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All Journal Jurnal Buana Informatika Jurnal Teknologi Informasi dan Ilmu Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Pilar Nusa Mandiri Informatics for Educators and Professional : Journal of Informatics Syntax Literate: Jurnal Ilmiah Indonesia JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Teknoinfo Jurnal Ilmu Komputer dan Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Journal of Applied Computer Science and Technology (JACOST) Jurnal Interkom : Jurnal Publikasi Ilmiah Bidang Teknologi Informasi dan Komunikasi Ilmu Komputer untuk Masyarakat Paradigma Journal of Innovation and Sustainable Empowerment Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK)

Jajang Jaya Purnama

Universitas Bina Sarana Informatika

Author-ID : 6567485

Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Sistem Pakar Diagnosa Penyakit Pada Kucing Menggunakan Metode Forward Chaining Ridwansyah; Jajang Jaya Purnama; Hermanto; Suhardjono; Abdul Hamid
Jurnal Ilmu Komputer dan Bisnis Vol. 11 No. 2a (2020): Special Issue Vol. 11 No. 2a (2020)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v11i2a.27

Kucing merupakan hewan yang popular dan sangat disukai di kalangan masyarakat baik dalam bentuk fisik yang lucu maupun tingkah laku yang menggemaskan merupakan salah satu alasan yang membuat banyak orang memelihara hewan peliharaan yang satu ini, dan memelihara kucing juga merupakan sunah rasul bagi umat muslim. Kepopuleran memelihara kucing membuat jumlah peminat kucing di Indonesia sangatlah besar, dan berbagai masalahpun akan terjadi ketika pemilik kucing mendapati kucing kesayangannya sakit. Banyak kucing terserang penyakit, kucing peliharaan ataupun kucing liar, penyakit kucing diantaranya: Helminthiasis, Skabies, Ektoparasit, Koksidiosis, Feline Viral Rhinotracheitis, Feline Caliviral disease, Felice Panleukopenia, Earmite. Sistem pakar adalah metode ilmu yang bertujuan untuk menyelesaikan permasalahan yang bisa dibilang cukup rumit, yang biasanya permasalahan itu hanya bisa diatasi oleh para ahli tertentu. Pemelihara kucing yang tidak mengetahui tentang penyakit yang diderita terhadap kucing akan menjadi permasalahan yang besar maka dengan itu dapat dibuatkan dan dibangun suatu sistem pakar. Dengan sistem yang dibuat dan dibangun tersebut dapat membantu dalam mendiagnosis penyakit yang diderita pada kucing dan memberi solusi cara pengobatan dan pencegahannya.

Rancang Bangun Aplikasi Penggajian Menggunakan Framework CI : Studi Kasus : PD. Perkasa 3 Rahayu, Sri; Ridwansyah, Ridwansyah; Purnama, Jajang Jaya; Hamid, Abdul; Herliawan, Irwan
Jurnal Ilmu Komputer dan Bisnis Vol. 12 No. 2a (2021): Vol. 12 No. 2a Special Issue (2021)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v12i2a.203

Kegiatan yang ada pada perusahaan dagang pada umumnya yaitu pembelian dan penjualan. Selain kedua kegiatan tersebut yang terkadang hampir dilupakan namun merupakan hal vital diantara adalah kegiatan penggajian karyawan. Masalah pemberian gaji merupakan hal yang penting karena mempunyai pengaruh yang sangat besar terhadap semangat kerja para karyawannya. PD. Perkasa 3 memiliki ratusan karyawan yang berbeda sistem perhitungan penggajiannya. Kerumitan pencatatan dan perhitungan penggajian dapat diatasi dengan rancang bangun sebuah aplikasi penggajian berbasis website yang dibangun menggunakan framework code igniter dengan bahasa pemrograman PHP dan database MySQL mampu memecahkan masalah mengenai rumitnya pencatatan dan perhitungan penggajian pada PD. Perkasa 3. Saat ini, PD. Perkasa 3 dapat melakukan penggajian dengan cepat dan tepat, pelaporan dan pengarsipan lebih rapi, aman, tidak mudah terbakar, basah dan hilang karena data tersimpan pada database rancang bangun ini dilakukan dengan berdasarkan metode SDLC (Systems Development Lifecycle) yang umum digunakan, yaitu Waterfall.

Analisis Algoritma Klasifikasi Neural Network Untuk Diagnosis Penyakit Diabetes Jajang Jaya Purnama; Sri Rahayu; Siti Nurdiani; Tuti Haryanti; Nissa Almira Mayangky
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 5, No 1 (2020): Mei 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Abstrak – Diabetes merupakan penyakit yang sangat mematikan terbukti dari tahun ke tahun selalu ada yang meninggal dikarnakan pasien tersebut mengidap penyakit diabetes, banyak cara penangguhan sejak dini penyakit diabetes. Salah satunya dengan data mining klasifikasi algoritma neural network yang dapat digunakan untuk prediksi pasien mana yang terkena penyakit diabetes dan pasien mana yang tidak terkena diabetes dengan menggunakan parameter dan indikator yang ada, dan tools yang digunakan adalah tools rapid miner 9.0 yang mengahasilkan accuracy sebesar = 80.00% precision sebesar = 100.00 % dan recall sebesar = 2.50 % dengan AUC sebesar = 0.605 % yang artinya klasifikasi dinyatakan cukup, dari hasil tersebut bisa dimbil kesimpulan bahwa penelitian ini bisa mencegah dan bisa diketahui sejak dini mana yang termasuk penyakit diabetes mana yang tidak mengidap penyakit diabetes, dan dari penelitian ini sangat diharapkan angka kematian bisa berkurang.</>Katakunci: diabetes, klasifikasi, data mining, neural network.Abstract – Diabetes is a very proven disease from year to year there are always people who die, many ways to postpone early diabetes. One of them is data mining neural network algorithm classification which can be used to predict which patients are affected by diabetes and which patients are not affected by diabetes by using existing parameters and indicators, and the tools used are rapid miner 9.0 tools that produce accuracy = 80.00% precision = 100.00% and recall of = 2.50% with AUC of = 0.605% which means the classification is declared sufficient, From these results it can be concluded that this study can prevent and can be known from the outset which of the diabetics do not have diabetes, and from this study it is expected that the mortality rate can be reduced. Keywords: classification, data mining, diabetes, neural network

Aplikasi Mobile Sistem Pakar Dalam Mengidentifiaksi Diagnosis Penyakit Kucing Ridwansyah Ridwansyah; Jajang Jaya Purnama; Hermanto Hermanto; Suhardjono Suhardjono; Abdul Hamid
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol 5 No 1 (2020): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Desember 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v5i1.1414

Abstrak: Adanya sebuah aplikasi saat ini dapat digunakan dalam beberapa hal khususnya sistem pakar. Sistem pakar penyakit kucing merupakan sistem yang dapat mengidentifikasi penyakit pada kucing, yang dikarenakan hewan tersebut sangat populer di masyarakat khususnya Indonesia sangatlah besar peminatnya. Hewan ini sangat disukai karena bentuknya yang lucu dan perilaku yang menggemaskan, terlebih nabi Muhammad juga menyukai hewan ini dan jika kita merawatnya makan sunah rasul yang kita dapat ini merupakan kepercayaan umat muslim. Dalam memelihara kucing berbagai masalah akan terjadi dimana kucing yang kita pelihara dalam keadaan sakit dan berbagai virus yang menyerang kucing misalnya penyakit kucing scabies, penyakit kucing feline caliviral disease, penyakit kucing helminthiasis, penyakit kucing koksidiosis, penyakit kucing felice panleukopenia, penyakit kucing ektoparasit, penyakit kucing, penyakit kucing feline viral rhinotracheitis dan penyakit kucing Earmite. Dengan adanya aplikasi sistem pakar yang bertujuan untuk menyelesaikan suatu permasalahan yang dapat di anggap cukup rumit dan hanya bisa diatasi para ahli atau para pakar tertentu. Pemilik kucing yang tidak mengetahui adanya penyakit yang dialami oleh kucing yang dipeliharanya maka akan menjadi permasalahan yang besar. Oleh karena itu dengan adanya aplikasi sistem pakar tersebut dapat membantu dalam melakukan diagnosis penyakit pada kucing dan memberikan alternatif pengobatan, penanganan dan pencegahannya. Kata kunci: Aplikasi Sistem Pakar, Forward Chaining, Penyakit Kucing. Abstract: The existence of an application today can be used in several ways, especially expert systems. The cat disease expert system is a system that can identify diseases in cats, which is because these animals are very popular in society, especially in Indonesia, and are in great demand. This animal is very popular because of its cute shape and adorable behavior, especially the prophet Muhammad also likes this animal and if we take care of it, eat the Prophet's Sunnah which we get is the belief of Muslims. In keeping cats, various problems will occur where the cat we keep is sick and various viruses that attack cats, for example, scabies cat disease, feline caliviral disease, cat helminthiasis, cat coccidiosis, felice panleukopenia cat disease, ectoparasite cat disease, cat disease feline cat disease, viral rhinotracheitis and Earmite cat disease. With the existence of an expert system application that aims to solve a problem that can be considered quite complicated and can only be overcome by certain experts or experts. Cat owners who do not know about the disease experienced by the cat they keep will be a big problem. Therefore, with the application of this expert system, it can help diagnose diseases in cats and provide alternative treatments, treatments and prevention. Keywords: Cats, Expert Systems, Forward Chaining

KLASIFIKASI PENENTUAN PENERIMA MANFAAT PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA C5.0 (Studi kasus: Desa Sukamaju, Kec.Kadudampit) Dede Wintana; Hikmatulloh Hikmatulloh; Nurul Ichsan; Jajang Jaya Purnama; Ami Rahmawati
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 6, No 3 (2019)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v6i3.206

Poverty is the main focus of the central government and local governments. Because it is one of the causes of backwardness and an obstacle in the development of a nation. With the existence of a family program, it is expected that it can improve the socio-economic conditions of the Very Poor Family, increase the level of Very Poor Family education and improve the health and nutrition status of pregnant women and toddlers in Indonesia. Very Poor Family. The Family Hope Program is expected to reduce poverty and improve human resources, especially in the group of very poor people. The main problem in channeling the Hope Family Program was that the eligibility determination system was still manual and used data several years ago. This is feared to cause confusion and inaccuracy of beneficiaries of the Family Hope Program, so a decision support system is needed to determine the qualifications of recipients of the Hope Family Program. The results of the study using C5.0 Algorithm from this study, can know that the main root in determining recipients of family planning programs is the ownership of school children with acquisition of 0.512716784 Keywords: C5.0, Decision tree, Poverty, Classification, Hope family program.Kemiskinan adalah fokus utama pemerintah pusat dan pemerintah daerah. Karena itu merupakan salah satu faktor penyebab keterbukaan dan penghambatan dalam pembangunan suatu bangsa. Dengan adanya program keluarga, diharapkan meningkatkan status sosial ekonomi Keluarga Sangat Miskin, meningkatkan tingkat pendidikan Keluarga Sangat Miskin dan meningkatkan status kesehatan dan gizi ibu hamil dan balita di Indonesia. Keluarga yang Sangat Miskin. Program Keluarga Harapan dapat mengurangi kemiskinan dan meningkatkan sumber daya manusia, terutama pada kelompok orang yang sangat miskin. Masalah utama dalam menyalurkan Program Program Keluarga Harapan adalah sistem pemilihan menentukan apakah masih manual dan menggunakan data beberapa tahun yang lalu.Hal ini menimbulkan keraguan dan ketidaktepatan penerima Program Keluarga Harapan, sehingga diperlukan sistem pendukung keputusan untuk menentukan kualifikasi penerima Program Keluarga Harapan. Hasil penelitian dengan menggunakan Algoritma C5.0 dari penelitian ini, dapat membantu penelitian tentang akar dalam menentukan penerima program Keluarga harapan adalah kepemilikan anak sekolah dengan persetujuan 0,512716784Kata Kunci: C5.0, Decision tree, Kemiskinan, Klasifikasi, Program keluarga Harapan.

ANALISA ALGORITMA K-MEANS CLUSTERING PEMETAAN JUMLAH TINDAK PIDANA Jajang jaya Purnama
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 6, No 2 (2019)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v6i2.208

Marine fisheries is an effort to catch marine fish, fishermen catch fish in the sea using two kinds of ways, namely through traditional and modern methods. to support the daily lives of fishermen looking for sea fish. the abundance of marine fish in the Indonesian sea means that the processed food is also very diverse. The high level of crime in the Indonesian sea is a mirror of the quality of the Indonesian navy's military defense, considering that the Indonesian sea is very rich in marine resources which makes fish thieves from neighboring countries tempted to catch fish in the Indonesian sea. in general it can be called a crime if unlicensed fishermen, illegal fishing gear, without permission and illegal fishing gear, falsification of documents, incomplete documents, shocking (ACCU), carrying explosives / bombs, fishing ground, fishing ground and illegal logging equipment , fish transportation / transhipment, without information on criminal types of fisheries, transhipment and fishing gear, no transmitter, theft of coral reefs, unsuitable fishing gear (SIPI), incomplete documents and fishing ground, foreign crew members not suitable for SIPI, not fishing in accordance with SIKPI, documents are incomplete and there are no transmitters, SIB is not valid, SLO (SIB is not in accordance with SIPI), without permits and fake documents, sea sand without documents, do not have SLO, loading and unloading is not SIPI, uses chemical / biological / explosives, fishing in the Gray Area / illegal fishing equipment / returned to the country of origin related to the MoU. Based on the background described there are problems that occur, the formulation of the problem in this study are: Analyzing k-means clustering by using proximity euclidean distance distance, How to group data using K-means clustering for illegal fishing crime into the category of illegal crime fishing the highest, medium, and sufficient cases in 266 data with the euclidean distance calculation.Keywords : criminal act, clustering, k-means Perikanan laut merupakan usaha menangkap ikan laut, para nelayan menangkap ikan di laut menggunakan dua macam cara yaitu melalui cara traditional dan modern. untuk menunjang kehidupan sehari-hari nelayan mencari ikan kelaut. melimpahnya ikan laut di laut Indonesia berarti menjadikan olahan masakannya juga sangat beragam. Tingginya tingkat kejahatan di laut Indonesia merupakan cermin kualitas pertahanan militer angkatan laut Indonesia, mengingat laut Indonesia sangat kaya akan baharinya yang membuat para pencuri ikan dari negara-negara tetangga menjadi tergiur untuk menangkap ikan di laut Indonesia. secara umum bisa disebut tindak kejahatan bila mana nelayan tanpa ijin, alat tangkap terlarang, tanpa ijin dan alat tangkap terlarang, pemalsuan dokumen, dokumen tidak lengkap, penyetruman (ACCU), membawa bahan peledak/bom, fishing ground, fishing ground dan alat tagkap terlarang, pengangkutan ikan/transhipment, tanpa keterangan jenis pidana perikanan, transhipment dan alat tangkap, tidak ada transmitter, pencurian terumbu karang, alat tangkap tidak sesuai ijin (SIPI), dokumen tidak lengkap dan fishing ground, ABK asing tidak sesuai SIPI, menampung ikan tidak sesuai SIKPI, Dokumen tidak lengkap dan tidak ada transmitter, SIB tidak berlaku, SLO (SIB tidak sesuai dengan SIPI), tanpa ijin dan dokumen palsu, pasir laut tanpa dokumen, tidak memiliki SLO, bongkar muat tidak sesuai SIPI, menggunakan bahan kimia/biologis/peledak, penangkapan ikan di daerah Grey Area/alat tangkap terlarang/dikembalikan ke negara asal terkait MoU. Berdasarkan latar belakang yang telah diuraikan terdapat permasalahan yang terjadi, rumusan permasalahan dalam penelitian ini adalah : Menganalisa k-means clustering dengan menggunakan kedekatan jarak euclidean distance, Bagaimana melakukan pengelompokan data menggunakan K-means clustering bagi tindak pidana ilegal fishing kedalam kategori tindak pidana ilegal fishing paling tinggi, menengah, dan cukup.studi kasus pada 266 data dengan perhitungan euclidean distance.Kata Kunci : tindak pidana, clustering, k-means

CLASSIFICATION OF LIVER DISEASE BY APPLYING RANDOM FOREST ALGORITHM AND BACKWARD ELIMINATION Irwan Herliawan; Muhammad Iqbal; Windu Gata; Achmad Rifai; Jajang Jaya Purnama
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Cancer is a type of disease that is not realized by most people because most people associated with this disease lack understanding of cancer itself and are doing early detection of cancer, due to the majority of cancers found at an advanced stage and difficult to overcome to facilitate large expenditure to help cancer. Early detection of liver or liver cancer is very important to overcome the very high risk of death caused by liver or liver cancer. This study aims to help classify liver or liver cancer based on data from routine examination results of patients summarized in the Indian Liver Data Patient (ILDP) dataset. The method used in the classification process in this research is backward elimination modeling for testing optimization and Random Forest algorithm and split validation to validate the model. The results of this study yielded 76.00% and value of AUC 0.758 results. These results indicate that the results of this study are good enough to help classify breast cancer

IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION BASED MACHINE LEARNING ALGORITHM FOR STUDENT PERFORMANCE PREDICTION Muhammad Iqbal; Irwan Herliawan; Ridwansyah Ridwansyah; Windu Gata; Abdul Hamid; Jajang Jaya Purnama; Yudhistira Yudhistira
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Education plays an important role in the development of a country, especially educational institutions as places where the educational process has an important goal to create quality education in improving student performance. Based on research conducted in the last few decades the quality of education in Portugal has improved, but statistics show that the failure rate of students in Portugal is high, especially in the fields of Mathematics and Portuguese. On the other hand, machine learning which is part of Artificial Intelligence is considered to be helpful in the field of education, one of which is in predicting student performance. However, measuring student performance becomes a challenge since student performance has several factors, one of which is the relationship of variables and factors for predicting the performance of participating in an orderly manner. This study aims to find out how the application of machine learning algorithms based on particle sworm optimization to predict student performance. By using experimental research methods and the results of empirical studies shown in each model, namely random forest, decision tree, support vector machine and particle swarm optimization based neural network can improve the accuracy of student performance predictions.

ALGORITMA C4.5 UNTUK MEMPREDIKSI PENGAMBILAN KEPUTUSAN MEMILIH DEPOSITO BERJANGKA Hendri Mahmud Nawawi; Sri Rahayu; Muhammad Ja’far Shidiq; Jajang Jaya Purnama
Jurnal Techno Nusa Mandiri Vol 16 No 1 (2019): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Ma
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Deposits are one form of investment offered by the Bank or other financial institutions with the nature of regulating and binding according to the rules set by the manager and the investor or commonly called investors. The advantage of being an investor is getting a fee or profit calculated based on the agreed time period at the beginning of the agreement. Whereas for investment fund managers can be used to advance and develop their business and business. Finding and determining potential customers is the first step to running a financial business in the form of this deposit, before the transaction decision is taken which is a favorable decision for both parties, investors or managers, one of the decision-making techniques can be done using Data Mining using the C4.5 Algorithm which is a structured decision-making technique based on input variables so that it can produce the most potential typical information for customers to participate in time deposits.

GARMENT EMPLOYEE PRODUCTIVITY PREDICTION USING RANDOM FOREST Imanuel Balla; Sri Rahayu; Jajang Jaya Purnama
Jurnal Techno Nusa Mandiri Vol 18 No 1 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.2210

Clothing also means clothing is needed by humans. Besides the need for clothing in terms of function, clothing sales or business is also very potent. About 75 million people worldwide are directly involved in textiles, clothing, and footwear. In this case, a common problem in this industry is that the actual productivity of apparel employees sometimes fails to reach the productivity targets set by the authorities to meet production targets on time, resulting in huge losses. Experiments were conducted using the random forest model, linear regression, and neural network by looking for the values of the correlation coefficient, MAE, and RMSE. This aims to predict the productivity of garment employees with data mining techniques that apply machine learning and look for the minimum MAE value. The results of testing the proposed algorithm on the garment worker productivity dataset obtained the smallest MAE, namely the random forest algorithm, namely 0.0787, linear regression 0.1081, and 0.1218 neural networks

Co-Authors Abdul Hamid Abdul Hamid Abdul Hamid Abdul Hamid Abdul Hamid Abdul Hamid Achmad Baroqah Pohan Achmad Rifai Ade Suryadi Afandi, Fifin Agung Baitul Hikmah Ami Rahmawati Anna Mukhayaroh, Anna Dede Wintana Ela Siti Laela Erni Ermawati Fitria Septia Nugraha Ganda Wijaya Ganda Wijaya, Ganda Hafis Nurdin Hendri Mahmud Nawawi Herliawan, Irwan Hermanto Hermanto Hermanto Hikmatulloh Hikmatulloh Imanuel Balla Irwan Herliawan Irwan Herliawan Kahfi, Ahmad Hafidzul Marliana Rahmawati Nurhanifah Mayangky, Nissa Almira Muhamad Hasan Muhammad Iqbal Muhammad Ja’far Shidiq Nawawi, Hendri Mahmud Nina Kurnia Hikmawati Nina Kurnia Hikmawati Nugraha, Fitra Septia Nurul Ichsan Ridwansyah Ridwansyah Ridwansyah Ridwansyah Ridwansyah Risnandar, Risnandar Siti Nurdiani Sri Hadianti Sri Rahayu SRI RAHAYU Sri Rahayu Sri Rahayu Sri Rahayu Sri Rahayu Suhardjono S Susy Rosyida Tri Wahyuni Tuti Haryanti Verry Riyanto Windu Gata Windu Gata Windu Gata Yudhistira Yudhistira

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