Article Per Year (5 Year)
p-Index From 2020 - 2025
1.745
P-Index
This Author published in this journals
All Journal Katalogis Journal of Fisheries Resources Utilization Management and Technology Jurnal Teknologi Informasi dan Ilmu Komputer Collaborative Medical Journal (CMJ) PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Journal of Islamic Economics Lariba Jurnal Ventilator: Jurnal Riset Ilmu Kesehatan dan Keperawatan Compromise Journal : Community Proffesional International Journal Of Public Health
Risnandar, Risnandar
Unknown Affiliation
Religion Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
ANALISIS E-GOVERNMENT DALAM PENINGKATAN PELAYANAN PUBLIK PADA DINAS KOMUNIKASI DAN INFORMATIKA PROVINSI SULAWESI TENGAH Risnandar, Risnandar
Katalogis Vol 2, No 7 (2014)
Publisher : Katalogis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (232.186 KB)

Abstract

Theobjective of this research was to find out the implementation of e-Goverment in increasingpublic service at comunication and information official of central Sulawesi province. The Main theory employed was e-goverment theory covers (1) content development , (2) competency building, (3) Connectivity, (4) Cyber Laws, (5) citizen Interfaces, and (6) Capital. It was also supported by President Instruction No. 3 year 2003. The research method employed was qualitative research setting. The research setting  was at communication and information official of central Sulawesi province with 5 informants who chosen purposively as the sample. The tehnique of data collection were interview, observation and documentation. The technique of data analysis was descriptive model by Robson With case study approach. The research results showed that the implementation of e-government in Increasing Public Service at Comunication and Information Official of Central Sulawesi  Province  have  run  well  enough  such  as  Capital  and  Content  Development  and Connectivity even tough still need improvement. Competency Building and Citizen interfaces were less cinsidered where as Cyber Laws was not judged because it was nationally so it needed to be improved by Central Government. Primarily, there was two issues encountered in conducting the main  duty  and  function  of  e-Government  section.  The  first  was  infrastructure  availability, supporting facility such as server, computer, and website from Communication and Information Official were lack. The second was human resources availability particulary those had IT background and technical officers to solve administration and digital information issues. To solve the  issues,  e-Government  had  already  done  some  efforts  at  Communication  and  Information Official of Central of Sulawesi Province. The first efforts was providing and requesting infrastructure availability,  supporting  facility of e-Government.  The second  was  asking  to  the secretariat which would be forwarded by Regional Officery Board to provide technical and IT officers to proceed electronic information and administration.
Kombinasi K-NN dan Gradient Boosted Trees untuk Klasifikasi Penerima Program Bantuan Sosial Elly Firasari; Umi Khultsum; Monikka Nur Winnarto; Risnandar Risnandar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0813087

Abstract

Kemiskinan bagi pemerintah Indonesia termasuk masalah yang sulit untuk diselesaikan. Upaya yang dilakukan pemerintah dalam mengatasi kemiskinan di Indonesia yaitudengan  program bantuan sosial meliputiBLT (Bantuan Langsung Tunai), PKH (Program Keluarga Harapan), Raskin (Beras Miskin), dan lain lain. Dalam Pelaksanaan program bantuan sosial saat masih sangat terbatas sehingga dalam penerimaan program bantuan tidak tepat sasaran. Data mining membantu untuk menentukan keputusan dalam memprediksi data di masa yang akan datang. Gradient Boosted Trees dan K-NN merupakan salah satu metode data mining untuk klasifikasi data. Masing-masing metode tersebut memiliki kelemahan. Gradient Boosted Trees menghasilkan nilai persentase akurasi lebih rendah dibanding metode K-NN. Dari permasalahan tersebut maka diusulkan metode kombinasi K-NN dan Gradient Boosted Trees untuk meningkatkan akurasi pada pelaksanaan program bantuan sosial agar tepat sasaran. Metode K-NN, Gradient Boosted Trees, K-NN-Gradient Boosted Treesdilakukan pengujian pada data yang sama untuk mendapatkan hasil perbandingan nilai akurasi. Hasil pengujian membuktikan bahwa kombinasi tersebut menghasilkan nilai persentase yang tinggi dibanding metode K-NN atau Gradient Boosted Trees yaitu 98.17%.AbstractPoverty for the Indonesian government is a problem that is difficult to solve. The efforts made by the government in overcoming poverty in Indonesia are through social assistance programs including BLT (Bantuan Langsung Tunai), PKH (Program Keluarga Harapan), Raskin (Beras Miskin), and others. In the implementation of the social assistance program when it was still very limited, the acceptance of the aid program was not on target. Data mining helps to determine decisions in predicting data in the future. Gradient Boosted Trees and K-NN are data mining methods for data classification. Each of these methods has weaknesses. Gradient Boosted Trees produce lower accuracy percentage values than the K-NN method. From these problems, a proposed method of combination of K-NN and Gradient Boosted Trees is used to improve the accuracy of the implementation of social assistance programs so that it is right on target. The K-NN, Gradient Boosted Trees, and K-NN-Gradient Boosted Trees methods are tested on the same data to get a comparison of the accuracy values. The test results prove that the combination produced a high percentage value compared to the K-NN or Gradient Boosted Trees method that is 98.17%.
Analisis Kinerja Algoritma CART dan Naive Bayes Berbasis Particle Swarm Optimization (PSO) untuk Klasifikasi Kelayakan Kredit Koperasi Eko Arif Riyanto; Tri Juninisvianty; Doddy Ferdian Nasution; Risnandar Risnandar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 1: Februari 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0812988

Abstract

Koperasi memiliki peranan penting terutama untuk masyarakat kecil dan menengah. Salah satu kendala yang dirasakan oleh koperasi adalah analisa pemberian kredit yang dilakukan secara manual dan hanya berdasarkan kedekatan secara personal dengan anggota sehingga menyebabkan terjadinya kredit – kredit  macet yang tidak diduga. Oleh karena itu perlu adanya perhitungan yang sistematis dalam pemberian kredit kepada para peminjam. Teknik klasifikasi data mining merupakan salah satu teknik yang bisa digunakan dalam menentukan kelayakan kredit. Tujuan dari penelitian ini adalah untuk menentukan metode terbaik untuk klasifikasi kelayakan kredit koperasi menggunakan software Rapidminer dengan membandingkan perhitungan algoritma CART, Naive Bayes, optimasi CART + PSO, dan Naive Bayes + PSO. Data yg digunakan adalah 113 data anggota koperasi. Dari perhitungan dengan acuan kriteria pekerjaan, pendapatan, usia, jenis kelamin, jumlah pinjaman, jangka waktu, akan memperoleh metode terbaik untuk klasifikasi kelayakan kredit. Metode terbaik yang dihasilkan dari penelitian ini adalah metode Naive Bayes + PSO. Nilai accuracy yang diperoleh dari penelitian ini adalah 96,43%, nilai recall 94,12%, niilai precision 100%. Dengan nilai AUC sebesar 0,963 , penelitian ini termasuk dalam klasifikasi baik. Hasil dari penelitian ini dapat digunakan sebagai salah satu pertimbangan untuk klasifikasi kelayakan kredit pada koperasi simpan pinjam. AbstractCredit Union have an important role especially to the small and medium society. One of the problem  that credit union have is an analyzing credit manually and only based on closeness personally that can be an unexpected bad credit for credit union. Therefore, it is necessary to build a systematic calculation to give a credit for debtor. Classification technic in data mining is one of the technic that can use to classify the credit properness. The purpose of this study is to get the best method to classify the credit properness using Rapidminer by compare the calculation of CART, Naive Bayes and the optimization of CART+PSO and Naive Bayes+PSO. The study using 113 data member of credit union. From the calculation reference to the criteria of occupation, income, age, gender, loan amount, loan term, will get the best method for this study. The best method from this study is the Naive Bayes+PSO. The accuracy value obtained from this study was 96.43%, the recall value was 94.12%, and the precision value is 100%. AUC value of 0.963 indicates that this study is included in the good classification. The results of this study can be used as a consideration for the classification of the credit properness of credit union.
Analisis Loyalitas Pelanggan Berbasis Model Recency, Frequency, dan Monetary (RFM) dan Decision Tree pada PT. Solo Basri Basri; Windu Gata; Risnandar Risnandar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 5: Oktober 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020752284

Abstract

Perkembangan bisnis alat tulis kantor dan sekolah saat ini banyak yang menjanjikan, maka banyak bermunculan pemasok baru dalam bisnis Alat Tulis Kantor dan Sekolah (ATKS). PT Solo yang bergerak di bidang bisnis ATKS harus memiliki strategi dalam setiap persaingan usaha, khususnya dalam meraih loyalitas pelanggan. Loyalitas pelanggan sering dipengaruhi oleh faktor jumlah aktivitas transaksi, nilai nominal transaksi, waktu transaksi di perusahaan, dan atribut outlet. Penelitian ini mengusulkan model Recency, Frequency, dan Monetary (RFM) yang dikombinasikan dengan Decision Tree. Model RFM digunakan untuk proses klasterisasi data pelanggan berdasarkan jumlah transaksi, nilai nominal transaksi, waktu transaksi, dan atribut outlet. Sedangkan Decision Tree dapat menggambarkan tingkat loyalitas pelanggan. Data transaksi dalam penelitian ini dilakukan sepanjang 1 Januari hingga 31 Desember 2018 terhadap 1.203 pelanggan dan 18.087 transaki melalui faktur pembelian. Hasil penelitian ini menunjukan bahwa state-of-the-art pada model RFM dan Decision Tree yang diusulkan lebih unggul dibandingkan hanya dengan menggunakan model RFM saja. Cluster ke-1 memiliki 860 pelanggan menghasilkan loyalitas pelanggan sedang (biru), cluster ke-2 memiliki 69 pelanggan menghasilkan loyalitas pelanggan yang tinggi (hijau), dan cluster ke-3 memiliki 274 pelanggan menghasilkan loyalitas pelanggan yang rendah (merah). Model klasterisasi RFM dan klasifikasi Decision Tree telah menghasilkan atribut outlet yang berpengaruh terhadap nilai akurasi sebesar 67,54%. Abstract The development of office and school stationery business at this time, many promising, so many new suppliers have sprung up in the office and school stationery business. PT Solo, which has the office and school stationery business, must have a strategy in every business competition, especially in achieving customer loyalty. Customer loyalty is often influenced by factors in the number of transaction activities, transaction nominal value, transaction time at the company, and outlet attributes. This research proposes a Recency, Frequency, and Monetary (RFM) model combined with a Decision Tree. RFM model is used to process customer data clustering based on number of transactions, transaction nominal value, transaction time, and outlet attributes. Whereas Decision Tree can describe the level of customer loyalty. Transaction data in this study were conducted from 1 January to 31 December 2018 to the 1,203 customers and 18,087 transactions through purchase invoices. The results of this study indicate that the state-of-the-art in the proposed RFM and Decision Tree models is outperform compared to only using the RFM model. Cluster 1 has 860 customers resulting in moderate customer loyalty (blue), Cluster 2 has 69 customers resulting in high customer loyalty (green), and Cluster 3 has 274 customers resulting in lower customer loyalty (red). RFM clustering model and Decision Tree classification have produced outlet attributes that affect the accuracy value of 67.54%.
Environmental Management in Fishery Harbour (Case Study of “Pelabuhan Perikanan Nusantara Palabuhanratu”, Sukabumi Regency, West Java Province Risnandar, Risnandar
Journal of Fisheries Resources Utilization Management and Technology Vol 2, No 3: Agustus, 2013
Publisher : Fakultas Perikanan dan Ilmu Kelautan, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Environmental management in fishery harbour was studied in PPN Palabuhanratu. The study was mainly based on the survey methodological. The data collected based on primary and secondary data. Field observation was conducted to determine physico-chemical characteristics and biological characteristics of the benthos and plankton, depth interview with the fishermans and stakeholders of PPN Palaburanratu and identify of existing environmental management facility in PPN Palaburanratu. In generally the available facilities and environmental management in PPN Palabuhanratu focused on environment cleaning from solid waste. The Pollution Index and STORET analysis of surface water quality from 7 sampling point in the PPN Palabuhanratu area categorize as polluted indicated by quite high ammonia at St. 5, St 6 and St.7. The plankton analysis community saprobic index was in the phase of β-mesosaprobic to polysaprobic indicating low to heavy level pollutions with few organic and anorganic contaminant substance. PPN Palabuhanratu has already conducted standar environmental management. However the efforts standard regulations or procedures still not comply with that stated by Misnistry of Environment. 
HUBUNGAN LAMA MENDERITA DIABETES MELITUS TIPE 2 DAN DISFUNGSI EREKSI Firmansyah, Rio; Nugraha, Dimas Pramita; Susanti, Lasiah; Risnandar, Risnandar
Collaborative Medical Journal Vol 6 No 3 (2023): September 2023
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/cmj.v6i3.4019

Abstract

Diabetes melitus (DM) tipe 2 merupakan salah satu penyakit sistemik yang menyebabkan tingginya angka kesakitan dan mortalitas di Indonesia. Kali ini Disfungsi Ereksi (DE), salah satu komplikasi DM tipe 2 menjadi masalah serius karena pertama kejadian disfungsi ereksi tinggi dengan 50% -80% orang dengan DM tipe 2 mengalami DE. Kedua, masalah ini berdampak pada kehidupan pasien medis (psikologi dan infertilitas) serta nonmedis (bahan lama bercerai dan keluarga). DM tipe 2 adalah neuropati diabetik, angiopati diabetik, psikisis dan faktor hormonad. Semuanya berhubungan dengan durasi DM tipe 2 yang dialami penderita. Penelitian ini bertujuan untuk mengetahui korelasi durasi DM tipe 2 dengan DE pada RSUP Arifin Achmad pekanbaru. Penelitian ini menggunakan metode cross sectional yaitu populasi pasien rawat inap di RS Arifin Achmad. Penelitian dilaksanakan dengan teknik nonprobability sampling, consecutive sampling, dan terdapat 42 responden. Berdasarkan hasil uji koefisien kontingensi, terdapat korelasi antara durasi DM tipe 2 dengan DE (p=0,012, r=0,453). Terdapat korelasi antara durasi DM tipe 2 dengan DE, dengan kekuatan korelasi dan arah korelasi positif antara durasi DM tipe 2 dengan DE.
DETEKSI OBJEK BAYANGAN KENDARAAN MENGGUNAKAN FASTER R-CNN Nabila, Deeva; Iswanto, Bambang Heru; Risnandar, Risnandar
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA04

Abstract

Abstrak Objek bayangan memiliki intensitas dan bentuk yang beragam, yang dapat menimbulkan masalah dalam sistem visi kendaraan otonom. Bayangan yang ditimbulkan dari pohon, bangunan, dan objek lain di sekitar jalan dapat mempengaruhi kinerja sistem pengenalan dan pelacakan target. Maka itu, diperlukan suatu model pendeteksian bayangan untuk mengetahui lokasi bayangan agar dapat digunakan pada penelitian terkat eliminasi bayangan. Penelitian ini bertujuan untuk mengetahui tingkat akurasi model dengan variasi dataset yang kami berikan dan mendefinisikan masing-masing label objek non-shadow dan shadow merupakan metode yang digunakan untuk membedakan antara bayangan dan objeknya yang mirip. Pelatihan model dilakukan dengan fine-tuning Faster R-CNN pada kerangka kerja Pytorch menggunakan arsitektur ResNet50 sebagai rancangan dasar. Implementasi model untuk dapat mendeteksi bayangan diterapkan pada video perjalanan kendaraan otonom. Hasil penelitian menunjukkan bahwa dari kelima model yang dibuat, model P5 berhasil mendeteksi bayangan dengan rata-rata akurasi F1-score sebesar 46%. Kata-kata kunci: Bayangan, Deteksi, Faster R-CNN, R-CNN, ResNet50, Pytorch Abstract Shadow objects exhibit varying intensities and shapes, which can pose problems in autonomous vehicle vision systems. Shadows generated by trees, buildings, and other objects in the vicinity of the road can impact the performance of the recognition and tracking system. Thus, a shadow detection model is necessary to determine the location of shadows, which can be employed in studies related to shadow removal. This study aims to determine the accuracy level of the model with our given diverse dataset and defining distinct labels for non-shadow and shadow objects to differentiate between shadows and similar-looking objects. The model training was performed by fine-tuning Faster R-CNN on the PyTorch framework, utilizing ResNet50 as the backbone architecture. The implemented model aimed to detect shadows in videos of autonomous vehicle. The results indicated that out of the five models developed, P5 model successfully detected shadows with an average accuracy based on F1-score is 0.46%. Keywords: Shadow, Detection, Faster R-CNN, Faster R-CNN, R-CNN, ResNet50, Pytorch
Pendidikan Kesehatan Persiapan Menghadapi Menopause Pada Ibu-Ibu Usia Premenopause Di Sungai Pagar, Kabupaten Kampar Neni Ristiani; Mofri Lindo; Risnandar Risnandar; Huda Marlinawati; Neni Triana
Compromise Journal : Community Proffesional Service Journal Vol. 2 No. 2 (2024): Compromise Journal : Community Proffesional Service Journal
Publisher : LPPM STIKES KESETIAKAWANAN SOSIAL INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57213/compromisejournal.v2i2.254

Abstract

Menopause is a physiological process that every woman will go through. During menopause, many changes occur in a woman's body, both physical and psychological. The changes that occur during menopause tend to cause discomfort, therefore menopause is a process that is quite a burden for a woman. Fear of facing menopause should be minimized if someone has sufficient knowledge about the menopause process and the complaints that can arise during menopause as well as the efforts that can be made to overcome these complaints.
Case Report : Hepatic Cirrhosis and Nephrolithiasis Risnandar Risnandar; Yoga Rizki Danil; Yuharika Pratiwi
International Journal of Public Health Vol. 1 No. 3 (2024): September : International Journal of Public Health
Publisher : Asosiasi Riset Ilmu Kesehatan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijph.v1i3.65

Abstract

Liver cirrhosis and nephrolithiasis are significant health problems with different pathophysiological mechanisms. Liver cirrhosis, the final stage of chronic liver disease, is characterized by fibrosis and regenerative nodules, leading to severe complications, including portal hypertension and liver failure. Nephrolithiasis, commonly known as kidney stones, is a common urological condition characterized by the formation of stones in the renal system. Although these conditions are distinct, metabolic and physiological changes in cirrhotic patients may predispose to nephrolithiasis. It was reported that a man came to the emergency room of RSUD Dr. Suhatman MARS with complaints of left-sided low back pain that had been felt for 1 week. The complaint was accompanied by shortness of breath which was getting worse over time. The patient also felt cough, headache, nausea, fatigue, urine slightly coloured like tea, weight loss. The patient has a history of untreated kidney stones. The patient has a history of hepatitis 31 years ago. The main objective of investigating the coexistence of liver cirrhosis and nephrolithiasis is to understand the relationship between these two conditions and to develop effective management strategies that can address their combined impact on patients.
Case Report : CKD Stg V + Suspect Encapsulated Peritoneal Sclerosis Risnandar Risnandar
Jurnal Ventilator Vol. 3 No. 1 (2025): Jurnal Ventilator
Publisher : Stikes Kesdam IV/Diponegoro Semarang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59680/ventilator.v3i1.1732

Abstract

This case report discusses a 54-year-old female patient diagnosed with Stage V Chronic Kidney Disease (CKD) undergoing Continuous Ambulatory Peritoneal Dialysis (CAPD). The patient presented with clinical symptoms such as nausea, vomiting, abdominal pain, and reduced ultrafiltration volume, raising suspicion of Encapsulated Peritoneal Sclerosis (EPS). EPS is a rare but serious complication in long-term CAPD patients. Management includes discontinuation of CAPD, adequate nutritional support, and symptomatic therapy. This report aims to enhance understanding of the diagnosis and management of EPS in Stage V CKD patients.
Co-Authors Arianty, Erny Bambang Heru Iswanto Basri Basri Dimas Pramita Nugraha Doddy Ferdian Nasution Eko Arif Riyanto Firasari, Elly Huda Marlinawati Indrawati, Iin Marsono Marsono Mofri Lindo Monikka Nur Winnarto Nabila, Deeva Neni Ristiani Neni Triana Rio Firmansyah, Rio Susanti, Lasiah Tri Juninisvianty Umi Khultsum Windu Gata Yoga Rizki Danil Yuharika Pratiwi