{"title":"Penerapan Metode Convolution Neural Network (CNN) Dalam Proses Pengolahan Citra Untuk Mendeteksi Cacat Produksi Pada Produk Masker","authors":"Yozika Arvio, Dine Tiara Kusuma, Iriansyah Bm Sangadji, Erno Kurniawan Dewantara","doi":"10.30998/faktorexacta.v16i4.20073","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.20073","url":null,"abstract":"ABSTRACT","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.19447
R. Astuti, Firmansyah Firmansyah, MS Hasibuan
Service on site is one of the after-sales services for Hino Truck vehicles. The Service on Site contract program provides customer vehicle service services at the customer's location or site by placing a mechanic at the customer's location. In its implementation, several obstacles were encountered, such as the vehicle service history was not recorded, there were no service reports so the customer did not know the vehicle's performance. So this research develops the design of the Hino Service on Site Information System using observational research methods, literature review, and documentation. To build the system, Use Case diagrams were designed and then measured using Use Case Points (UCP) to assist management in expanding the Servicee on Site Information System. UCP will assist management when making decisions regarding system development in terms of time, human resources and finances. Software measurement using UCP in the Service on Site Information System at Hino Dealers PT. Persada Lampung Raya has a Use Case Point (UCP) score of 38.448 and is categorized as a small software size project, which is smaller than 99. With the proposed design of this system, it can simplify and speed up the on site service administration process and can provide information in the form of vehicle performance reports to customers so that they can improve service on site program
{"title":"Perancangan Sistem Informasi Hino Service on Site (Studi Kasus : Dealer Hino, PT. Persada Lampung Raya)","authors":"R. Astuti, Firmansyah Firmansyah, MS Hasibuan","doi":"10.30998/faktorexacta.v16i4.19447","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.19447","url":null,"abstract":"Service on site is one of the after-sales services for Hino Truck vehicles. The Service on Site contract program provides customer vehicle service services at the customer's location or site by placing a mechanic at the customer's location. In its implementation, several obstacles were encountered, such as the vehicle service history was not recorded, there were no service reports so the customer did not know the vehicle's performance. So this research develops the design of the Hino Service on Site Information System using observational research methods, literature review, and documentation. To build the system, Use Case diagrams were designed and then measured using Use Case Points (UCP) to assist management in expanding the Servicee on Site Information System. UCP will assist management when making decisions regarding system development in terms of time, human resources and finances. Software measurement using UCP in the Service on Site Information System at Hino Dealers PT. Persada Lampung Raya has a Use Case Point (UCP) score of 38.448 and is categorized as a small software size project, which is smaller than 99. With the proposed design of this system, it can simplify and speed up the on site service administration process and can provide information in the form of vehicle performance reports to customers so that they can improve service on site program","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"22 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.19216
E. Wardhani, Saruni Dwiasnati
ABSTRACT
摘要
{"title":"Deteksi Pelat Nomor Dengan Menggunakan Optical Character Recognition Berbasis Algoritma LSTM","authors":"E. Wardhani, Saruni Dwiasnati","doi":"10.30998/faktorexacta.v16i4.19216","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.19216","url":null,"abstract":"ABSTRACT","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"25 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.19767
Nofita Rismawati, Muhamad Femy Mulya
,
,
{"title":"Perancangan Diagnosa Covid-19 Menggunakan Metode Case Based Reasoning (CBR) Untuk Mengidentifikasi Tingkatan Gejala Pasien Covid-19","authors":"Nofita Rismawati, Muhamad Femy Mulya","doi":"10.30998/faktorexacta.v16i4.19767","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.19767","url":null,"abstract":",","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"33 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.19670
Rifki Ristiawan, Farrell Wahyudi, Noni Selvia
ABSTRACT
摘要
{"title":"Analisis Model Matematika dan Simulasi Pada Penyebaran Hepatitis Non HepA-E Akut di Indonesia","authors":"Rifki Ristiawan, Farrell Wahyudi, Noni Selvia","doi":"10.30998/faktorexacta.v16i4.19670","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.19670","url":null,"abstract":"ABSTRACT","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"23 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.18962
I. Fauzi, Imaniah Bazlina Wardani, Indra Lukmana Putra, Peni Puspitasari
One aspect of marketing activities is distribution. In the process of distributing goods, it is important to determine the optimal route that minimize mileage and reduce costs. This study aims to provide alternative solutions in determining distribution routes with the shortest distance which has implications for shorter travel times and lower costs. This research adapts the Capacitated Vehicle Routing Problem (CVRP) model with the approach of sweep and Particle Swarm Optimization (PSO) algorithm to determine the route. To generate a comparison route, we use the Nearest Neighbor (NN) algorithm. The result was that 100 agents were divided into 6 clusters and the total distance of the PSO-generated route is 218.115 units or 85.70% of the route distance generated by Nearest Neighbor algorithm.
{"title":"Penerapan Algoritma Sweep dan Particle Swarm Optimization (PSO) sebagai Alternatif Menentukan Rute Distribusi","authors":"I. Fauzi, Imaniah Bazlina Wardani, Indra Lukmana Putra, Peni Puspitasari","doi":"10.30998/faktorexacta.v16i4.18962","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.18962","url":null,"abstract":"One aspect of marketing activities is distribution. In the process of distributing goods, it is important to determine the optimal route that minimize mileage and reduce costs. This study aims to provide alternative solutions in determining distribution routes with the shortest distance which has implications for shorter travel times and lower costs. This research adapts the Capacitated Vehicle Routing Problem (CVRP) model with the approach of sweep and Particle Swarm Optimization (PSO) algorithm to determine the route. To generate a comparison route, we use the Nearest Neighbor (NN) algorithm. The result was that 100 agents were divided into 6 clusters and the total distance of the PSO-generated route is 218.115 units or 85.70% of the route distance generated by Nearest Neighbor algorithm.","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"41 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.20852
Rayung Wulan, Themotia Titi Widaningsih, Fit Yanuar
{"title":"Clustering the K-means Algorithm with the Approach to Student Interpersonal Communication Patterns in Selecting Secondary Schools","authors":"Rayung Wulan, Themotia Titi Widaningsih, Fit Yanuar","doi":"10.30998/faktorexacta.v16i4.20852","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.20852","url":null,"abstract":"","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"21 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.30998/faktorexacta.v16i4.21040
Riri Fajriah, Melyana Melyana, Gandung Triyono
PT Bank DKI Cabang Syariah Wahid Hasyim adalah cabang usaha yang melayani segmentasi pasar syariah dari PT Bank DKI sebagai BUMD dari Pemerintah Provinsi DKI Jakarta. Adapun produk bank yang ditawarkan terkait jenis layanan keuangan dan berbagai jenis kredit yang ditawarkan kepada calon debitur, seperti Kredit Pemilikan Rumah (KPR), Mikro UMKM, Kredit Multiguna, Bank Garansi. Permasalahan yang dihadapi saat ini adalah masih cukup signifikan kasus kredit macet di bank akibat kesalahan keputusan dalam pemberian kredit dari data analisa kelayakan calon debitur. Oleh karena itu, tujuan penelitian ini adalah untuk merancang sistem pendukung keputusan dengan menggunakan metode waterfall analysis dengan model perbandingan eksponensial dimana sistem ini akan digunakan oleh Relationship Manager (RM) untuk mengevaluasi kelayakan kredit calon debitur dengan lebih tepat dan akurat. Hasil penelitian ini menyajikan rancangan sistem pendukung keputusan dengan metode perbandingan eksponensial yang dapat membantu proses analisa kredit dari data-data calon debitur yang diproses untuk menghasilkan ranking penilaian kelayakan pemberian kredit, dimana keputusan pemberian kredit diambil berdasarkan nilai tertinggi hasil perhitungan MPE dan hasil ini akan menjadai landasan bagi Relationship Manager sebagai prioritas calon debitur untuk proses selanjutnya mendapatkan persetujuan kredit dari Pemimpin Cabang sebagai penyelia kredit di PT Bank DKI Cabang Syariah Wahid Hasyim.
PT Bank DKI Wahid Hasyim Syariah Branch 是雅加达 DKI 省政府下属的 PT Bank DKI 伊斯兰教法分行，为伊斯兰教法市场提供服务。该分行提供的银行产品涉及金融服务类型以及向潜在债务人提供的各类信贷，如住房自有贷款（KPR）、微型中小微企业贷款、多用途贷款、银行担保等。目前面临的问题是，由于从潜在债务人可行性分析数据中得出的授信决策失误，银行仍存在大量不良信贷案例。因此，本研究的目的是利用瀑布分析法和指数比较模型设计一个决策支持系统，关系经理（RM）将利用该系统更准确、更精确地评估潜在债务人的信用度。本研究的结果介绍了一种使用指数比较法的决策支持系统设计，该系统可以帮助对潜在债务人数据进行信用分析，处理后产生信用度评估排名，根据 MPE 计算结果的最高值做出授信决定，这些结果将成为关系经理的依据，作为潜在债务人下一步从作为 PT Bank DKI Wahid Hasyim Syariah Branch 信贷主管的分行经理处获得信贷审批的优先级。
{"title":"Implementasi Metode Perbandingan Eksponensial Dalam Sistem Pendukung Keputusan Pemberian Kredit Nasabah Pada PT Bank DKI Cabang Syariah Wahid Hasyim","authors":"Riri Fajriah, Melyana Melyana, Gandung Triyono","doi":"10.30998/faktorexacta.v16i4.21040","DOIUrl":"https://doi.org/10.30998/faktorexacta.v16i4.21040","url":null,"abstract":"PT Bank DKI Cabang Syariah Wahid Hasyim adalah cabang usaha yang melayani segmentasi pasar syariah dari PT Bank DKI sebagai BUMD dari Pemerintah Provinsi DKI Jakarta. Adapun produk bank yang ditawarkan terkait jenis layanan keuangan dan berbagai jenis kredit yang ditawarkan kepada calon debitur, seperti Kredit Pemilikan Rumah (KPR), Mikro UMKM, Kredit Multiguna, Bank Garansi. Permasalahan yang dihadapi saat ini adalah masih cukup signifikan kasus kredit macet di bank akibat kesalahan keputusan dalam pemberian kredit dari data analisa kelayakan calon debitur. Oleh karena itu, tujuan penelitian ini adalah untuk merancang sistem pendukung keputusan dengan menggunakan metode waterfall analysis dengan model perbandingan eksponensial dimana sistem ini akan digunakan oleh Relationship Manager (RM) untuk mengevaluasi kelayakan kredit calon debitur dengan lebih tepat dan akurat. Hasil penelitian ini menyajikan rancangan sistem pendukung keputusan dengan metode perbandingan eksponensial yang dapat membantu proses analisa kredit dari data-data calon debitur yang diproses untuk menghasilkan ranking penilaian kelayakan pemberian kredit, dimana keputusan pemberian kredit diambil berdasarkan nilai tertinggi hasil perhitungan MPE dan hasil ini akan menjadai landasan bagi Relationship Manager sebagai prioritas calon debitur untuk proses selanjutnya mendapatkan persetujuan kredit dari Pemimpin Cabang sebagai penyelia kredit di PT Bank DKI Cabang Syariah Wahid Hasyim.","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"28 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-22DOI: 10.30998/faktorexacta.v14i3.10591
Y. Cahyana, Amril Mutoi Siregar
Penyakit COVID-19 sekarang ini telah dinyatakan penyeakit pandemic karena tingkat penyebaran dan resiko yang ditimbulkan sangat berbahaya. Berbagai langkah seperti program awareness social distancing dan contact tracing telah dilakukan untuk mengendalikan wabah COVID-19. Jika tidak ada vaksin prediksi kasus yang dikonfirmasi meninggal dan pulih diperlukan untuk meningkatkan kapasitas sistem perawatan kesehatan dan mengendalikan penularan. Dalam studi ini kasus kumulatif dan harian dikonfirmasi meninggal dan pulih di Indonesia. Analisisa tidak mempertimbangkan perubahan apa pun dalam tindakan pengendalian pemerintah. Informasi dari studi ini dapat memberikan informasi yang relevan kepada pemerintah dan pejabat Kesehatan dan masyarakat. Bagaimana tingkat kesembuhan terhadap terkonfirmasi tingkat kematian terhadap jumlah penderita. Penelitian ini menggunakan model regresi dan clustering dengan K-means menggunakan unsupervised learning dan supervised learning untuk membangun distribusi model. Hasil penelitian ini dengan metode regresi dengan R2 = 0.99 sedangkan untuk clustering denga K= interval 10 - 15 dilihat dari hasil metode elbow The COVID-19 disease has now been declared a pandemic disease because the level of spread and the risk posed is very dangerous. Various steps such as awareness programs, social distancing, and contact tracing have been taken to control the COVID-19 outbreak. In the absence of a vaccine, prediction of confirmed cases, deaths, and recoveries is needed to increase the capacity of the health care system and control transmission. In this study, cumulative and daily cases were confirmed, died, and recovered in Indonesia. The analysis does not consider any changes in government control measures. Information from this study can provide relevant information to government and health officials and the public. How is the cure rate to the confirmed, the death rate to the number of sufferers? This study uses regression and clustering models with K-means, using unsupervised learning and supervised learning to build the distribution model. The results of this study using the regression method with R2 = 0.99, while for clustering with K = 10 - 15 intervals seen from the results of the elbow method. Keywords: COVID-19, Regresi, Unsupervised learning, Prediction, k-means
{"title":"Prediksi Analisis Penderita Covid19 di Indonesia dengan Metode Linier Regresi dan Unsupervised Learning","authors":"Y. Cahyana, Amril Mutoi Siregar","doi":"10.30998/faktorexacta.v14i3.10591","DOIUrl":"https://doi.org/10.30998/faktorexacta.v14i3.10591","url":null,"abstract":"Penyakit COVID-19 sekarang ini telah dinyatakan penyeakit pandemic karena tingkat penyebaran dan resiko yang ditimbulkan sangat berbahaya. Berbagai langkah seperti program awareness social distancing dan contact tracing telah dilakukan untuk mengendalikan wabah COVID-19. Jika tidak ada vaksin prediksi kasus yang dikonfirmasi meninggal dan pulih diperlukan untuk meningkatkan kapasitas sistem perawatan kesehatan dan mengendalikan penularan. Dalam studi ini kasus kumulatif dan harian dikonfirmasi meninggal dan pulih di Indonesia. Analisisa tidak mempertimbangkan perubahan apa pun dalam tindakan pengendalian pemerintah. Informasi dari studi ini dapat memberikan informasi yang relevan kepada pemerintah dan pejabat Kesehatan dan masyarakat. Bagaimana tingkat kesembuhan terhadap terkonfirmasi tingkat kematian terhadap jumlah penderita. Penelitian ini menggunakan model regresi dan clustering dengan K-means menggunakan unsupervised learning dan supervised learning untuk membangun distribusi model. Hasil penelitian ini dengan metode regresi dengan R2 = 0.99 sedangkan untuk clustering denga K= interval 10 - 15 dilihat dari hasil metode elbow The COVID-19 disease has now been declared a pandemic disease because the level of spread and the risk posed is very dangerous. Various steps such as awareness programs, social distancing, and contact tracing have been taken to control the COVID-19 outbreak. In the absence of a vaccine, prediction of confirmed cases, deaths, and recoveries is needed to increase the capacity of the health care system and control transmission. In this study, cumulative and daily cases were confirmed, died, and recovered in Indonesia. The analysis does not consider any changes in government control measures. Information from this study can provide relevant information to government and health officials and the public. How is the cure rate to the confirmed, the death rate to the number of sufferers? This study uses regression and clustering models with K-means, using unsupervised learning and supervised learning to build the distribution model. The results of this study using the regression method with R2 = 0.99, while for clustering with K = 10 - 15 intervals seen from the results of the elbow method. Keywords: COVID-19, Regresi, Unsupervised learning, Prediction, k-means","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":"48 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41259277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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