Pub Date : 2022-10-17DOI: 10.31328/jointecs.v7i3.3782
Imron Rosydi, Aryo Nugroho, Awalludiyah Ambarwati
Telecommunications is an important thing today. Service providers and telecommunications networks compete to provide the best service, one of which is by increasing their BTS. BTS (Base Transceiver Station) owned by telecommunications companies are spread throughout the region. BTS is a cellular telecommunications network device which is generally in the form of a tower with an antenna that functions as a signal transmitter and receiver, so that it can connect the cellular telecommunications operator network with its users. Maintenance and handling of BTS disturbances must be carried out properly and appropriately, so that network quality is maintained. If a BTS experiences interference, the cellular network signal in that area will be lost, and will automatically harm consumers because they cannot make phone calls and cannot access the internet. Therefore repairs must be made immediately to avoid losses from the company and consumers. The method used is a waterfall development life cycle (SLDC) system based on Android. Testing was using 5 characteristics of the ISO 25010; functional suitability, usability, and performance efficiency. The test results of functional suitability test is 1 (good), 90% (very feasible) on the usability test, and 2 seconds (accepted) on the performance
{"title":"Sistem Monitoring BTS Pada Perusahaan Telekomunikasi Seluler Berbasis Aplikasi Mobile","authors":"Imron Rosydi, Aryo Nugroho, Awalludiyah Ambarwati","doi":"10.31328/jointecs.v7i3.3782","DOIUrl":"https://doi.org/10.31328/jointecs.v7i3.3782","url":null,"abstract":"Telecommunications is an important thing today. Service providers and telecommunications networks compete to provide the best service, one of which is by increasing their BTS. BTS (Base Transceiver Station) owned by telecommunications companies are spread throughout the region. BTS is a cellular telecommunications network device which is generally in the form of a tower with an antenna that functions as a signal transmitter and receiver, so that it can connect the cellular telecommunications operator network with its users. Maintenance and handling of BTS disturbances must be carried out properly and appropriately, so that network quality is maintained. If a BTS experiences interference, the cellular network signal in that area will be lost, and will automatically harm consumers because they cannot make phone calls and cannot access the internet. Therefore repairs must be made immediately to avoid losses from the company and consumers. The method used is a waterfall development life cycle (SLDC) system based on Android. Testing was using 5 characteristics of the ISO 25010; functional suitability, usability, and performance efficiency. The test results of functional suitability test is 1 (good), 90% (very feasible) on the usability test, and 2 seconds (accepted) on the performance","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131031092","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 : 2022-10-17DOI: 10.31328/jointecs.v7i3.4053
Firman Nurdiansyah, Fitri Marisa
Indonesia merupakan negara yang sangat berkembang jumlah penduduknya. Seiring dengan perkembangan tahun ke tahun terus diimbangi dengan kesadaran akan arti penting peningkatan gizi dalam kehidupan. Oleh karena itu diperlukan sistem klasifikasi ayam petelur menggunakan Artificial Neural Network dan Decision Tree. Penelitian ini bertujuan untuk mengklasifikasikan jenis-jenis dari ayam petelur yang ada di Indonesia. Karena banyaknya jenis ayam, nantinya akan memudahkan masyarakat ataupun pengusaha ayam dalam memilih ayam petelur yang berkualitas baik. Disisi lain juga dapat meningkatkan ekonomi masyarakat dengan cara menjual sebuah ayam petelur dengan kualitas yang baik. Dalam pengujian yang dihasilkan Artificial Neural Network lebih baik dalam proses pengujiannya. Hasil membuktikan pada split ratio 50:50 tekstur dan bentuk dengan nilai precision mendapatkan nilai mencapai 0.680, recall mendapatkan nilai 0.521, f-measure mendapatkan nilai 0.600 dan accuracy juga memiliki nilai tertinggi mencapai 92.50% pada split ratio 50:50 antara data training dan data testing. Hasil membuktikan dengan klasifikasi menggunakan Artificial Neural Network menghasilkan precision, recall, f-measure dan accuracy tertinggi dibandingkan decision tree.
{"title":"Klasifikasi Ayam Petelur Menggunakan Artificial Neural Network dan Decision Tree","authors":"Firman Nurdiansyah, Fitri Marisa","doi":"10.31328/jointecs.v7i3.4053","DOIUrl":"https://doi.org/10.31328/jointecs.v7i3.4053","url":null,"abstract":"Indonesia merupakan negara yang sangat berkembang jumlah penduduknya. Seiring dengan perkembangan tahun ke tahun terus diimbangi dengan kesadaran akan arti penting peningkatan gizi dalam kehidupan. Oleh karena itu diperlukan sistem klasifikasi ayam petelur menggunakan Artificial Neural Network dan Decision Tree. Penelitian ini bertujuan untuk mengklasifikasikan jenis-jenis dari ayam petelur yang ada di Indonesia. Karena banyaknya jenis ayam, nantinya akan memudahkan masyarakat ataupun pengusaha ayam dalam memilih ayam petelur yang berkualitas baik. Disisi lain juga dapat meningkatkan ekonomi masyarakat dengan cara menjual sebuah ayam petelur dengan kualitas yang baik. Dalam pengujian yang dihasilkan Artificial Neural Network lebih baik dalam proses pengujiannya. Hasil membuktikan pada split ratio 50:50 tekstur dan bentuk dengan nilai precision mendapatkan nilai mencapai 0.680, recall mendapatkan nilai 0.521, f-measure mendapatkan nilai 0.600 dan accuracy juga memiliki nilai tertinggi mencapai 92.50% pada split ratio 50:50 antara data training dan data testing. Hasil membuktikan dengan klasifikasi menggunakan Artificial Neural Network menghasilkan precision, recall, f-measure dan accuracy tertinggi dibandingkan decision tree.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134408121","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 : 2022-10-17DOI: 10.31328/jointecs.v7i3.3988
A. L. Maukar, Fitri Marisa, Anik Vega Vitianingsih, Bella Chelsea Berliana, Mucalinda Rupasari
Many barriers to attending study sessions at university are removed by online learning which minimizes the financial burden of travel, and transfers, and is not constrained by time or location constraints. Visualization tools can engage students and instructors in an active learning process as they build a spatially semantic view of the knowledge, concepts, and skills students possess and acquire. This study aims to provide a systematic literature review on the use of gamification in online collaborative learning, including the various important components of online collaborative learning that ensure active student participation, important elements of games that facilitate active student participation, and effective gamification approaches to online learning. collaborative learning. student. Systematic Literature Review (SLR) method was used in this study. Starting with determining the topic, then proceeding with collecting, sorting, and analyzing papers related to the topic. Game design on gamification attracts the attention of professionals in the field of education who are still trying to find methods to motivate, engage, persuade, and improve student performance. They have the lowest preference for this element of the game because of the negative feelings and emotions evoked by getting a low rating.
{"title":"Model Pembelajaran Kolaborasi dengan Gamifikasi: Sebuah Kajian Pustaka","authors":"A. L. Maukar, Fitri Marisa, Anik Vega Vitianingsih, Bella Chelsea Berliana, Mucalinda Rupasari","doi":"10.31328/jointecs.v7i3.3988","DOIUrl":"https://doi.org/10.31328/jointecs.v7i3.3988","url":null,"abstract":"Many barriers to attending study sessions at university are removed by online learning which minimizes the financial burden of travel, and transfers, and is not constrained by time or location constraints. Visualization tools can engage students and instructors in an active learning process as they build a spatially semantic view of the knowledge, concepts, and skills students possess and acquire. This study aims to provide a systematic literature review on the use of gamification in online collaborative learning, including the various important components of online collaborative learning that ensure active student participation, important elements of games that facilitate active student participation, and effective gamification approaches to online learning. collaborative learning. student. Systematic Literature Review (SLR) method was used in this study. Starting with determining the topic, then proceeding with collecting, sorting, and analyzing papers related to the topic. Game design on gamification attracts the attention of professionals in the field of education who are still trying to find methods to motivate, engage, persuade, and improve student performance. They have the lowest preference for this element of the game because of the negative feelings and emotions evoked by getting a low rating.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125199585","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 : 2022-10-17DOI: 10.31328/jointecs.v7i3.3873
Vindy Kusuma Dwinanda, Cepi Ramdani, S. T. Safitri
Photography is an activity of taking pictures through a camera to produce works of art that can be enjoyed by other people and a service job to capture activities in the form of photos. The types of services provided in photography services are ordering, scheduling, administrative management, and photo data management. The processing of these data in MSME Phi Photograph is still done conventionally. The documentation is not good and requires customers to come to a studio, causing customers to lack time efficiency. These problems cause obstacles and a lack of time efficiency. The research aims to design an information system that can perform data processing for services to be adequately computerized the RAD Method for development because it requires quick and short steps and time. Furthermore, testing is carried out using two methods: black box testing to determine the level of success and testing using the SUS to reduce the system's risks. The average score is 80, which can be categorized as an Excellent (B) scale with an acceptable rating. With the information system, it is hoped that it can facilitate business processes that run with business goals so that admins and visitors can order photos.
{"title":"Digitalisasi Proses Bisnis UMKM Fotografi Melalui Aplikasi Berbasis Web Menggunakan Metode RAD","authors":"Vindy Kusuma Dwinanda, Cepi Ramdani, S. T. Safitri","doi":"10.31328/jointecs.v7i3.3873","DOIUrl":"https://doi.org/10.31328/jointecs.v7i3.3873","url":null,"abstract":"Photography is an activity of taking pictures through a camera to produce works of art that can be enjoyed by other people and a service job to capture activities in the form of photos. The types of services provided in photography services are ordering, scheduling, administrative management, and photo data management. The processing of these data in MSME Phi Photograph is still done conventionally. The documentation is not good and requires customers to come to a studio, causing customers to lack time efficiency. These problems cause obstacles and a lack of time efficiency. The research aims to design an information system that can perform data processing for services to be adequately computerized the RAD Method for development because it requires quick and short steps and time. Furthermore, testing is carried out using two methods: black box testing to determine the level of success and testing using the SUS to reduce the system's risks. The average score is 80, which can be categorized as an Excellent (B) scale with an acceptable rating. With the information system, it is hoped that it can facilitate business processes that run with business goals so that admins and visitors can order photos.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122927053","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 : 2022-10-17DOI: 10.31328/jointecs.v7i3.3915
Mochammad Choirur Roziqin, adinda prameswari, A. Wicaksono, Veronika Vestine
Rekam Medis adalah dokumen rahasia sehingga dalam penyelenggaraannya perlu adanya pencatatan data rekam medis yang terintegrasi dan lengkap. Klinik Pratama Kimia Farma Jember melaksanakan pencatatan rekam medis secara manual, belum dilaksanakannya retensi dan angka kunjungan yang tinggi sebesar 20416 pada tahun 2021 menyebabkan ruang penyimpanan yang tersedia tidak cukup untuk menampung berkas rekam medis, serta pencatatan penggunaan nomor RM dan laporan kunjungan pasien yang menggunakan Google sheets. Berdasarkan pernyataan tersebut, pencatatan rekam medis yang dilaksanakan kurang efektif. Sehingga dibutuhkan rekam medis elektronik yang mencakup proses pencatatan rekam medis secara elektronik, pelaporan dan retensi rekam medis. Penelitian ini merupakan penelitian research and development dengan metode pengumpulan data melalui wawancara, observasi, dokumentasi, dan brainstorming. Perancangan ini menggunakan metode pengembangan sistem prototype yang terdiri dari tahapan analisis kebutuhan user, pembuatan prototype, penyesuaian prototype, pembuatan program, pengujian dan evaluasi. Tahapan analisa yaitu melalui analisa masalah dan kebutuhan sistem. Tahap pembuatan prototype menggunakan flowchart system, Context Diagram, DFD, dan ERD. Tahap penyesuaian prototype menggunakan metode brainstorming. Tahap pembuatan program menggunakan bahasa pemrograman PHP, Bootstrap, MySQL, dan Codeigniter. Tahapan pengujian menggunakan blackbox testing. Tahap evaluasi sistem menggunakan brainstorming. Hasil penelitian adalah rekam medis elektronik rawat jalan berbasis web yang dapat mempermudah dan mengatasi permasalahan dalam penyelenggaraan rekam medis.
{"title":"Sistem Rekam Medis Elektronik Berbasis Web","authors":"Mochammad Choirur Roziqin, adinda prameswari, A. Wicaksono, Veronika Vestine","doi":"10.31328/jointecs.v7i3.3915","DOIUrl":"https://doi.org/10.31328/jointecs.v7i3.3915","url":null,"abstract":"Rekam Medis adalah dokumen rahasia sehingga dalam penyelenggaraannya perlu adanya pencatatan data rekam medis yang terintegrasi dan lengkap. Klinik Pratama Kimia Farma Jember melaksanakan pencatatan rekam medis secara manual, belum dilaksanakannya retensi dan angka kunjungan yang tinggi sebesar 20416 pada tahun 2021 menyebabkan ruang penyimpanan yang tersedia tidak cukup untuk menampung berkas rekam medis, serta pencatatan penggunaan nomor RM dan laporan kunjungan pasien yang menggunakan Google sheets. Berdasarkan pernyataan tersebut, pencatatan rekam medis yang dilaksanakan kurang efektif. Sehingga dibutuhkan rekam medis elektronik yang mencakup proses pencatatan rekam medis secara elektronik, pelaporan dan retensi rekam medis. Penelitian ini merupakan penelitian research and development dengan metode pengumpulan data melalui wawancara, observasi, dokumentasi, dan brainstorming. Perancangan ini menggunakan metode pengembangan sistem prototype yang terdiri dari tahapan analisis kebutuhan user, pembuatan prototype, penyesuaian prototype, pembuatan program, pengujian dan evaluasi. Tahapan analisa yaitu melalui analisa masalah dan kebutuhan sistem. Tahap pembuatan prototype menggunakan flowchart system, Context Diagram, DFD, dan ERD. Tahap penyesuaian prototype menggunakan metode brainstorming. Tahap pembuatan program menggunakan bahasa pemrograman PHP, Bootstrap, MySQL, dan Codeigniter. Tahapan pengujian menggunakan blackbox testing. Tahap evaluasi sistem menggunakan brainstorming. Hasil penelitian adalah rekam medis elektronik rawat jalan berbasis web yang dapat mempermudah dan mengatasi permasalahan dalam penyelenggaraan rekam medis.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"97 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114502036","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 : 2022-05-31DOI: 10.31328/jointecs.v7i2.3725
Ahmad Farisi, Rizani Teguh, R. Lestari
This study measures the quality of information systems using the McCall method with a case study of the Integrated Hajj Information System called SIHAT at PT. Arraudhah Wisata Imani. After studying the literature and spreading the preresearch questionnaire, this research started by distributing Mc’Call’s questionnaires to 30 respondents. Furthermore , the results were tested for validity and reliability values to obtain valid and reliable variables and indicators. These variables and indicators are then used to measure the quality value (Fa) of each variable. The measurement begins with the weighting process of the variables and indicators through a questionnaire filled out by experts. The weighting uses a scale of 0.1 to 0.5 for each variable of correctness, reliability, efficiency, integrity, and usability along with their indicators. The quality measurement results show that the correctness factor is 58%, reliability is 30%, efficiency is 19%, integrity is 58% and usability is 45%. Overall, the quality of SIHAT Arraudhah is at a value of 41% which is in the range of 41%-60%, which means that SIHAT Arraudhah is of sufficient quality.
{"title":"Analisis Kualitas Sistem Informasi Haji Terpadu Menggunakan Metode McCall","authors":"Ahmad Farisi, Rizani Teguh, R. Lestari","doi":"10.31328/jointecs.v7i2.3725","DOIUrl":"https://doi.org/10.31328/jointecs.v7i2.3725","url":null,"abstract":"This study measures the quality of information systems using the McCall method with a case study of the Integrated Hajj Information System called SIHAT at PT. Arraudhah Wisata Imani. After studying the literature and spreading the preresearch questionnaire, this research started by distributing Mc’Call’s questionnaires to 30 respondents. Furthermore , the results were tested for validity and reliability values to obtain valid and reliable variables and indicators. These variables and indicators are then used to measure the quality value (Fa) of each variable. The measurement begins with the weighting process of the variables and indicators through a questionnaire filled out by experts. The weighting uses a scale of 0.1 to 0.5 for each variable of correctness, reliability, efficiency, integrity, and usability along with their indicators. The quality measurement results show that the correctness factor is 58%, reliability is 30%, efficiency is 19%, integrity is 58% and usability is 45%. Overall, the quality of SIHAT Arraudhah is at a value of 41% which is in the range of 41%-60%, which means that SIHAT Arraudhah is of sufficient quality.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123410723","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 : 2022-05-31DOI: 10.31328/jointecs.v7i2.3685
Sarah Latifah, Irfan Ardiansah
PT. Saudagar Buah Indonesia is an agro-industry company with processed fruit products, namely Frutivez. During the pandemic, Frutivez product sales have dropped drastically. Therefore, the company needs to implement a new marketing strategy, namely opening a store on the Lazada site for market expansion through online store media. On e-commerce platforms, newly opened stores need to be optimized so that these products can appear at the top when consumers search for products. This research was conducted using the implementation of SEO techniques to increase Frutivez store traffic on Lazada and measure the effectiveness of the Frutivez store page on Lazada. The method used is a descriptive quantitative method using primary data and secondary data. The results of the SEO implementation on the store show that the store's conversion rate is 3.33%. Of the 4 products used in the search analysis based on keywords, the four products are in the 1st row, 6th row, 38th row, and 26th row. The use of the product upgrade feature for 14 days shows a pretty good performance. All Frutivez feed posts have a 0% conversion value so that the Frutivez store lazada feed content does not affect the sales and number of shop visitors.
PT. Saudagar Buah Indonesia是一家农业工业公司，生产加工水果产品，即Frutivez。疫情期间，Frutivez的产品销量大幅下降。因此，公司需要实施新的营销策略，即在Lazada网站上开设门店，通过网店媒体进行市场拓展。在电商平台上，新开的门店需要进行优化，让这些产品在消费者搜索产品时出现在最前面。本研究使用SEO技术来增加Lazada上Frutivez商店的流量，并测量Lazada上Frutivez商店页面的有效性。使用的方法是描述性的定量方法，使用主要数据和次要数据。对店铺进行SEO实施的结果显示，店铺的转化率为3.33%。在基于关键词进行搜索分析的4个产品中，这4个产品分别位于第1行、第6行、第38行、第26行。产品升级功能使用了14天，表现相当不错。所有的Frutivez feed帖子都有0%的转换值，这样Frutivez商店lazada feed内容就不会影响销售和商店访客的数量。
{"title":"Implementasi Teknik Search Engine Optimization Dalam Meningkatkan Trafik Toko Frutivez Pada Lazada","authors":"Sarah Latifah, Irfan Ardiansah","doi":"10.31328/jointecs.v7i2.3685","DOIUrl":"https://doi.org/10.31328/jointecs.v7i2.3685","url":null,"abstract":"PT. Saudagar Buah Indonesia is an agro-industry company with processed fruit products, namely Frutivez. During the pandemic, Frutivez product sales have dropped drastically. Therefore, the company needs to implement a new marketing strategy, namely opening a store on the Lazada site for market expansion through online store media. On e-commerce platforms, newly opened stores need to be optimized so that these products can appear at the top when consumers search for products. This research was conducted using the implementation of SEO techniques to increase Frutivez store traffic on Lazada and measure the effectiveness of the Frutivez store page on Lazada. The method used is a descriptive quantitative method using primary data and secondary data. The results of the SEO implementation on the store show that the store's conversion rate is 3.33%. Of the 4 products used in the search analysis based on keywords, the four products are in the 1st row, 6th row, 38th row, and 26th row. The use of the product upgrade feature for 14 days shows a pretty good performance. All Frutivez feed posts have a 0% conversion value so that the Frutivez store lazada feed content does not affect the sales and number of shop visitors.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124607794","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 : 2022-05-31DOI: 10.31328/jointecs.v7i2.3687
Dodi Suprayogi, H. Pardede
Penyebaran Virus COVID-19 sangat mengkhawatirkan dan terus menyebar serta meluas di seluruh negara terinfeksi mulai dari anak-anak hingga orang dewasa. Banyak cara dalam membuat suatu prediksi, dalam hal ini menentukan prediksi jumlah penderita COVID-19 bisa dengan menggunakan machine learning, tidak hanya COVID-19. Penelitian ini mencoba memprediksi kapan Pandemic COVID-19 ini menurun dengan menggunakan algoritma SVR dengan kernel RBF, Linear, Polynomial, dan Sigmoid, pemilihan model menggunakan SVR karena SVR mampu mengatasi overfitting. Penelitian ini menggunakan dataset dari github John Hopkins University menggunakan sample lima negara dengan jumlah kasus COVID-19 yang berbeda. Hasil yang didapat untuk kernel RBF sangat baik untuk lima negara dalam membuat pola grafik yang fit antara data aktual dan data prediksi, dengan melakukan tunning parameter yang berbeda-beda disetiap negara, kemudian melakukan pengujian nilai gamma untuk mendapatkan nilai RMSE, R2, dan MAE, hasil terbaik ada pada negara Jerman dengan nilai RMSE 0.099, kemudian Itali dengan nilai RMSE 0.101, Indonesia nilai RMSE 0.102, brazil nilai RMSE 0.105, dan US nilai RMSE 0.105.
{"title":"Support Vector Regression Dalam Prediksi Penurunan Jumlah Kasus Penderita Covid-19","authors":"Dodi Suprayogi, H. Pardede","doi":"10.31328/jointecs.v7i2.3687","DOIUrl":"https://doi.org/10.31328/jointecs.v7i2.3687","url":null,"abstract":"Penyebaran Virus COVID-19 sangat mengkhawatirkan dan terus menyebar serta meluas di seluruh negara terinfeksi mulai dari anak-anak hingga orang dewasa. Banyak cara dalam membuat suatu prediksi, dalam hal ini menentukan prediksi jumlah penderita COVID-19 bisa dengan menggunakan machine learning, tidak hanya COVID-19. Penelitian ini mencoba memprediksi kapan Pandemic COVID-19 ini menurun dengan menggunakan algoritma SVR dengan kernel RBF, Linear, Polynomial, dan Sigmoid, pemilihan model menggunakan SVR karena SVR mampu mengatasi overfitting. Penelitian ini menggunakan dataset dari github John Hopkins University menggunakan sample lima negara dengan jumlah kasus COVID-19 yang berbeda. Hasil yang didapat untuk kernel RBF sangat baik untuk lima negara dalam membuat pola grafik yang fit antara data aktual dan data prediksi, dengan melakukan tunning parameter yang berbeda-beda disetiap negara, kemudian melakukan pengujian nilai gamma untuk mendapatkan nilai RMSE, R2, dan MAE, hasil terbaik ada pada negara Jerman dengan nilai RMSE 0.099, kemudian Itali dengan nilai RMSE 0.101, Indonesia nilai RMSE 0.102, brazil nilai RMSE 0.105, dan US nilai RMSE 0.105. ","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619239","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}
According to WHO, cancer is one type of disease with a high increase in terms of cases around the world. Breast cancer is the highest contributor to morbidity rates in 2020, which is 2.26 million cases. In determining the patient's prognosis, several examinations are needed, one of them is histopathological analysis. However, histopathological analysis is a relatively tedious and time-consuming process. With the development of deep learning, computer vision can be applied for detection in medical images, which is expected to help improve the accuracy of the prognosis and the speed of identification carried out by experts. Based on this knowledge, this study aims to implement multi-class classification (normal, benign, in situ, invasive) and prediction of normal digital tissue images or has suspected cancer cells using the Convolutional Neural Network with multi-scale and multi-feature network (CNN-G). The dataset used is 400 breast tissue image data which are classified into four classes and labeled by a pathologist. The accuracy result obtained from the training is 0.5375~0.54 and has made an increase when the result was compared to single models (CNN14, CNN42, CNN84). Other model evaluation methods conducted are confusion matrix, precision, recall, and f-1 score.
{"title":"Implementasi Metode CNN Multi-Scale Input dan Multi-Feature Network untuk Dugaan Kanker Payudara","authors":"Ghifari Prameswari Natakusumah, Ernastuti Ernastuti","doi":"10.31328/jointecs.v7i2.3637","DOIUrl":"https://doi.org/10.31328/jointecs.v7i2.3637","url":null,"abstract":"According to WHO, cancer is one type of disease with a high increase in terms of cases around the world. Breast cancer is the highest contributor to morbidity rates in 2020, which is 2.26 million cases. In determining the patient's prognosis, several examinations are needed, one of them is histopathological analysis. However, histopathological analysis is a relatively tedious and time-consuming process. With the development of deep learning, computer vision can be applied for detection in medical images, which is expected to help improve the accuracy of the prognosis and the speed of identification carried out by experts. Based on this knowledge, this study aims to implement multi-class classification (normal, benign, in situ, invasive) and prediction of normal digital tissue images or has suspected cancer cells using the Convolutional Neural Network with multi-scale and multi-feature network (CNN-G). The dataset used is 400 breast tissue image data which are classified into four classes and labeled by a pathologist. The accuracy result obtained from the training is 0.5375~0.54 and has made an increase when the result was compared to single models (CNN14, CNN42, CNN84). Other model evaluation methods conducted are confusion matrix, precision, recall, and f-1 score.","PeriodicalId":259537,"journal":{"name":"JOINTECS (Journal of Information Technology and Computer Science)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132458238","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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