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Rizal Amegia Saputra
Universitas Bina Sarana Informatika
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Meningkatkan Akses Pelayanan, Akuntabilitas Dan Transparansi Koperasi Simpan Pinjam Melalui SIMOKO Rahayu, Yuri; Ramdhani, Lis Saumi; Riyanto, Andi; Saputra, Rizal Amegia
Evolusi : Jurnal Sains dan Manajemen Vol 12, No 1 (2024): Jurnal Evolusi 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/evolusi.v12i1.21171

Abstract

Digitalization has not been fully implemented by cooperative institutions, especially for cooperatives in the community, so data and information cannot be accessed by all interested parties, especially members. Therefore, the digitalization of cooperatives, which is a reform step in cooperatives, is very important to be implemented immediately so that cooperatives are able to be competitive in the current digital era and can reach millennials. SIMOKO (Cooperative Mobile Information System) is the first step so that cooperatives can advance in class and be technologically literate. The problems currently faced by partners are 1). The data processing system is still recorded manually by the treasurer assisted by the secretary and then reported to the chairman, especially in loan applications, checking loan balances and total savings. 2). Publication, there is no publication media so the addition of members every year is slow, the ongoing process of developing and adding members only relies on a word of mouth strategy. 3). Financial reporting is still less than optimal and not timely, and 4). Management of Information Systems with the support of information technology is not yet visible, so knowledge and understanding of using information technology platforms is still not visible. The research method used is Research and Development, namely the method used to design an application. The solution to the problem is the application of the SIMOKO Application (Mobile Cooperative Information System). This application is expected to accommodate the problems faced by Savings and Loans Cooperatives. In this application there are various features for both members and administrators: member biodata features, loan applications, balance checks loans, checking total deposits, preparing financial reports.Digitalisasi belum sepenuhnya diterapkan oleh lembaga koperasi terlebih untuk koperasi yang berada di masyarakat sehingga data dan informasi belum bisa di akses oleh semua pihak yang berkepentingan terutama anggota. Maka dari itu digitalisasi koperasi yang merupakan langkah reformasi dalam koperasi menjadi sangat penting untuk segera di implementasikan agar koperasi mampu berdaya saing di era digital saat ini dan bisa menyentuh kaum milenial. SIMOKO (Sistem Informasi Mobile Koperasi) merupakan Langkah awal agar koperasi bisa naik kelas dan melek Teknologi. Permasalahan yang dihadapi oleh mitra saat ini yaitu 1).Sistem pengolahan data masih dicatat manual oleh bendahara dibantu sekretaris dan selanjutnya dilaporkan kepada ketua terutama dalam pengajuan pinjaman, cek sisa pinjaman dan total simpanan. 2). Publikasi, belum memilikinya media publikasi sehingga penambahan anggota tiap tahun lambat, proses berjalan dalam mengembangkan dan penambahan anggota hanya mengandalkan strategi mulut ke mulut. 3). Pelaporan keuangan masih kurang optimal dan tidak tepat waktu,  dan 4). Pengelolaan Sistem Informasi dengan dukungan teknologi informasi belum nampak, sehingga pengetahuan dan pemahaman dengan menggunakan platform teknologi informasi masih belum nampak. Metode penelitioan yang dipakai adalah Research and Development yaitu  Metode yang digunakna untuk merancang sebuah Aplikasi. Solusi atas permasalahan   yaitu penerapan Aplikasi SIMOKO (Sistem Informasi Mobile Koperasi) aplikasi ini diharapkan dapat mengakomodir permasalahan-permasalahan yang dihadapi oleh Koperasi Simpan Pinjam, pada aplikasi ini terdapat berbagai macam fitur baik untuk anggota maupun pengurus  : fitur biodata anggota, pengajuan pinjaman, cek sisa pinjaman, cek total simpanan, pembuatan pelaporan keuangan.
PENERAPAN METODE ITERATIVE DICHOTOMIZER 3 (ID 3) UNTUK MENENTUKAN BEASISWA BERPRESTASI PADA SMP PGRI CARINGIN SUKABUMI Saputra, Rizal Amegia; Ramdhani, Lis Saumi; Supriatman, Supriatman
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1207.643 KB) | DOI: 10.33480/pilar.v15i1.29

Abstract

Scholarships are assistance from the government to students / students who are less able or have the ability in the academic and non-academic fields that are given individually to reduce the burden in terms of material. Frequently stalling time in selection, the number of students who apply for scholarships, the number of students whose homes are far from school, the number of students who race to come early as one of the criteria eligible to receive scholarships as well as the most scholarship applicants feel disadvantaged by unfavorable decisions. Iterative Dichotomizer 3 (ID3) algorithm is the most basic decision tree learning algorithm (decision tree learning algorithm). This algorithm conducts a thorough search on all possible decisions. In this research, it will be analyzed the application of the iterative dichotomizer 3 method in the case of determining achievement scholarships. In order to make decisions quickly and accurately. From 708 scholarship candidates including 28 eligible and 680 scholarship recipients, 136 scholarship recipients were obtained from ID3 algorithm with 3 eligible and 133 who had not, and obtained an accuracy rate of 97.75% so that it could be concluded that good and can help the school.
APPLICATION OF EXPERT SYSTEM FOR ANDROID-BASED FOOD LAND SUITABILITY AND HOLTICULTURE Ramdhani, Lis Saumi; Susilawati, Desi; Saputra, Rizal Amegia
Jurnal Pilar Nusa Mandiri Vol 16 No 2 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v16i2.1461

Abstract

Plant land suitability is a way of evaluating the characteristics of planted land-based on certain criteria to determine which types of plants are most suitable for planting in that land, land suitability has not been utilized properly by farmers due to limited knowledge about the varieties of plant types that can be planted in their land, selection The types of plants are still based on traditions and elements of the surrounding agricultural environment which are only limited to a few types of plants without taking into account the suitability of the plants planted to their land characteristics. For this reason, an expert system application was created to help farmers determine the suitability of land for food crops and horticulture on an Android basis because on an Android basis it can make it easier for users, especially farmers to determine the suitability of their land without the need to find a plant land expert and can easily accessible to anyone, anywhere. To produce a good expert system, the research method will be used, namely the certainty factor method. The results of testing expert system applications with certainty factor methods are proven to be able to provide accurate land suitability information
ABILITY CONVOLUTIONAL FEATURE EXTRACTION FOR CHILI LEAF DISEASE USING SUPPORT VECTOR MACHINE CLASSIFICATION Saputra, Rizal Amegia; Haryanto, Toto; Wasyianti, Sri
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.4961

Abstract

Chili plants are among the most commonly used food ingredients in various dishes in Indonesia. Leaves on chili plants are often affected by disease; if the disease is not treated immediately, it can damage the plant and cause crop failure. Early detection of chili plant diseases is important to reduce the risk of crop failure. The development of technology and the application of machine-learning algorithms can automatically monitor chili plants using a computer system. Using this algorithm, the system analyzes and identifies diseases that a camera can observe and record. In this study, the proposed method for feature extraction uses a convolutional neural network (CNN) algorithm with transfer learning using VGG19. For classification using SVM for training data, accuracy generated 95%, precision 95%, recall 95%, and F1-Score 95%, and testing data accuracy generated 90%, precision 89%, recall 90%, and F1-Score 89%, proving that the convolutional process with architecture VGG19 and SVM algorithm is acceptable for classification. In future research, other architectures or extraction fusions can be used to maximize the results.
Automated Staging of Diabetic Retinopathy Using Convolutional Support Vector Machine (CSVM) Based on Fundus Image Data Novitasari, Dian C Rini; Fatmawati, Fatmawati; Hendradi, Rimuljo; Nariswari, Rinda; Saputra, Rizal Amegia
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1501

Abstract

Diabetic Retinopathy (DR) is a complication of diabetes mellitus, which attacks the eyes and often leads to blindness. The number of DR patients is significantly increasing because some people with diabetes are not aware that they have been affected by complications due to chronic diabetes. Some patients complain that the diagnostic process takes a long time and is expensive. So, it is necessary to do early detection automatically using Computer-Aided Diagnosis (CAD). The DR classification process based on these several classes has several steps: preprocessing and classification. Preprocessing consists of resizing and augmenting data, while in the classification process, CSVM method is used. The CSVM method is a combination of CNN and SVM methods so that the feature extraction and classification processes become a single unit. In the CSVM process, the first stage is extracting convolutional features using the existing architecture on CNN. CSVM could overcome the shortcomings of CNN in terms of training time. CSVM succeeded in accelerating the learning process and did not reduce the accuracy of CNN's results in 2 class, 3 class, and 5 class experiments. The best result achieved was at 2 class classification using CSVM with data augmentation which had an accuracy of 98.76% with a time of 8 seconds. On the contrary, CNN with data augmentation only obtained an accuracy of 86.15% with a time of 810 minutes 14 seconds. It can be concluded that CSVM was faster than CNN, and the accuracy obtained was also better to classify DR.
Transformasi Pengelolaan Koperasi Syariah Dengan Aplikasi SIKOMPAK Sebagai Jaring Pengaman Kesejahteraan Dosen Rahayu, Yuri; Riyanto, Andi; Saputra, Rizal Amegia; Bahri, Saeful
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 9, No 2 (2024): November 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcit.v9i2.24444

Abstract

Koperasi Syariah Dosen Universitas Bina Sarana Informatika di Sukabumi mengalami transformasi dengan implementasi aplikasi SIKOMPAK untuk memperkuat prinsip akuntabilitas dan transparansi. Berangkat dari permasalahan minimnya akuntabilitas dan transparansi real-time pada transaksi koperasi yang masih berbasis media sederhana, penelitian ini mengembangkan dan menguji aplikasi SIKOMPAK. Penelitian ini bertujuan mengevaluasi kenyamanan anggota dalam mengakses layanan keuangan koperasi melalui SIKOMPAK. Menggunakan metode Research and Development, aplikasi ini dikembangkan dan diuji dengan pendekatan kuantitatif. Hasil penelitian menunjukkan bahwa penggunaan SIKOMPAK memudahkan anggota melakukan transaksi keuangan, meningkatkan kenyamanan, serta mendukung kesejahteraan anggota melalui fitur seperti simpanan, pinjaman, dan laporan keuangan. Analisis kuantitatif menunjukkan adanya hubungan positif yang signifikan antara aksesibilitas dan fitur aplikasi dengan persepsi kesejahteraan anggota. Kesimpulannya, SIKOMPAK berpotensi menjadi model bagi koperasi lain dalam upaya meningkatkan kesejahteraan dosen melalui digitalisasi layanan berbasis syariah. The Sharia Cooperative for Lecturers at Universitas Bina Sarana Informatika in Sukabumi has undergone transformation through the implementation of the SIKOMPAK application to reinforce principles of accountability and transparency. Addressing issues of limited real-time accountability and transparency in cooperative transactions, which were previously managed with simple media, this study developed and tested the SIKOMPAK application. The research aims to evaluate member convenience in accessing cooperative financial services via SIKOMPAK. Utilizing a Research and Development approach, the application was developed and tested through a quantitative methodology. The findings indicate that SIKOMPAK facilitates financial transactions, enhances user convenience, and supports member welfare through features such as savings, loans, and financial reports. Quantitative analysis reveals a significant positive relationship between the application’s accessibility and features with members' perceived welfare. In conclusion, SIKOMPAK has the potential to serve as a model for other cooperatives in improving lecturers’ welfare through the digitalization of Sharia-based services.
Implementasi Algoritma Random Forest Untuk Menentukan Penerima Bantuan Raskin Kurniawan, Ilham; Buani, Duwi Cahya Putri; Abdussomad, Abdussomad; Apriliah, Widya; Saputra, Rizal Amegia
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 2: April 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20236225

Abstract

Kemiskinan adalah salah satu perhatian mendasar dari setiap pemerintah. Program Beras Keluarga Miskin (Raskin) merupakan  salah satu program pemerintah. Skema raskin mempunyai tujuan meminimalisir beban rumah tangga tidak mampu sebagai bentuk bantuan untuk menaikkan ketahanan pangan melalui perlindungan sosial. Tujuan penelitian ini adalah menemukan akurasi tertinggi di antara algoritma klasifikasi prediktif yang diusulkan penerima bantuan raskin menggunakan tools python machine learning dan di implementasikan melalui suatu website. Klasifikasi adalah metode penambangan data yang menentukan kategori pada kelompok data untuk mendukung prediksi dan analisa yang semakin akurat. Beberapa algoritma klasifikasi pembelajaran mesin seperti, SVM, NB dan RF, digunakan pada penelitian ini demi menentukan penerima bantuan raskin. Eksperimen dilakukan menggunakan dataset Raskin Kelurahan Gunungparang, Kota Sukabumi yang bersumber dari Kelurahan Gunungparang. Kinerja algoritma klasifikasi dievaluasi dengan beragam metrik seperti Precision, Accuracy, F-Measure, dan Recall. Akurasi diukur melalui contoh yang dikelompokan dengan benar atau salah. Hasil yang diperoleh menunjukkan algoritma klasifikasi RF memiliki nilai precision, recall, f-measure dengan nilai 97%, nilai accuracy sebesar  97,26% dan nilai ROC 0,970, lebih baik dari algoritma klasifikasi lainnya yaitu perbedaan sebesar 5,11% dengan algoritma klasifikasi support vector machine dan 8,87% dengan algoritma klasifikasi naive bayes. Akurasi sangat baik digunakan sebagai acuan kinerja algoritma apabila jumlah False Negative dan False Positive jumlah nya mendekati. Hasil penelitian ini dibuktikan secara akurat dan sistematis menggunakan Receiver Operating Characteristic (ROC). Abstract The problem of poverty is one of the fundamental concerns of every government. The Raskin  program is one of the government's programs. The Raskin scheme has the aim of minimizing the burden on poor households in the form of assistance to improve food security by providing social protection. The purpose of this study is to find the highest accuracy among the predictive classification algorithms proposed by Raskin beneficiaries using python machine learning tools and implemented through a website. Classification is a data mining method that determines categories in data groups to support more accurate predictions and analysis. Therefore, three machine learning classification algorithms such as, support vector machine, naive bayes and random forest, were used in this experiment. to determine recipients of Raskin assistance. The experiment was carried out using the Raskin dataset, Gunungparang Village, Sukabumi City, which was sourced from Gunungparang Village. The performance of the classification algorithm is evaluated by various metrics such as Precision, Accuracy, F-Measure, and Recall. Accuracy is measured by correctly and incorrectly grouped samples. The results obtained show that the random forest classification algorithm has precision, recall, f-measure values with a value of 97%, an accuracy value of 97.26% and an ROC value of 0.970, better than other classification algorithms, namely the difference of 5.11% with the support vector classification algorithm. machine and 8.87% with naive bayes classification algorithm. Very good accuracy is used as a reference for algorithm performance if the number of False Negatives and False Positives is close. These results were proven accurately and systematically using Receiver Operating Characteristics (ROC).
Pemanfaatan Aplikasi Pengelolaan Dana Keuangan Penjualan Gas Berbasis Framework Code Igniter Pada PT Selamat Lestari Mandiri Divisi Gas Industri Amegia Saputra, Rizal; Gunawan, A; Yulianti, Ita; Septiani Nurfauzia K, Tya; Saputra, Rizal Amegia
Abditeknika Jurnal Pengabdian Masyarakat Vol. 1 No. 2 (2021): Oktober 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v1i2.625

Abstract

Selamat Lestari Mandiri Divisi Gas Industri merupakan salah satu perusahaan yang bergerak dalam bidang penjualan gas industri. Perusahaan tersebut berlokasi di Jl. Pramuka No.17 A Kelurahan Cikondang Kecamatan Citamiang Kota Sukabumi. Permasalahan yang dihadapi perusahaan ini salah satunya yaitu pencatatan pengelolaan dana keuangan penjualan gas yang masih dilakukan secara tulis tangan sehingga tidak heran apabila terjadi kesalahan pencatatan dan sulitnya pengecekan serta pencarian data keuangan dari history transaksi sebelumnya akibat penyimpanan dokumen tidak tertata rapi. Oleh karena itu, sebuah rancang bangun sistem baru dibutuhkan agar dapat membantu mengatasi permasalahan yang saat ini terjadi sehingga dapat memberikan kemudahan khususnya dalam melakukan pengelolaan dana keuangan penjualan gas pada perusahaan tersebut. Kegiatan pengabdian masyarakat ini dilakukan dengan menganalisis kebutuhan sistem terlebih dahulu kemudian dilanjutkan dengan tahap desain, implementasi dan pengujian secara terbatas sehingga dapat diketahui kelemahan dan kelebihan dari sistem yang akan dibangun dan diperlukan pelatihan kepada admin agar dapat menggunakan aplikasi ini dengan baik.
Pelatihan Aplikasi SIMOKO Dalam Menunjang Pelayanan, Akuntabilitas Dan Transparansi Pada KSP PKK Sejahtera Sukabumi Rahayu, Yuri; Riyanto, Andi; Saputra, Rizal Amegia; Aisyah, Aisyah; Damayanti, Vanysia; Ramdhani, Lis Saumi
Indonesian Community Service Journal of Computer Science Vol. 1 No. 1 (2024): Periode Januari 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/indocoms.v1i1.3024

Abstract

Pelatihan SIMOKO (Sistem Informasi Mobile Koperasi) merupakan langkah awal agar koperasi bisa naik kelas dan melek teknologi. Permasalahan yang dihadapi oleh mitra saat ini yaitu 1) Sistem pengolahan data masih dicatat manual oleh bendahara dibantu sekretaris dan selanjutnya dilaporkan kepada ketua terutama dalam pengajuan pinjaman, cek sisa pinjaman dan total simpanan. 2) Publikasi, belum memilikinya media publikasi sehingga penambahan anggota tiap tahun lambat, proses berjalan dalam mengembangkan dan penambahan anggota hanya mengandalkan strategi mulut ke mulut. 3) Pelaporan keuangan masih kurang optimal dan tidak tepat waktu, dan 4) Literasi mengenai pengelolaan manajerial dengan sistem informasi berbasis teknologi masih minim, sehingga akuntabilitas dan transparansi sebagai wujud pertanggungjawaban pengurus masih belum maksimal untuk diimplementasikan. Salah satu solusi berbasis teknologi informasi yang dapat diterapkan yaitu aplikasi SIMOKO (Sistem Informasi Mobile Koperasi) pada mitra, aplikasi SIMOKO dapat mengakomodir permasalahan-permasalahan yang dihadapi oleh KSP PKK Sejahtera Sukabumi, pada aplikasi ini terdapat berbagai macam fitur baik untuk anggota maupun pengurus : fitur biodata anggota, pengajuan pinjaman, cek sisa pinjaman, cek total simpanan, pembuatan pelaporan keuangan. Untuk mendukung hal itu maka mitra akan mendapatkan pendampingan untuk penggunaan Aplikasi SIMOKO agar pengetahuan dan kemampuan mitra dalam IT dan penggunaan aplikasi SIMOKO semakin meningkat, dengan begitu harapan pengelola untuk menjadi koperasi yang memiliki layanan yang baik, akuntabilitas dan transparansi keuangan akan mudah tercapai.
Co-Authors A Gunawan A.Gunawan Abdussomad, Abdussomad Adi Supriyatna Aira Elzahra Aisyah Aisyah Amegia Saputra, Rizal Ami Rahmawati Ami Rahmawati Andi Riyanto Damayanti, Vanysia Dasya Arif Firmansaha Dede Firmansyah Saefudin Dede Saefudin Desi Susilawati - AMIK BSI Sukabumi Desi Susilawati, Desi Dewi Ayu Nur Wulandari Dewi Ayu Nurwulandari Diah Puspitasari Dudus Kurnia Duwi Cahya Putri Buani Eka Fitriani Erika Mutiara Erika Mutiara, Erika Fatmawati Fatmawati Ferdian Agustiana Gumgum Darmawan Ilham Kurniawan Ilham Kurniawan Ita Yulianti Ita Yulianti Jamal Maulana Hudin Julia Rahmah Lis Saumi Ramdhani Medi Firmansyah Muhammad Faittullah Akbar Muhammad Sukrisno Mardiyanto Nandya Ayu Fatmandini Neng Senja Nekida Nita Novianti Novitasari, Dian C Rini Nurul Gusriani Pribadi, Denny Rahmawati, Rahmawati Ramdhan Saepul Rohman, Ramdhan Saepul Resti Yulistria Rimuljo Hendradi Rinda Nariswari Rizki Ramadhan Rosita Rosita Ruslan Ruslan Rusli Nugraha Saeful Bahri Septiani Nurfauzia K, Tya Shinta Ayuningtias Siti Masripah Sri Wasiyanti, Sri Supriatman, Supriatman Taufik Baidawi, Taufik Taufik Hidayatulloh Toto Haryanto Tya Septiani Nurfauzia K Wasyianti, Sri Widya Apriliah, Widya Yuri Rahayu