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PENDAMPINGAN MERANCANG PENELITIAN TINDAKAN KELAS DAN PENULISAN PUBLIKASI KEPADA GURU-GURU SD DI DESA SAKATIGA Novi Rustiana Dewi; Evi Yuliza; Alfensi Faruk; Ning Eliyati
Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Vol. 3 No. 3 (2019)
Publisher : Universitas Ahmad Dahlan, Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jp.v3i3.1270

Abstract

Penelitian Tindakan Kelas  (PTK) merupakan penelitian yang dapat dilakukan guru dalam rangka memperbaiki proses pembelajaran untuk mencapai tujuan tertentu. Hal ini menunjukkan bahwa sangat penting bagi guru untuk melakukan PTK. Peningkatan jenjang jabatan dan golongan bagi para guru memerlukan beberapa karya ilmiah yang dipublikasikan. Karya ilmiah dapat dihasilkan dari kegiatan PTK, oleh sebab itu perlu adanya tambahan wawasan bagi para guru bagaimana menuangkan hasil PTK ke dalam makalah ilmiah. Pelaksanaan kegiatan pengabdian ini bertujuan untuk memberikan tambahan wawasan akan pentingnya PTK dalam proses pembelajaran dan membantu para guru dalam menulis serta mempublikasikan hasil PTK pada jurnal nasional. Diharapkan dari kegiatan ini, para guru dapat melakukan PTK dan menulis makalah ilmiah dari hasil PTK yang sesuai metode ilmiah. Kegiatan pengabdian dilakukan dengan dua tahap, yaitu tahap pelaksanaan dan tahap pendampingan. Tahap pelaksanaan meliputi penyampaian materi PTK dan Penulisan ilmiah. Berdasarkan hasil kuesioner diketahui bahwa terdapat peningkatan  mengenai pemahaman konsep PTK dan publikasi ilmiah antara sebelum penyampaian materi dan sesudah penyampaian materi. Tahap yang kedua adalah tahap pendampingan. Pada tahap ini dilakukan pendampingan penulisan dalam bentuk review draf artikel.
ESK Pengaruh Penerapan Konsep Matematika Gasing dalam Meningkatkan Kemampuan Penjumlahan Bilangan Bulat Guru SDIT Auladi Plaju Endang Sri Kresnawati; Novi Rustiana Dewi; Bambang Suprihatin; Yulia Resti
Jurnal Pengabdian Pada Masyarakat Vol 6 No 4 (2021)
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/002.202164.882

Abstract

THE EFFECT OF MATEMATIKA GASING CONCEPTS APPLICATION IN IMPROVING THE ADDITION SKILL OF SDIT AULADI PLAJU TEACHERS. The teacher is the spearhead of the mathematics learning process at the elementary school level (SD). The SD curriculum applies a thematic system, where lower-level classes, grades 1, 2, and 3 are guided by a class teacher who is responsible for delivering material for all subjects. Includes math subjects. Problems arise when the teacher does not master the material, mathematical concepts. This is due to the background of most classroom teachers not from the field of mathematics. One of the approaches used to help increase teachers' knowledge is Gasing mathematics. In accordance with the level, the mathematical concept conveyed in the training is addition. The activity method is a general lecture and demonstration using simple props and items in the school environment. The evaluation results showed an increase in the participants' abilities by 55% compared to before. This means that the top method has succeeded in increasing the teacher's ability to complete additions more quickly and correctly.
Liver Segmentation Using Convolutional Neural Network Method with U-Net Architecture Muhammad Awaludin Djohar; Anita Desiani; Ali Amran; Sugandi Yahdin; Dewi Lestari Dwi Putri; Des Alwine Zayanti; Novi Rustiana Dewi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.6751

Abstract

Abnormalities in the liver can be used to identify the occurrence of disorders of the liver, one of which is called liver cancer. To detect abnormalities in the liver, segmentation is needed to take part of the liver that is affected. Segmentation of the liver is usually done manually with x-rays. . This manual detection is quite time consuming to get the results of the analysis. Segmentation is a technique in the image processing process that allocates images into objects and backgrounds. Deep learning applications can be used to help segment medical images. One of the deep learning methods that is widely used for segmentation is U-Net CNN. U-Net CNN has two parts encoder and decoder which are used for image segmentation. This research applies U-Net CNN to segment the liver data image. The performance results of the application of U-Net CNN on the liver image are very goodAccuracy performance obtained is 99%, sensitivity is 99%. The specificity is 99%, the F1-Score is 98%, the Jacard coefficient is 96.46% and the DSC is 98%.  The performance achieved from the application of U-Net CNN on average is above 95%, it can be concluded that the application of U-Net CNN is very good and robust in segmenting abnormalities in the liver. This study only discusses the segmentation of the liver image. The results obtained have not been applied to the classification of types of disorders that exist in the liver yet. Further research can apply the segmentation results from the application of U-Net CNN in the problem of classifying types of liver disorders.
PENERAPAN ALGORITMA TABU SEARCH PADA MODEL ACVRP UNTUK MENENTUKAN RUTE PENGANGKUTAN SAMPAH YANG OPTIMAL DI KECAMATAN KALIDONI Rani Elekta Togatorop; Fitri Maya Puspita; Sisca Octarina; Evi Yuliza; Novi Rustiana Dewi
Teorema: Teori dan Riset Matematika Vol 7, No 2 (2022): September
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/teorema.v7i2.6947

Abstract

Penulisan artikel ini membahas mengenai penerapan Algoritma Tabu Search pada model ACVRP untuk mencari rute pengangkutan sampah yang optimal di Kecamatan Kalidoni. ACVRP merupakan matriks jarak asimetris dimana perjalanan dari tempat i ke j tidak sama dengan perjalanan dari tempat j ke i. Proses algoritma berpindah dari satu solusi ke solusi berikutnya dengan memilih solusi terbaik yang ada pada Tabu List. Hasil penelitian menunjukkan bahwa rute terpendek yang diperoleh dari perhitungan menggunakan Algoritma Tabu yaitu berjarak 17,7 km pada iterasi 1, dengan rute (6 – 4 – 5 – 3 – 2 – 1 – 0) yaitu TPS 6 (Jl. Mayor Zen Mata Merah (Depan SMA N 7)) – TPS 4 (Jl. Arozak (Depan Halte Sekojo)) – TPS 5 (Jl. Arozak (Depan SPBU Sekojo)) – TPS 3 (Jl. Arozak (Depan Perumahan Buana Hijau)) – TPS 2 (Jl. Arozak (Depan Perumahan Kedamaian)) – TPA Sukawinatan.
OPTIMASI SISTEM PERENCANAAN PERSEDIAAN BUAH MENGGUNAKAN MODEL PROBABILISTIC FUZZY INVENTORY MULTI-ITEM DENGAN FUZZY LEAD-TIME Novi Rustiana Dewi; EKA SUSANTI; DES ALWINE ZAYANTI; ELI WIDIYANTI; BONGOT R. PURBA; ABDUL AZIZ ARROHMAN
Jurnal Matematika UNAND Vol 12, No 1 (2023)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.12.1.86-94.2023

Abstract

Abstrak:  Perencanaan kebijakan persediaan sangat penting terutama untuk produk-produk yang mudah rusak. Buah-buahan adalah jenis produk yang tidak tahan lama jika tidak disimpan di dalam pendingin.Tingkat kerusakan buah akan semakin meningkat jika disimpan lebih lama tanpa menggunakan ruang khusus. Hal ini berakibat menurunnya pada permintaan buah sehingga diasumsikan tingkat permintaan mengikuti distribusi eksponensial negatif. Waktu pengiriman buah ke pedagang juga tidak diketahui dengan pasti, maka nilai parameter leadtime dinyatakan dengan bilangan fuzzy. Pada makalah ini dibahas pemasalahan optimasi persediaan buah untuk meminimumkan total biaya persediaan. Terdapat 2 jenis buah yang dipertimbangkan yaitu jeruk dan salak. Model persediaan probabilistic fuzzy multi item dapat digunakan untuk menyelesaikan masalah persediaan. Berdasarkan parameter yang ditentukan diperoleh waktu peninjauan awal buah jeruk adalah 1,75 hari dan buah salak adalah 2,83 hari. Total biaya persediaan dengan variasi nilai beta semakin kecil untuk nilai beta semakin mendekati satu.Kata kunci: Fuzzy, , Inventori multi item, Probabilistik
Penerapan Model Inventori dengan Waktu Diskret dan Leadtime Pada Permasalahan Persediaan Daging Beku Eka Susanti; Des Alwine Zayanti; Endro Setyo Cahyono; Novi Rustiana Dewi; Oki Dwipurwani; Dian Cahyawati Sukanda; Muhammad 'Aqil
Jurnal Sains Matematika dan Statistika Vol 9, No 1 (2023): JSMS Januari 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v9i1.20783

Abstract

Inventory management is needed to ensure product availability and minimize the risk of loss, especially for perishable products. This study aims to determine the optimal supply of frozen meat that minimizes total costs using the analytical matrix method. The concept of Quasi-Birth-Death with discrete time and leadtime is applied for analytic matrix calculations. The results obtained were an increase in inventory levels in each inventory period with an average increase of 2.4336% and an average increase in total costs of 17.2056%.
ALGORITMA K-NEAREST NEIGHBOR (K-NN) DAN SINGLE LAYER PERCEPTRON (SLP) UNTUK KLASIFIKASI PENYAKIT ALZHEIMER Novi Rustiana Dewi; Anita Desiani; Fitri Salamah; Yuli Andriani
Jurnal Teknologi Terapan Vol 9, No 2 (2023): Jurnal Teknologi Terapan
Publisher : P3M Politeknik Negeri Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31884/jtt.v9i2.407

Abstract

Alzheimer's disease is a brain disorder that causes memory loss, decreased thinking skills, communication difficulties, and behavioral changes. Early detection of this disease is very important for proper treatment and planning of medical needs. However, there is currently no drug that can cure Alzheimer's. Therefore, this study aims to develop accurate early predictions for Alzheimer's disease by comparing two algorithms: K-Nearest Neighbor (KNN) and Single Layer Perceptron (SLP) using the percentage split method. The results showed that testing using the K-NN algorithm resulted in an accuracy of 96%. The precision and recall values for class 0 (nondemented) are 93% and 100%, respectively, while for class 1 (demented) are 100% and 91%. On the other hand, testing using the SLP algorithm produces an accuracy of 99%. The precision and recall values for class 0 (nondemented) are 97% and 100% respectively, while for class 1 (demented) are 100% and 98%. Based on a comparison of the values for accuracy, precision, and recall, as well as the performance of the two classification methods, it can be concluded that the implementation of the Single Layer Perceptron algorithm provides the best prediction for early detection of Alzheimer's disease. These findings provide potential use of this algorithm in facilitating early diagnosis and timely intervention for patients with Alzheimer's.
PERANCANGAN DAN PELATIHAN SISTEM PEMBELAJARANJARAK JAUH PADA MASA PANDEMIDI SD CENDIKIA FAIHA PALEMBANG DES ALWINE ZAYANTI; NOVI RUSTIANA DEWI; ENDANG SRI KRESNAWATI; YULIA RESTI
Jurnal Lentera Nusantara Vol 2 No 1 (2023): Jurnal Pelita Sriwijaya
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/jps.v2i1.113

Abstract

Teknologi informasi saat ini berkembang dengan cepat. Hal ini ditunjukkan dengan penggunaannya dalam berbagai bidang seperti pendidikan. Pembelajaran jarak jauh sudah dilaksanakan di SD Cendikia Faiha sejak bulan Maret 2020, dengan memanfaatkan teknologi informasi. Pengembangan dan Penyempurnaan sistem pembelajaran sangat dibutuhkan, agar kegiatan pembelajaran jarak jauh dapat lebih terpantau dan terukur. Kegiatan Perancangan dan Pelatihan Pembelajaran Jarak Jauh bertujuan untuk meningkatkan pengetahuan dan ketrampilan guru-guru di SD Cendikia Faiha dalam melaksanakan pembelajaran jarak jauh. Kegiatan dilakukan dalam 3 tahap : 1. Persiapan, 2. Pelaksanaan dan 3. Evaluasi. Hasil kegiatan pelatihan ini dapat disimpulkan bahwa perancangan dan Pelatihan Sistem Pembelajaran Jarak Jauh telah memberikan memberikan peningkatan keterampilan dalam pembelajaran jarak jauh bagi guru di SD Cendikia Faiha dalam melaksanakan pembelajaran synchronous dan asynchronous yang dapat diterapkan di SD Cendikia Faiha.
PENERAPAN MODEL INVENTORI PROBABILISTIK FUZZY MULTIOBJEKTIF PADA SISTEM PERSEDIAAN BUAH SALAK NOVI RUSTIANA DEWI; EKA SUSANTI; DES ALWINE ZAYANTI; INDRAWATI INDRAWATI; OKI DWIPURWANI; SITI NATASYA MUNAWAROH
E-Jurnal Matematika Vol 13 No 1 (2024)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2024.v13.i01.p440

Abstract

Inventory control is very important in production and trading activities. The purpose of inventory control is to maintain product availability. In certain cases, the products provided must be ordered from distributors outside the city and require waiting time from the time the order is placed until the product is received. The Multiobjective Probabilistic Fuzzy Inventory model can be applied to inventory optimization problems with the uncertainty of the leadtime parameter. In this study, the model was applied to the problem of supply salak fruit at one of the distributors. The first objective function is to minimize holding costs and the second is to minimize deterioration costs. The inventory model is transformed into a single objective form using a weighted method. Based on the results, the order cycle time is 3 days with the optimal total inventory of 430.1086 kg. The holding cost and deterioration costs are IDR 2,075,866 and IDR 571,034, respectively. Changes in the weight value of the objective function result in changes in the total cost value. The greater the weight for the first objective function, the smaller the total cost.
ON THE CONVERGENCE THEOREMS OF THE McSHANE INTEGRAL FOR RIESZ-SPACES-VALUED FUNCTIONS DEFINED ON REAL LINE Ansori, Muslim; Sumanto, Yosephus D.; Dewi, Novi Rustiana
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 3 No. 2: Desember 2007
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.579 KB) | DOI: 10.21831/pg.v3i2.654

Abstract

This paper is a partial result of our researchs in the main topic "On The McShane Integral for Riesz-Spaces-valued Functions Defined on the space ". We have constructed McShane integral for Riesz-spaces-valued functions defined on the space by a technique involving double sequences and proved some basic properties which coincides with the McShane Integral for Banach-spaces valued functions defined on real line. Further, we construct some convergence theorems involving uniformly convergence theorems, monotone convergence theorems and Fatou’s lemma in the sense of this integral.Keywords : Riesz Space, McShane Integral