Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

p-Index From 2019 - 2024

0.61

P-Index

This Author published in this journals

All Journal Jurnal Infomedia Jurnal Serambi Engineering Jurnal POLIMESIN Journal of Welding Technology Jurnal Teknologi

Amalia, Ismi

Politeknik Negeri Lhokseumawe

Author-ID : 895693

Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 6 Documents Claim Missing Document

Claim Missing Document

Articles

Sistem Pendukung Keputusan Penerimaan Bantuan Renovasi Rumah Dhuafa Menggunakan Metode Multi Attribute Utility Theory Derry Fajirwan; Muhammad Arhami; Ismi Amalia
Jurnal Infomedia:Teknik Informatika, Multimedia & Jaringan Vol 3, No 2 (2018): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Abstrak— Baitul Mal merupakan lembaga yang mengelola zakat, wakaf, dan harta agama sebagai potensi ekonomi umat Islam. Salah satu program Baitul Mal Aceh Barat Daya adalah pemberian bantuan renovasi rumah dhuafa. Dalam menentukan pemberian bantuan tersebut pihak Baitul Mal Abdya menyeleksi dari data yang masuk. Pada tahap penyeleksian ada beberapa kriteria dalam memutuskan seseorang berhak menerima atau tidak. Akan tetapi pada pelaksanaan masih menggunakan cara yang lama yaitu dengan faktor kedekatan petugas. Pada tahun 2017 setelah pergantian ketua Baitul Mal Abdya cara lama tersebut diganti dengan cara turun kelapangan untuk mengecek status kelayakan penerimaan bantuan. Untuk mendukung keputusan tersebut penulis akan membuat suatu sistem pendukung keputusan untuk menentukan kepada siapa saja yang berhak menerima bantuan rumah dhuafa berdasarkan data yang masuk. Metode yang digunakan adalah Multi Attribute Utility Theory (MAUT). Pengolahan nilai metode MAUT yaitu akan menghasilkan hasil akhir dengan perangkingan. Jadi dari perangkingan tersebut akan dipilih berdasarkan jumlah nilai tertinggi dengan batas nilai ≥ 0.58. Nilai batas 0.58 didapatkan berdasarkan hasil diskusi dengan ketua Baitul Mal Aceh Barat Daya. Dari hasil perbandingan perangkingan antara data hasil seleksi manual sebanyak 75 dengan data hasil seleksi sistem, didapatkan 60 data hasil seleksi sistem sesuai dengan hasil seleksi manual, sementara 15 data tidak sesuai dengan hasil seleksi manual. Tingkat akurasi yang didapatkan dari hasil implementasi Metode Multi Attribute Utility Theory (MAUT) mencapai 80%.Kata kunci — Sistem Pendukung Keputusan, Baitul Mal, Zakat, MAUT. Abstract— Baitul Mal is an institution that manages charity, endowments and religious property as an economic potential of Muslims. One of the Baitul Mal Aceh Barat Daya programs is the provision of renovation assistance for dhuafa homes. In determining the provision of assistance, Baitul Mal Abdya selected from incoming data. At the selection stage there are several criteria in deciding whether or not someone has the right to accept. However, the implementation still uses the old method, namely the proximity factor of the officer. In 2017 after the change of chairman of Baitul Mal Abdya the old method was replaced by the way to go down to check the status of eligibility for receiving assistance. To support this decision the author will make a decision support system to determine who has the right to receive assistance from poor households based on the data entered. The method used is Multi Attribute Utility Theory (MAUT). Processing the value of the MAUT method is that it will produce the final result by ranking. So the ranking will be chosen based on the highest number of values with a limit of ≥ 0.58. The limit value of 0.58 was obtained based on the results of discussions with the head of the Baitul Mal Aceh Barat Daya. From the results of the comparison of the ranking between the manual selection data as much as 75 with the data of the system selection results, obtained 60 data from the system selection results in accordance with the results of manual selection, while 15 data were not in accordance with the results of manual selection. The level of accuracy obtained from the implementation of the Multi Attribute Utility Theory (MAUT) method reaches 80%.Keywords — Decision Support System, Baitul Mal, Zakat, MAUT

Ekstraksi Fitur Citra Songket Berdasarkan Tekstur Menggunakan Metode Gray Level Co-occurrence Matrix (GLCM) Ismi Amalia
Jurnal Infomedia:Teknik Informatika, Multimedia & Jaringan Vol 3, No 2 (2018): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Abstrak— Songket merupakan warisan budaya Indonesia yang harus dijaga dan dilestarikan. Pelestarian songket dapat dilakukan dengan pendataan secara komputerisasi. Pendataan dapat dilakukan dengan pengenalan pola motif songket. Dalam pengenalan pola, ekstraksi fitur merupakan hal yang penting untuk mendapatkan informasi citra digital. Informasi dari hasil ekstraksi fitur digunakan dalam proses klasifikasi. Penelitian ini akan mengekstraksi fitur citra songket Aceh. Ekstraksi fitur tekstur menggunakan metode Gray Level Co-Occurrence Matrix (GLCM). Hasil ekstraksi fitur dapat digunakan untuk pendataan citra songket Aceh serta juga dapat digunakan untuk klasifikasi motif songket Aceh dengan menggunakan Jaringan Syaraf Tiruan (JST). Pengumpulan data pada penelitian ini melalui observasi dan wawancara. Implementasi metode yang diusulkan menggunakan Matlab R2009a. Pengujian menggunakan lima sampel citra songket Aceh. Hasil penelitian ini adalah nilai-nilai parameter dari metode GLCM meliputi fitur entropy, sum average, difference entropy dan autocorrelation. Diharapkan fitur-fitur ini dapat digunakan untuk proses klasifikasi citra songket Aceh.Kata kunci— Ekstraksi fitur, Gray Level Co-Occurrence Matrix (GLCM), Jaringan Syarat Tiruan (JST), Songket Aceh. Abstract - Songket is an Indonesian cultural heritage that must be preserved and preserved. The preservation of songket can be done by computerizing data collection. Data collection can be done by introducing songket motif patterns. In pattern recognition, feature extraction is important for obtaining digital image information. Information from the results of feature extraction is used in the classification process. This study will extract the features of the Aceh songket image. Texture feature extraction using the Gray Level Co-Occurrence Matrix (GLCM) method. Feature extraction results can be used for data collection of Aceh songket images and can also be used for the classification of Aceh songket motifs using Artificial Neural Networks (ANN). Data collection in this study through observation and interviews. The implementation of the proposed method uses Matlab R2009a. The test uses five samples of Aceh songket images. The results of this study are the parameter values of the GLCM method including entropy features, sum average, difference entropy and autocorrelation. It is expected that these features can be used for the process of classification of Aceh songket images.Keywords - Feature extraction, Gray Level Co-Occurrence Matrix (GLCM), Artificial Condition Network (ANN), Aceh SongketKeywords -

Pengaruh jenis kampuh terhadap ketangguhan sambungan pengelasan material St37 dengan AISI 1050 menggunakan proses SMAW Muhammad Siddiq; Nurdin Nurdin; Ismi Amalia
Journal of Welding Technology Vol 1, No 1 (2019): June
Publisher : Politeknik Negeri Lhokseumawe

The strength of the material joints is one of the expected goals of the material joints process using the welding process. This study aims to determine the effect of welding groove on the toughness of the welded joints in the SMAW welding process by using E7016 electrodes. This research uses St37 and AISI 1050 steel materials, St37 including low carbon steel and Aisi 1050 including medium carbon steel. The material is given a welding treatment with a variation of single V groove, single tire, and double tire using reverse DC polarity SMAW welding, the welding position used is horizontal or underhanded and the current used is 100 Amperes. The welding specimens were tested by the charpy method to determine the value of the material joints toughness. The Charpy Method Impact test results show that specimens of single V groove, single tapered, and Double tapered have varying absorbed energy values. Single V groove has the highest absorbed energy value with an average value of 256 Joules and 3.21 Joules / mm2, compared to single tapered and double tapered groove. The type of fracture obtained is also different, for specimen V groove and a single tapered duct fracture while double tapered groove occurs brittle fracture.Keywords: Groove, SMAW, Toughness, E7016, St37 steel and AISI 1050AbstrakKekuatan sambungan material merupakan salah satu tujuan yang diharapkan dari proses penyambungan material menggunakan proses pengelasan. Penelitian ini bertujuan untuk mengetahui pengaruh kampuh pengelasan terhadap ketangguhan sambungan las pada proses las SMAW dengan menggunakan elektroda E7016. Penelitian ini menggunakan material baja St37 dan AISI 1050, St37 termasuk baja karbon rendah dan Aisi 1050 termasuk baja karbon sedang. Bahan diberi perlakuan pengelasan dengan variasi kampuh V tunggal, Tirus tunggal, dan Tirus ganda dengan menggunakan las SMAW DC polaritas terbalik, posisi pengelasan yang digunakan adalah mendatar atau bawah tangan dan arus yang digunakan adalah 100 Ampere. Spesimen pengelasan dilakukan pengujian impak metode charpy untuk mengetahui nilai ketangguhan sambungan material. Hasil pengujian Impak Metode charpy menunjukkan bahwa spesimen kampuh V tunggal, tirus tunggal, dan tirus Ganda memiliki nilai energi yang diserap bervariasi. Kampuh V tunggal mempunyai nilai energi yang diserap tertinggi dengan nilai rata-ratanya sebesar 256 Joule dan 3,21 Joule/mm2, dibandingkan dengan kampuh tirus tunggal dan tirus ganda. Jenis perpatahan yang didapat juga berbeda, untuk spesimen kampuh V dan tirus tunggal terjadi patah ulet sedangkan kampuh tirus ganda terjadi patah getas.Kata kunci : Kampuh, SMAW, Ketangguhan, E7016, baja St37 dan AISI 1050

PENGENALAN CITRA TANDA TANGAN MENGGUNAKAN GRAY LEVEL CO-OCCURRENCE MATRIX (GLCM) DAN PROBABILISTIC NEURAL NETWORK (PNN) Ismi Amalia
Jurnal Teknologi Vol 14, No 1 (2014): Jurnal Teknologi
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v14i1.261

The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. There are various approaches to signature recognition with a lot of scope of research. In this paper, off-line signature recognition using probabilistic neural network is proposed, where the signature is captured and presented to the user in an image format. Signatures are recognized based on parameters extracted from the signature using gray level co-occurrence matrix. The features obtained are dissimilarity, entropy, and homogeneity. The recognition and verification was performed using probabilistic neural network. The proposed algorithm was tested on 100 signatures. The images of signature were divided in two sets: training set and test set. The leave-one-out cross-validation technique was applied for model validation. The research showed that the average accuracy from PNN was 71%

Investigation of the Mechanical Behavior of Laminated Composites Gypsum-Based Plastic Sack Waste Fiber Indra Mawardi; Samsul Bahri; Hamdani Nurdin; Irwin Syahri Cebro; Luthfi Luthfi; Zuhaimi Zuhaimi; Ismi Amalia
Jurnal POLIMESIN Vol 21, No 1 (2023): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v21i1.3275

The existence of plastic waste, such as used plastic sacks in large quantities, is a crucial problem for the environment and health because of its very low biodegradability. Therefore, reusing plastic sack waste as reinforcement in gypsum composites is a major research issue. This study investigates the mechanical and physical properties of gypsum composites reinforced with fiber layers from plastic sack waste. Gypsum composites are produced using casting gypsum flour as the matrix and various fiber layers from plastic sack waste (1, 2, 3, 4) as reinforcement. Gypsum-based laminated composites were tested for density, flexural strength, and compression. The behavior of mechanical, physical, and damage properties is studied to see its suitability as a building material. The results showed that gypsum composites' density decreased with increasing sack fiber layers. The density of gypsum composites ranges from 1064-1199 kg/m3, with a maximum value in samples with 100% gypsum. The flexural strength of gypsum composites ranges from 2.21-4.10 MPa, and the compressive strength ranges from 3.5-6.66 MPa. Increasing the number of layers of plastic sack fibers reduces density, flexural strength, and compressive strength. However, all the mechanical properties of gypsum composites met the requirements of the EN 13279-2 standard. Failure of fiber delamination with the resulting matrix is the main cause of the decrease in mechanical strength

Klasifikasi Citra Songket Aceh Menggunakan Metode Probabilistic Neural Network Ismi Amalia; Indra Mawardi; Indrawati Indrawati; Muhammad Arhami; Muhammad Muhammad; Guntur Syahputra
Jurnal Serambi Engineering Vol 8, No 3 (2023): Juli 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i3.6132

Tujuan penelitian ini untuk mengklasifikasikan citra Songket Aceh. Data penelitian menggunakan sepuluh motif Songket Aceh dan data diperoleh dari tempat usaha tenun Songket Nyak Mu. Tahapan penelitian ini adalah akuisisi citra, pra-proses, ekstraksi fitur, klasifikasi dan evaluasi. Ekstraksi fitur tekstur citra Songket Aceh menggunakan metode Gray Level Co-occurrence Matrix (GLCM). Fitur-fitur yang digunakan pada penelitian ini adalah entropy, energy, sum of squares: variance, difference entropy dan autocorrelation. Metode Probabilistic Neural Network (PNN) diaplikasikan untuk klasifikasi citra Songket Aceh. Metode Leave-One-Out Cross Validation (LOOCV) digunakan untuk pembagian data latih dan data uji. Hasil klasifikasi citra Songket Aceh dengan metode PNN adalah sebesar 93%.

Co-Authors Arhami, Muhammad Derry Fajirwan Guntur Syahputra Hamdani, Hamdani indra Mawardi Indra Mawardi Indrawati Indrawati Irwin Syahri Cebro Luthfi Luthfi Muhammad Muhammad Muhammad Siddiq Nurdin Nurdin Samsul Bahri Zuhaimi Zuhaimi

Title

Found 6 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 6 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 6 Documents
Search