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All Journal Jurnal Matematika Sainstek Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Riset Kimia Annual Research Seminar LIBRARIA Proceeding of the Electrical Engineering Computer Science and Informatics AKSIOMA Jurnal Penelitian Sains Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Infomedia JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Jurnal Teknik Elektro dan Komputasi (ELKOM) International Journal of Applied Sciences and Smart Technologies Jurnal Pedagogi dan Pembelajaran TADBIR: Jurnal Manajemen Dakwah FDIK IAIN Padangsidimpuan BAKTI : Jurnal Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) Bakti: Jurnal Pengabdian Kepada Masyarakat
Ali Amran
Sriwijaya University
Religion Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Pemanfaatan marketplace shopee sebagai strategi untuk meningkatkan pemasaran kain songket Anita Desiani; Irmeilyana Irmeilyana; Ajeng Islamia Putri; Enyta Yuniar; Nur Avisa Calista; Siddiq Makhalli; Ali Amran
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 4, No 2 (2021): Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v4i2.9222

Abstract

South Sumatera songket woven cloth is one of the cultural assets of South Sumatera Province which is usually used at weddings and other traditional ceremonies. One of the villages which is famous as a producer of songket cloth is a Penyandingan Village. The songket cloth industry in Penyandingan Village experienced a decline in turnover of up to 60% during the Covid-19 pandemic. This is supported by the lack of knowledge of society regarding marketing strategies and technology in marketing products. For this reason, Shopee market management training is needed for songket cloth craftsmen and the Penyandingan Village society through the Sriwijaya University Thematic Community Service team program so that the marketing of songket fabrics can reach a wide market and be able to compete with other products. The method used is the lecture method including data collection planning and implementation of activities. The research analysis uses descriptive analysis to provide a general description of the implementation of the Shopee marketplace training. After the training was carried out,  Penyandingan Village society was able to understand the material and apply it directly using the Shopee application, and could be applied on a sustainable scale so that sales of songket cloth could increase.
Pembelajaran Pengukuran Menggunakan Pendekatan Matematika Realistik Untuk Peserta Didik SD Negeri 04 Indralaya Selatan Anita Desiani; Sugandi Yahdin; Hermansyah; Ali Amran; Bambang Suprihatin; Muhammad Azwar Annas; Mega Tiara Putri; Carolina Rahman; Alga Mahida
BAKTI : Jurnal Pengabdian Kepada Masyarakat Vol. 2 No. 1 (2022): BAKTI : Jurnal Pengabdian Kepada Masyarakat
Publisher : LLDikti Wilayah XII Maluku dan Maluku Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51135/baktivol2iss1pp21-32

Abstract

Matematika merupakan sebuah pelajaran yang cukup sulit bagi banyak peserta didik. Sistem pembelajaran yang diajarkan bisa menjadi faktor peserta didik menyukai pelajaran Matematika. Salah satu metode belajar yang mudah dipahami dan mengasyikkan untuk peserta didik yaitu metode pembelajaran Matematika realistik. Kegiatan pembelajaran dengan pendekatan Matematika Realistik dilakukakan di Sekolah Dasar Negeri 04 Indralaya Selatan di desa Beti yang memiliki 68 peserta didik dan 11 guru. Kegiatan ini diberikan pada sisa kelas 2 dan kelas 3 karena proses pengajaran ini difokuskan pada materi pengukuran. Kegiatan ini dilakukan dengan cara pemberian materi, latihan dan diskusi. Untuk mengetahui sejauh mana pemahaman siswa dilakukan pre-test dan post-test untuk materi Matematika pengukuran yang telah diberikan.  Dari hasil pre-test dan post-test yang diberikan terlihat pemahaman siswa kelas 2 dan kelas 3 meningkat. Hal ini dapat diliat dari skor yang diperoleh sebelum dilakukan kegiatan yaitu rata-rata hanya 66.33 poin. Hasil setelah dilakukan kegiatan skor rata-rata dari peserta naik menjadi 80. Hal ini menunjukan pembelajaran Matematika pengukuran dengan pendekatan Matematika realistik mampu membantu dan meningkatkan minat dari siswa dalam mempelajari Matematika terutama bagi siswa kelas 2 dan kelas 3 SD Negeri 04 Indralaya.
Independence Test and Plots in Correspondence Analysis to Explore Tracer Study Data Endang Sri Kresnawati; Irmeilyana Irmeilyana; Ali Amran; Danny Matthew Saputra
International Journal of Applied Sciences and Smart Technologies Volume 03, Issue 02, December 2021
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v3i2.3891

Abstract

The results of the exploration of tracer study data can be used as information about the career of graduates and the relevance of work to the field of study as well as the competencies obtained before graduation. The question items discussed were a description of the time and process of looking for a job, the length of time to get the first job, the relationship between length of study, gender, field of work, total income, alumni's perception of the closeness of the field of study to work, the suitability of the level of education on the job, and average level of competence. The aim of this study was to analyze the relationship between these variables in the 2020 tracer study data from graduates of all faculties at Sriwijaya University. Respondents studied were 2,669 people. The method used is descriptive statistics, biplot analysis, independence test and plots by simple correspondence analysis. Respondents' perceptions of the suitability of the level of education in employment are related to gender and also with respondents' perceptions of the closeness of the field of study to the field of work. Meanwhile, respondents' perceptions of the closeness of the field of study with work are related to the field of work. The average length of study, the average number of job applications, the number of companies or agencies that responded to applications, and invited interviews for female respondents were lower than male respondents.
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.
Application of the Waterfall Method in Software Design on Android-Based Programming Language Course Applications Anita Desiani; Ali Amran; Nuni Gofar; Chairu Nisa Apriyani; Redina An Fadhila Chaniago
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.v6i1.6995

Abstract

In this era of technology and information proliferating, programming skills are needed. Technology affects every area of life from industry, business, communication, transportation, health, and others. Everyone has the same opportunity to learn and master technology thus programming language courses are needed to provide education, innovation, and improvement of skills and abilities in the field of programming and data science to the public. Until now, programming language courses still use the conventional system, where everything is done manually, from class registration, class scheduling, teaching and learning process, and payment processing which results in many archives that must be stored for administrative purposes and require a relatively large amount of time for customers to come to the course location. Therefore, an information technology-based system is needed to fix the weaknesses of the old system. In this study, an Android-based programming language course application is designed to facilitate customers and course owners in teaching and learning activities and transactions. The design in this study uses the waterfall method, which consists of five stages, needs analysis, design, code, testing, and maintenance. The results obtained from testing applications using questionnaires on programming language course applications are 80% stated by course customers, where the application is easy to use, faster, and more practical in registering. In conclusion, this designed application can make it easier for customers to carry out teaching and learning activities and transact quickly and practically.
Comparison of Support Vector Machine and K-Nearest Neighbors in Breast Cancer Classification Anita Desiani; Adinda Ayu Lestari; M Al-Ariq; Ali Amran; Yuli Andriani
Pattimura International Journal of Mathematics (PIJMath) Vol 1 No 1 (2022): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (470.745 KB) | DOI: 10.30598/pijmathvol1iss1pp33-42

Abstract

Cancer is one of the leading causes of death, and breast cancer is the second leading cause of cancer death in women. One method to realize the level of malignancy of breast cancer from an early age is by classifying the cancer malignancy using data mining. One of the widely used data mining methods with a good level of accuracy is the Support Vector Machine (SVM) and K-Nearest Neighbors (KNN). Evaluation techniques of percentage split and cross-validation were used to evaluate and compare the SVM and KNN classification models. The result was that the accuracy level of the SVM classification method was better than the KNN classification method when using the cross-validation technique, which is 95,7081%. Meanwhile, the KNN classification method was better than the SVM classification method when using the percentage split technique, which is 95,4220%. From the comparison results, it can be seen that the KNN and SVM methods work well in the classification of breast cancer.
Implementasi Algoritma Naïve Bayes dan Support Vector Machine (SVM) Pada Klasifikasi Penyakit Kardiovaskular Anita Desiani; Muhammad Akbar; Irmeilyana Irmeilyana; Ali Amran
Jurnal Teknik Elektro dan Komputasi (ELKOM) Vol 4, No 2 (2022): ELKOM
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/elkom.v4i2.7691

Abstract

Penyakit kardiovaskuler adalah penyakit yang diakibatkan penyempitan atau penyumbatan pembuluh darah di jantung penyakit ini disebabkan gangguan fungsi jantung dan pembuluh darah. Sistem kardiovaskular terdiri dari jantung dan pembuluh darahnya. Penelitian ini bertujuan melakukan klasifikasi penyakit kardiovaskular untuk memprediksi suatu pola. Pada penelitian ini akan menggunakan metode support vector machine dan naïve bayes dengan metode latih percentage split dan k-fold cross validation. Hasil akurasi pengolahan menggunakan Algoritma Naïve Bayes adalah sebesar 70% untuk metode latih percentage split dan 71% untuk metode latih k-fold cross validation. Kemudian dengan menggunakan algoritma support vector machine didapat akurasi 61% untuk metode latih percentage split dan 65% untuk metode latih k-fold validation. Hasil tersebut menunjukkan bahwa algoritma naïve bayes dengan metode latih k-fold validation cukup baik dalam melakukan klasifikasi penyakit kardiovaskular.
Perbandingan Klasifikasi Penyakit Kanker Paru-Paru menggunakan Support Vector Machine dan K-Nearest Neighbor Anita Desiani; Sri Indra Maiyanti; Yuli Andriani; Bambang Suprihatin; Ali Amran; Nyanyu Chika Marselina; Aulia Salsabila
Jurnal PROCESSOR Vol 18 No 1 (2023): Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2023.18.1.700

Abstract

Lung cancer is a condition where cells grow uncontrollably in the lungs due to carcinogens. Lung cancer is the first cause of death in men and women’s second cause of death. One way to reduce the death rate due to lung cancer is to carry out early detection, that is classification. The process of identifying and grouping objects with the same characteristics or characteristics into several predetermined classes is called classification. Several algorithms widely used in the classification process are Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). SVM has advantages, being able to identify hyperplanes separately to maximize the margin between two or more different classes, but it is difficult to use in large data, while KNN can perform large-scale data separation and is resilient to noise in the data. This study aims to build a model using the SVM and KNN algorithms to classify lung cancer. The lung cancer dataset has a total of 309 data, where data is divided using the percentage split method and k-fold cross validation on each algorithm used. The parameters used in evaluating the model are accuracy, precision, and recall. From the research, the highest accuracy, precision, and recall values were obtained in the SVM algorithm with the percentage split method with consecutive values, namely 95.16%, 88%, and 82.5%. This indicates that the SVM algorithm with the percentage split method performs better in classifying lung cancer than other algorithms and methods,
Pembelajaran Pengukuran Menggunakan Pendekatan Matematika Realistik Untuk Peserta Didik SD Negeri 04 Indralaya Selatan Anita Desiani; Sugandi Yahdin; Hermansyah Hermansyah; Ali Amran; Bambang Suprihatin; Muhammad Azwar Annas; Mega Tiara Putri; Carolina Rahman; Alga Mahida
Bakti: Jurnal Pengabdian Kepada Masyarakat Vol. 2 No. 1 (2022): BAKTI : Jurnal Pengabdian Kepada Masyarakat
Publisher : LLDikti Wilayah XII Maluku dan Maluku Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51135/baktivol2iss1pp21-32

Abstract

Matematika merupakan sebuah pelajaran yang cukup sulit bagi banyak peserta didik. Sistem pembelajaran yang diajarkan bisa menjadi faktor peserta didik menyukai pelajaran Matematika. Salah satu metode belajar yang mudah dipahami dan mengasyikkan untuk peserta didik yaitu metode pembelajaran Matematika realistik. Kegiatan pembelajaran dengan pendekatan Matematika Realistik dilakukakan di Sekolah Dasar Negeri 04 Indralaya Selatan di desa Beti yang memiliki 68 peserta didik dan 11 guru. Kegiatan ini diberikan pada sisa kelas 2 dan kelas 3 karena proses pengajaran ini difokuskan pada materi pengukuran. Kegiatan ini dilakukan dengan cara pemberian materi, latihan dan diskusi. Untuk mengetahui sejauh mana pemahaman siswa dilakukan pre-test dan post-test untuk materi Matematika pengukuran yang telah diberikan.  Dari hasil pre-test dan post-test yang diberikan terlihat pemahaman siswa kelas 2 dan kelas 3 meningkat. Hal ini dapat diliat dari skor yang diperoleh sebelum dilakukan kegiatan yaitu rata-rata hanya 66.33 poin. Hasil setelah dilakukan kegiatan skor rata-rata dari peserta naik menjadi 80. Hal ini menunjukan pembelajaran Matematika pengukuran dengan pendekatan Matematika realistik mampu membantu dan meningkatkan minat dari siswa dalam mempelajari Matematika terutama bagi siswa kelas 2 dan kelas 3 SD Negeri 04 Indralaya.
Pengaruh DAR dan Ukuran Perusahaan Terhadap ROA Perusahaan yang Terdaftar Di LQ45 Pada BEI Luckieta, Meiliani; Amran, Ali; Alamsyah, Doni Purnama
Perspektif : Jurnal Ekonomi dan Manajemen Akademi Bina Sarana Informatika Vol 19, No 1 (2021): Maret 2021
Publisher : www.bsi.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jp.v19i1.9235

Abstract

Penelitian ini dilaksanakan dengan tujuan untuk menganalisis adanya pengaruh dari Struktur Modal (DAR) dan Ukuran Perusahaan terhadap profitabilitas perusahaan (ROA) yang terdaftar di LQ45 pada BEI sehingga dapat memberikan gambaran dan pemahaman yang mendalam untuk digunakan para investor dan pelaku bisnis dalam upaya meningkatkan profitabilitas perusahaannya. Metode yang digunakan adalah metode verifikatif. Variabel yang digunakan adalah variabel Struktur Modal (DAR) dan ukuran perusahaan sebagai variabel independent, variabel profitabilitas perusahaan (ROA) sebagai variabel dependent. Sumber data yang digunakan adalah data sekunder berupa laporan keuangan 23 perusahaan yang aktif selama periode 2013 – 2017 dan terdaftar di LQ 45 Bursa Efek Indonesia. Sedangkan Teknik pengumpulan data yang digunakan yaitu dengan metode dokumentasi, berdasarkan kriteria-kriteria yang telah diseleksi diperoleh 23 perusahaan sebagai sampel penelitian. Sumber data berasal dari Laporan Keuangan Perusahaan yang terdaftar di LQ 45 Bursa Efek Indonesia periode 2013 – 2017. Teknik analisis data menggunakan Analisis Regresi Linier Sederhana dengan Program SPSS 20. Hasil penelitian ini membuktikan secara parsial bahwa Struktur Modal berpengaruh secara positif dan signifikan terhadap Profitabilitas Ukuran Perusahaan berpengaruh terhadap Profitabilitas Struktur Modal dan Ukuran Perusahaan secara  bersama-sama berpengaruh terhadap ProfitabilitasKata Kunci: Ukuran Perusahaan, ROA, DAR.
Co-Authors Adinda Ayu Lestari Ajeng Islamia Putri Alfensi Faruk Alga Mahida Anita Desiani Apriyani, Eka Ardila, Nebi Aulia Salsabila Bambang Suprihatin Carolina Rahman Chairu Nisa Apriyani Chairunnisa Siregar, Fitri Danny Matthew Saputra Danny Matthew Saputra Des Alwine Zayanti, Des Alwine Dewi Lestari Dwi Putri Dian Cahyawati Doni Purnama Alamsyah Endang Sri Kresnawati Enyta Yuniar Evi Yuliza, Evi Ganafri, Ganafri HARDIMANSYAH HARDIMANSYAH Hasibuan, MS Hermansyah Hermansyah Hermansyah Indah Verdya Alvionita Irmeilyana Luckieta, Meiliani M Al-Ariq Maya Meilensa Mega Tiara Putri MS Hasibuan Muhammad Akbar Muhammad Awaludin Djohar Muhammad Azwar Annas Ngudiantoro . Nopri Nasir Novi Rustiana Dewi NUNI GOFAR Nur Avisa Calista Nyanyu Chika Marselina Redina An Fadhila Chaniago Shintia, Clara Siddiq Makhalli Sri Indra Maiyanti Sugandi Yahdin Triyani Triyani Yuli Andriani Yuli Andriani