the dataset into data-train and data-test with a ratio of 70%:30%, then building and testing the model. The dataset is freshwater fish images, totaling 100 images from 10 freshwater fish types. Model testing is done by measuring performance using a confusion matrix. Based on the test results, the model has an accuracy performance of 70%. Thus, KNN can be used as a model to identify freshwater fish species based on their image.
Expert System for Diagnosing Gourami Fish Diseases Using the Certainty Factor Approach Hindayati Mustafidah; Ilham Gunadi; Cahyono Purbomartono; Suwarsito Suwarsito; Eri Zuliarso
JUITA: Jurnal Informatika JUITA Vol. 13 Issue 1, March 2025
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v13i1.26031

Abstract

Gourami is an economically significant fish in the aquaculture sector due to its high market demand and relatively stable price. However, it is also challenging to cultivate, with disease outbreaks being one of the primary difficulties. Early diagnosis of gourami fish diseases requires expertise from fish health specialists, who are often difficult to find due to their limited availability. With advancements in artificial intelligence-based technology, this study developed an expert system to diagnose gourami fish diseases based on observed symptoms. The system employs the Certainty Factor (CF) approach to estimate the likelihood of a particular disease affecting the fish. The Certainty Factor approach utilizes a knowledge base derived from expert knowledge to address uncertainty in diagnosis. The certainty factor weights are determined based on confidence levels from both experts and users to generate an accurate diagnosis. This expert system was developed using data from 20 types of gourami fish diseases and 38 associated symptoms. The system successfully identified diseases with a certain level of confidence and provided appropriate treatment recommendations based on the confidence level obtained. By implementing this expert system, the risk of disease outbreaks can be minimized, thereby improving efficiency and productivity in gourami fish farming while helping maintain fish health and reducing economic losses caused by disease.
Image-Based Classification of Freshwater Fish Species to Support Feed Recommendation Using Random Forest Hindayati Mustafidah; Suwarsito Suwarsito; Rahmat Setiawan; Abdul Karim
JUITA: Jurnal Informatika JUITA Vol. 13 Issue 2, July 2025
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v13i2.27358

Abstract

Accurate identification of freshwater fish species plays a vital role in aquaculture, particularly in determining appropriate feed strategies to optimize fish growth. Visual similarities among species—such as color, shape, and surface texture—often hinder novice farmers from correctly recognizing fish types. This study proposes an image-based classification system using the Random Forest algorithm to identify six freshwater fish species: pomfret (bawal), gourami (gurame), catfish (lele), barb (melem), tilapia (nila), and Java barb (tawes) and provide automated feed recommendations. A total of 120 fish images were used as the dataset, collected from various sources, including online repositories and field documentation. Feature extraction was applied to capture color characteristics (HSV), texture patterns (GLCM), and morphological features (regionprops). The model was trained on 70% of the dataset and tested on the remaining 30%. Evaluation results show that the system achieved a classification accuracy of 83.33%, with a precision of 83.53%, recall of 83.33%, and an F1-score of 82.86%. Notably, catfish, barb, and tilapia classes achieved perfect classification, while pomfret and gourami showed room for improvement due to overlapping visual features. The findings indicate that the integration of Random Forest with multi-domain image features offers an effective, affordable, and practical solution to support the digital transformation of small and medium scale aquaculture systems through intelligent species recognition and feed guidance
Co-Authors Abdul Karim Abdurrohman Muzakki Ade Rusman Adi Imantoyo Afiani, Indri Ahmad Qurtubi Ahyani, Edi Akhmad Darmawan Al Hikmatul Zahro Kamila Almira Ulimaz Aman Suyadi Aman Suyadi Anang Widhi Nirwansyah Anna Ulie Nafisha Archristhea Amahoru, Archristhea Arif Ihsanul Fikri Arifudin, Opan Aris Hidayat Aris Hidayat Astika Nurul Hidayah Aulia, Safira Aviza, Aviza Alyama Ayundasari, Cantika Diffa Beny Wijarnako Budi, Larasati Ika Bustanol Arifin Cahyono Purbomartono Cantika Diffa Ayundasari Chodidjah Chodidjah Danang Dwi Harmoko Darmono Dedi Mulyawan, Dedi Diana Indra Dewi Didik Trianto Nugroho, Didik Trianto Dini Siswani Mulia Dinny Fauziah Dwi Ma’rifatun Khasanah Eri Zuliarso Esti Sarjanti Esti Sarjanti Euis Meinawati Faiza, Childa Fajriati, Hevi Hanifah Falasifa Azizah Fathurnnadi Shalihati Fitria Aulia Hamzah Syarifuddin, Hamzah Harjono Harjono Harna Adianto Heri Maryanto, Cahyono Purbomartono, Heri Maryanto, Herlin Widasiwi Setianingrum Hilmi, Mukhamad Rizal Hindayati Mustafidah Ibnu Afan Ikhsan Mujahid Ilham Gunadi Istiqomah, Adilah Al Jagad, Nimas Ayu Sekar Kinasih Jaka Purwa Nugraha, Jaka Purwa Jejentri, Jejentri Juanita Juanita kurniawan, rahmat adi Lestari, Viviana Lisma M. Agung Miftahuddin Mahmud, Annisa Kayla Azzira Meilani, Alen Fadila Mira Rosita Moh Aya Sofia Mohammad Ardin Pahlevi Mr. Suwarno, Mr. Muhamad Zaeni Budiastanto Mustolikh Mustolikh Nadifah, Itqon Ngaynun Nadiya Nur Apreli Nasril, Nasril Niken Herawati Ni`maturrohmah Ni`maturrohmah Noerhaliza Rachman Asriana Dwi Nur Mahmudah, Fitri Pambudi, Asidqo Kurnia Luhur Pradita, Mufidah Putri Pribadi, Teguh Purnomo Purnomo Putri, Nadia Khasanah Radin Alhif Dirgantara Rahayu, Wiwit Sayekti Rahmat Setiawan Ramli, Akhmad Ratna Kartika Wati Ratna Kartikawati Rifari Baron Ririn Windari, Ririn Rizki Herdani, Rizki Rusnendi Rusnendi Sabila Tri Amelia Sakinah Fathrunnadi Shalihati Salim, Agus Nur Saputra, Eqwar Saputri, Seffiana Aprilka Sembiring, Darmawanta Shahiffa Nur Pranannisa Sigit Sriwanto Sri Wahyuni Sufi Alawiyah Sugeng Priyadi Susanto Susanto Susylowati, Dewi Sutomo Sutomo Sutomo Sutomo Tito Pinandita Triyadi Haryanto Utbah Aminatul Hofisah Veronica Sovita Sari, Veronica Sovita Vivian Lisma Lestari Viviana Lisma Lestari Viviana Lisma Lestari Wahyu Agung Ciptadi Wakhudin Wildan Ahid Mujamal Wiwin Bregasnia Wiwit Sayekti Rahayu Yuda, Sabik Husni Maula Yunia Dwi Pambudi, Yunia Dwi Yuniarista, Lulu Dwi Zahrah Hana Afifah