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All Journal Jurnal Sosio Ekonomika Bisnis Syntax Jurnal Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Universitas Pamulang Conference on Innovation and Application of Science and Technology (CIASTECH) MIND (Multimedia Artificial Intelligent Networking Database) Journal Jambura Journal of Informatics Journal of Electronics, Electromedical Engineering, and Medical Informatics INTI Nusa Mandiri BRITech : Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan TIN: TERAPAN INFORMATIKA NUSANTARA Abdi Kami : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Infotech: Jurnal Informatika & Teknologi Computer Science (CO-SCIENCE) Jurnal Mandiri IT Scientific Student Journal for Information, Technology and Science Jurnal Algoritma Technologica International Journal of Management Research and Economics Journal of Computer Science Contributions (Jucosco) ABDI KAMI: Jurnal Pengabdian Kepada Masyarakat
Fitri Nur Masruriyah, Anis
Universitas Buana Perjuangan Karawang
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Performance Evaluation of Popular Supervised Learning Algorithms Towards Cardiovascular Disease Masruriyah, Anis Fitri Nur; Novita, Hilda Yulia; Sukmawati, Cici Emilia
Jurnal Informatika Universitas Pamulang Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i3.34103

Abstract

Many studies have discussed the advantages of supervised learning for dealing with extensive data on heart disease. However, only a few studies evaluate the performance of supervised learning algorithms. This research builds a classification model using supervised learning algorithms, including C4.5, Random Forest, Logistic Regression, and Support Vector Machine. The data processed is in the form of category data with character data types. The accuracy, precision, and performance evaluation results show that the Logistic Regression Algorithm has the most superior value compared to the others. On the other hand, it was found that the C4.5 and SVM algorithms had anomalous events. Although the accuracy and precision values of C4.5 were superior to SVM, SVM had better performance.
CLASSIFICATION OF RICE ELIGIBILITY BASED ON INTACT AND NON-INTACT RICE SHAPES USING YOLO V8-BASED CNN ALGORITHM Hastari, Nazwa Putri; Rohana, Tatang; Masruriyah, Anis Fitri Nur; Wahiddin, Deden
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.5.2413

Abstract

The large amount of unfit rice has an impact on the quality of rice provided to the community. This is due to the lack of supervision of the quality of existing rice, so that the quality of rice distributed to the community has a lot of unfit quality. Rice production for public consumption reached 21.69 million tons in 2021, according to data from the Central Statistics Agency (BPS). Rice is the main food of the Indonesian people because most Indonesians are farmers and the vast amount of agricultural land makes Indonesia one of the largest rice producing countries in Southeast Asia, this has a huge impact on people's habits in consuming rice as the main food provider. The Government of the Republic of Indonesia started a Social Assistance rice distribution program through the Ministry of Social Affairs in 2018. This program is named Prosperous Rice Social Assistance (Bansos Rastra). Classification of rice eligibility can be the first step to ensure that the rice received from the government is of high quality and can meet the daily needs of households in Indonesia. CNN algorithm based on YOLOv8 system can automatically recognize the form of rice given by the government whether it is feasible or not. In the research stages there are dataset collection, preprocessing, training models to evaluation. Based on the results obtained in this study, the accuracy achieved is 79% for the Eligible class and 79% for the Ineligible class with Confidence score reaching a value of 1.00. The results of this study can be used as a decent and unfit rice classification detection model by looking at the shape of the rice. So that the rice distributed to the community has decent rice quality.
Pengenalan Prototype Kumbung Jamur Merang Berbasis Internet of Things Pada Desa Gempol Kolot Masruriyah, Anis Fitri Nur
Journal Of Computer Science Contributions (JUCOSCO) Vol. 2 No. 1 (2022): Januari 2022
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/0endn253

Abstract

One of the impacts of the COVID-19 pandemic in Karawang Regency is the reduction of employees and cutting costs on mushroom cultivation. This has an impact on the monitoring period for mushrooms, mushroom farmers who have to enter the mushroom kumbung with higher temperature and humidity outside the kumbung. Prior to the pandemic, the monitoring employees took turns checking the condition of the mushrooms, but due to the pandemic and the limited number of employees, farmers were overwhelmed. Based on these problems, the introduction of technology in the form of a prototype of kumbung mushroom based on the internet of things was carried out to help mushroom cultivators. The recommendation given to mushroom farmers is to implement an IoT system to help increase the number of harvests and shorten harvest time. Furthermore, for the implementing team for community service and universities, it is to find a solution to create an economical system. So that mushroom farmers are not burdened with system installation costs.
ANALISIS PENERIMAAN PASAR TERHADAP PRODUK MIE SAYUR BERBASIS MOCAF KAYA BETA KAROTEN: ANALYSIS OF MARKET ACCEPTANCE OF VEGETABLE NOODLE PRODUCTS BASED ON MOCAF CONTAINS OF BETA KAROTEN Nita, yustina; Fitri Nur Masruriyah, Anis; Dasmadi
Jurnal Ilmiah Sosio-Ekonomika Bisnis Vol 22 No 1 (2019): Jurnal Ilmiah Sosio-Ekonomika Bisnis
Publisher : Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (352.532 KB) | DOI: 10.22437/jiseb.v22i1.8074

Abstract

Mie sayur berbasis mocaf (Modified Cassava Flour) yang mengandung beta karoten merupakan salah satu produk inovasi hasil penelitian dari tim peneliti Pusat Penelitian Bioteknologi, Lembaga Ilmu Pengetahuan Indonesia (LIPI). Ditinjau dari aspek nutrisi, produk ini memiliki kandungan beta karoten, protein dan zat besi yang sangat bermanfaat bagi kesehatan. Selain itu, produk ini juga berpotensi mengurangi penggunaan dan ketergantungan terhadap tepung terigu. Untuk mendapatkan gambaran tentang potensi pasar, maka dilakukan penelitian untuk mengetahui penerimaan pasar terhadap produk ini. Penelitian dilaksanakan dengan metode kuantitatif, sedangkan pengambilan data menggunakan metode kuesioner dengan metode analisa data skala likert dan Algoritme Relief. Disimpulkan dari hasil analisa data dengan menggunakan metode skala likert dan algoritma relief, terlihat perbedaan pada hasil analisa : 1) penerimaan responden terhadap tekstur dan rasa mie; 2) harga produk yang diterima responden; 3) faktor yang mempengaruhi responden dalam membeli produk mie. Namun data keduanya menunjukkan bahwa produk mie sayur berbasis mocaf kaya beta karoten dapat diterima dengan baik oleh pasar. Data hasil Analisa menunjukkan bahwa produk mie sayur berbasis mocaf kaya beta karoten memiliki potensi pasar yang cukup baik, dapat diterima oleh pasar dengan indeks presentase penerimaan tekstur mie sebesar 79,47% dan rasa sebesar 80,52%. Sedangkan untuk harga produk, responden menerima produk dengan kisaran harga Rp. 6.500 hingga Rp. 7.500 per bungkus, dengan indeks persentase penerimaan sebesar 86.31%. Hasil analisa data dengan metode algoritme Relief menunjukkan bahwa penerimaan rasa oleh responden memiliki peringkat sebesar 0.05288. Kemudian dalam atribut harga, responden dapat menerima di kisaran harga Rp. 7.500 hingga Rp. 8.500 per bungkus dengan nilai peringkat 0.10439.
PROGRAM PENGENALAN ALAT KUMBUNG JAMUR CERDAS BERBASIS INTERNET OF THINGS Elsa Elvira Awal; Anis Fitri Nur Masruriyah
ABDI KAMI: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2022): (Februari 2022)
Publisher : LPPM Institut Agama Islam (IAI) Ibrahimy Genteng Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/abdi_kami.v5i1.1294

Abstract

The environment that affects the growth and yield of mushrooms is one of them is the thickness of planting media. Different thicknesses of planting media will produce different temperature conditions. Mushrooms grow in locations that have enough oxygen and grow optimally at 32°-35°C and 80-90% humidity for the vegetative/mycelium phase, while in the generative/body formation phase the fruit is optimal at 30°-32°C and humidity is 85-95%. Based on this explanation, it is necessary to introduce intelligent mushroom kumbuh tool with internet of things to help the cultivation of mushrooms using fuzzy logic methods. The tool can control ioT-based temperature and humidity so that mushroom farmers can monitor mushrooms through the web, so that mushroom farmers can understand that smart mushrooms are able to provide information about temperature and humidity conditions in real time.
Pemodelan topik Dokumen Tesis menggunakan Metode Latent dirichlet allocation Mardiah, Mardiah; Masruriyah, Anis Fitri Nur; Tiana, Ade Hikma; Prakoso, Bobby Suryo; Prasetyo, Rizky Tito; Ardika, Sanggi Bayu
Technologica Vol. 5 No. 1 (2026): Technologica
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/technologica.v5i1.376

Abstract

Penelitian merupakan suatu langkah yang dilakukan untuk mengembangkan ilmu pengetahuan dan mencari kebenaran. Dasar dalam melakukan penelitian adalah membaca dokumen penelitian sebelumnya. Namun, pencarian dokumen penelitian yang saling berhubungan seringkali membutuhkan banyak waktu. Maka, dibutuhkan pemodelan topik yang dapat mengelompokkan dokumen  berdasarkan topiknya agar membantu peneliti dalam melaksanakan tugasnya. Penelitian ini menggunakan metode Latent dirichlet allocation untuk memodelkan topik dalam dokumen, dan menggunakan perhitungan nilai coherence untuk menentukan jumlah topik yang akan dimodelkan. Hasil analisis menunjukkan bahwa pemodelan topik dengan metode Latent dirichlet allocation berhasil membagi 340 dokumen tesis dalam 5 topik utama dengan nilai coherence yaitu 0.445. Karakteristik yang terdapat dalam tiap topik merupakan bidang kajian tertentu yaitu sistem informasi, kebakaran lahan, bioinformatika, pengolahan citra, dan robotika. Hasil yang didapatkan menunjukkan metode LDA telah berhasil mengelompokkan dokumen dalam kesamaan topik atau kajian tertentu.
Co-Authors Ahmad Fauzi Alvionika, Nindy Amril Siregar ANANDA, MUHAMMAD DWI Anton Junior Anton Romadoni Junior Ardika, Sanggi Bayu Arief Wibowo ARIF, SITI NOVIANTI NURAINI Asep Maulana, Asep Awal, Elsa Elvira Bambang Saras Yulistiawan dasmadi, dasmadi Deden Wahiddin Deny Maulana Dexi Triadinda Dwi Vina Wijaya Elsa Elvira Awal Elsa Elvira Awal Emilia Sukmawati, Cici Emilia Sukmawati Faisal, Sutan Hanny Handayani Hanny Hikmayanti Handayani Hastari, Nazwa Putri Indra, Jamaludin Juwita, Ayu Ratna MALIK, KARENINA NURMELITA Maman Suherman Mardiah Mardiah Mudzakir, Tohirin Al Muhammad Cesar Afriansyah Arief Nita, yustina Novita, Hilda Yulia Nurmayanti, Trisya Permana, Tedi Prakoso, Bobby Suryo Prasetyo Ajie Prasetyo, Rizky Tito Rahmat Hidayat Rahmat Rahmat RAMADHAN, ANGGA RAMDA Risky Pratama, Adi Riyandi Aditya Fitrah Rohana, Tatang Ryan Gusti Nugraha Selly Rahmawati Septiany, Eva Senia Siregar, Amril Mutoi Siti Robiah Sukmawati, Cici Emilia Syahrul Azis Tania Puspa Rahayu Sanjaya Tejayanda, Rigger Damaiarta Tiana, Ade Hikma Tri Denda Ulfa Amelia Wahiddin, Deden Widiharto, Banani Yana Cahyana Yogi Alfiansah Yogi Firman Alfiansyah