Pub Date : 2019-03-12DOI: 10.12962/J24068535.V17I1.A771
P. Manek, D. Siahaan
Requirements engineering phase in software development resulting in a SRS (Software Requirements Specification) document. The use of natural language approach in generating such document has some drawbacks that caused 7 common mistakes among the engineer which had been formulated by Meyer as "The 7 sins of specifier". One of the 7 common mistakes is noise. This study attempted to detect noise in software requirements with spectral clustering. The clustering algorithm working on fewer dimensions compared to others. The resulting kappa coefficient is 0.4426 . The result showed that the consistency between noise prediction and noise assessment made by three annotators is still low.
{"title":"NOISE DETECTION IN SOFTWARE REQUIREMENTS SPECIFICATION DOCUMENT USING SPECTRAL CLUSTERING","authors":"P. Manek, D. Siahaan","doi":"10.12962/J24068535.V17I1.A771","DOIUrl":"https://doi.org/10.12962/J24068535.V17I1.A771","url":null,"abstract":"Requirements engineering phase in software development resulting in a SRS (Software Requirements Specification) document. The use of natural language approach in generating such document has some drawbacks that caused 7 common mistakes among the engineer which had been formulated by Meyer as \"The 7 sins of specifier\". One of the 7 common mistakes is noise. This study attempted to detect noise in software requirements with spectral clustering. The clustering algorithm working on fewer dimensions compared to others. The resulting kappa coefficient is 0.4426 . The result showed that the consistency between noise prediction and noise assessment made by three annotators is still low.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43779934","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 : 2019-03-12DOI: 10.12962/J24068535.V17I1.A731
Dea Nugraha, Vinda Daningrum, Ariyadi Ariyadi, Tegar Palyus Fiqar
Sistem penggajian umumnya merupakan proses penggajian dari awal sampai gaji itu dibayarkan sesuai dengan hak masing-masing karyawan dapat dilakukan atau dilaksanakan dengan sistematis dan diharapkan tidak akan terdapat kesalahan dalam prosedur penggajian. Pada PT. Bumi Sawindo Permai (BSP) sebagai perusahaan pengolahan kelapa sawit yang menjadi tempat penelitian memiliki 3 unit bisnis yang ditunjang oleh pemanfaatan teknologi informasi, meliputi: perangkat lunak Enterprise Resource Planning ASCEND, dan Standart Operational Procedure (SOP) ASCEND, serta SOP Sistem Menejemen Integrasi (SMI). Proses bisnis produksi dan operasional tidak didefinisikan pada semua komponen tersebut. BSP memberlakukan sistem penggajian secara sistematis sesuai dengan prosedur yang berlaku, akan tetapi prosedur ini tidak tercantum dengan jelas kedalam sebuah blueprint. Ditemukan ketidakselarasan dari ketiga komponen tersebut pada implementasinya. Hal ini mereduksi indeks kinerja perusahaan khususnya pada proses penggajian karyawan yang dilakukan oleh bagian Human Capital Management (HCM) di 3 unit bisnis BSP. Dengan demikian perlu dilakukan eliminasi bottleneck pada proses bisnis berjalan. Pemodelan proses bisnis dengan Business Process Modelling Notation (BPMN) dilakukan sebagai langkah strategis pengembangan SOP sebagai standar baku mutu untuk peningkatan efisiensi perusahaan dalam hal pengelolaan sistem pembayaran gaji karyawan yang lebih terukur.
工资系统通常是工资的开始过程，直到工资按员工的权利进行或系统执行，并预计工资程序中不会出现错误。在PT. Bumi Sawindo Permai (BSP)，作为一名油棕榈加工公司，该研究机构拥有三个由信息技术支持的业务单位，其中包括:企业资源计划提升，以及标准运行程序程序(SOP)提升系统和标准执行系统集成(SMI)。生产和运营的业务流程并没有定义所有这些组件。BSP根据现有程序系统启动了工资单系统，但该程序没有明确列出在蓝图中。他们发现这三个部分的不一致。它对人力资源管理部门(HCM)在BSP业务的三个部门的员工工资进程进行了特别的转导。因此，在业务进程中消除瓶颈是必要的。将业务流程(BPMN)作为标准操作规程开发的战略步骤，以提高公司在管理更可衡量的员工工资体系方面的效率。
{"title":"PEMODELAN PROSES BISNIS PENGGAJIAN PADA PT. BUMI SAWINDO PERMAI","authors":"Dea Nugraha, Vinda Daningrum, Ariyadi Ariyadi, Tegar Palyus Fiqar","doi":"10.12962/J24068535.V17I1.A731","DOIUrl":"https://doi.org/10.12962/J24068535.V17I1.A731","url":null,"abstract":"Sistem penggajian umumnya merupakan proses penggajian dari awal sampai gaji itu dibayarkan sesuai dengan hak masing-masing karyawan dapat dilakukan atau dilaksanakan dengan sistematis dan diharapkan tidak akan terdapat kesalahan dalam prosedur penggajian. Pada PT. Bumi Sawindo Permai (BSP) sebagai perusahaan pengolahan kelapa sawit yang menjadi tempat penelitian memiliki 3 unit bisnis yang ditunjang oleh pemanfaatan teknologi informasi, meliputi: perangkat lunak Enterprise Resource Planning ASCEND, dan Standart Operational Procedure (SOP) ASCEND, serta SOP Sistem Menejemen Integrasi (SMI). Proses bisnis produksi dan operasional tidak didefinisikan pada semua komponen tersebut. BSP memberlakukan sistem penggajian secara sistematis sesuai dengan prosedur yang berlaku, akan tetapi prosedur ini tidak tercantum dengan jelas kedalam sebuah blueprint. Ditemukan ketidakselarasan dari ketiga komponen tersebut pada implementasinya. Hal ini mereduksi indeks kinerja perusahaan khususnya pada proses penggajian karyawan yang dilakukan oleh bagian Human Capital Management (HCM) di 3 unit bisnis BSP. Dengan demikian perlu dilakukan eliminasi bottleneck pada proses bisnis berjalan. Pemodelan proses bisnis dengan Business Process Modelling Notation (BPMN) dilakukan sebagai langkah strategis pengembangan SOP sebagai standar baku mutu untuk peningkatan efisiensi perusahaan dalam hal pengelolaan sistem pembayaran gaji karyawan yang lebih terukur.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43250524","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 : 2019-03-12DOI: 10.12962/J24068535.V17I1.A775
A. Akbar, Akhmad Khanif Zyen
Setting Examination schedules to support learning evaluation is crucial. The ideal scheduling for this exam must be able to allocate all related components in the implementation of the test within a predetermined time span. The components of the implementation of an examination in a university include the departments in the faculty, a number of courses and participants, the room used, the time of execution, and the lecturer serving as supervisor. The arrangement of each component of the implementation of the exam needs to be carried out appropriately so there is no collision of the schedule between the participants, the schedule, the room used, and the supervisor in charge. The purpose of this study is to produce an ideal exam scheduling and examination supervisor. The study was conducted by applying the Multi-Criteria Iterative Forward Search from the Academic Information System (SIAKAD) data at the Faculty of Science and Technology, Unisnu Jepara. This research has resulted in a system that is able to create an examination schedule and supervisory schedule that accommodates all factors without conflict, well tested, and applied.
{"title":"Metode Multi-Criteria Iterative Forward Search Untuk Penjadwalan Ujian dan Pengawas Ujian","authors":"A. Akbar, Akhmad Khanif Zyen","doi":"10.12962/J24068535.V17I1.A775","DOIUrl":"https://doi.org/10.12962/J24068535.V17I1.A775","url":null,"abstract":"Setting Examination schedules to support learning evaluation is crucial. The ideal scheduling for this exam must be able to allocate all related components in the implementation of the test within a predetermined time span. The components of the implementation of an examination in a university include the departments in the faculty, a number of courses and participants, the room used, the time of execution, and the lecturer serving as supervisor. The arrangement of each component of the implementation of the exam needs to be carried out appropriately so there is no collision of the schedule between the participants, the schedule, the room used, and the supervisor in charge. The purpose of this study is to produce an ideal exam scheduling and examination supervisor. The study was conducted by applying the Multi-Criteria Iterative Forward Search from the Academic Information System (SIAKAD) data at the Faculty of Science and Technology, Unisnu Jepara. This research has resulted in a system that is able to create an examination schedule and supervisory schedule that accommodates all factors without conflict, well tested, and applied.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48055530","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 : 2019-03-12DOI: 10.12962/J24068535.V17I1.A734
Margaretha Mei Mei, J. Andry
Event organizer is a company which engaged in event organizing, PR, and advertising. A suitable information systems that fit company's business needs are required so the company can adapt themselves in this globalization era. Information systems had an important role in order to support the company’s business process and its performance. An example of applied information systems that have been widely used by companies is enterprise architecture. Currently, enterprise architecture has been used by many enterprises to be able connect between the planning and the technology implementation to the current business in the company. Enterprise Architecture Planning (EAP) is a method in enterprise architecture which can provides alignment between business and information technology by defining company’s needs. Main components of EAP are data architecture, applications, and technology. The framework that will be used to develop EAP on this research is TOGAF ADM with phases starting from preliminary phase, requirements management, architecture vision, business architecture, information systems architectures, technology architecture, opportunities & solutions, and migration planning. A result on this research will be a blueprint of enterprise architecture model that an event organizer can use in supporting its business. The blueprint contains the current used information systems and the ideal information systems planned by the authors.
{"title":"The Alignment of Business Process In Event Organizer And Enterprise Architecture Using TOGAF","authors":"Margaretha Mei Mei, J. Andry","doi":"10.12962/J24068535.V17I1.A734","DOIUrl":"https://doi.org/10.12962/J24068535.V17I1.A734","url":null,"abstract":"Event organizer is a company which engaged in event organizing, PR, and advertising. A suitable information systems that fit company's business needs are required so the company can adapt themselves in this globalization era. Information systems had an important role in order to support the company’s business process and its performance. An example of applied information systems that have been widely used by companies is enterprise architecture. Currently, enterprise architecture has been used by many enterprises to be able connect between the planning and the technology implementation to the current business in the company. Enterprise Architecture Planning (EAP) is a method in enterprise architecture which can provides alignment between business and information technology by defining company’s needs. Main components of EAP are data architecture, applications, and technology. The framework that will be used to develop EAP on this research is TOGAF ADM with phases starting from preliminary phase, requirements management, architecture vision, business architecture, information systems architectures, technology architecture, opportunities & solutions, and migration planning. A result on this research will be a blueprint of enterprise architecture model that an event organizer can use in supporting its business. The blueprint contains the current used information systems and the ideal information systems planned by the authors.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44031986","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 : 2018-10-12DOI: 10.12962/J24068535.V16I2.A688
Erwin Prasetyowati, Nilam Ramadhani
Pengawasan terhadap kinerja akademik mahasiswa sebagai bentuk peningkatan mutu harus dilakukan secara tersistem dan terintegrasi. Namun pengawasan tersebut akan lebih efektif jika dilakukan secara periodik, yaitu pada tahun kedua dan keeempat dengan maksud pihak akademik dapat mengetahui perkembangan pencapaian belajar masing-masing mahasiswa dengan cepat, sehingga peringatan atau tindakan yang akan diberikan pada mahasiswa dan evaluasi terhadap seluruh aktivitas akademis dapat segera dilakukan. Penelitian ini bertujuan mengklasifikasikan kinerja mahasiswa melalui IPK dan jumlah SKS yang belum diselesaikan selama masa studinya. Klasifikasi dilakukan pada tahun kedua dan tahun keempat masa studi. Pada tahun kedua, klasifikasi dibagi menjadi tiga status yaitu Normal, Bermasalah dan Peringatan dengan ditentukan melalui standar nilai yang ditentukan. Pada tahun keempat klasifikasi dibagi menjadi dua kelompok, yaitu kelompok Lulus dan Drop Out. Proses klasifikasi yang dilakukan pada tahun keempat, menggunakan algoritma Naive Bayes yang terbukti memiliki tingkat keakurasian yang tinggi dengan metode maximum likehood atau berdasarkan kemiripan tertinggi dari data yang diolah. Pada proses penghitungan Naive Bayes terdapat sedikit keraguan apabila ada peluang yang bernilai 0. Oleh karena itu untuk memaksimalkan performa dari Naive Bayes dalam klasifikasi ini, maka digunakan Dirichlet Smoothing. Berdasarkan hasil pengujian terhadap 200 data uji maka didapatkan nilai akurasi mencapai 91.50%, nilai precision sebesar 88.78% dan nilai recall adalah 95%. Dengan demikian dapat diketahui bahwa data memiliki nilai yang konsisten.
{"title":"SISTEM EVALUASI DAN KLASIFIKASI KINERJA AKADEMIK MAHASISWA UNIVERSITAS MADURA MENGGUNAKAN NAIVE BAYES DENGAN DIRICHLET SMOOTHING","authors":"Erwin Prasetyowati, Nilam Ramadhani","doi":"10.12962/J24068535.V16I2.A688","DOIUrl":"https://doi.org/10.12962/J24068535.V16I2.A688","url":null,"abstract":"Pengawasan terhadap kinerja akademik mahasiswa sebagai bentuk peningkatan mutu harus dilakukan secara tersistem dan terintegrasi. Namun pengawasan tersebut akan lebih efektif jika dilakukan secara periodik, yaitu pada tahun kedua dan keeempat dengan maksud pihak akademik dapat mengetahui perkembangan pencapaian belajar masing-masing mahasiswa dengan cepat, sehingga peringatan atau tindakan yang akan diberikan pada mahasiswa dan evaluasi terhadap seluruh aktivitas akademis dapat segera dilakukan. Penelitian ini bertujuan mengklasifikasikan kinerja mahasiswa melalui IPK dan jumlah SKS yang belum diselesaikan selama masa studinya. Klasifikasi dilakukan pada tahun kedua dan tahun keempat masa studi. Pada tahun kedua, klasifikasi dibagi menjadi tiga status yaitu Normal, Bermasalah dan Peringatan dengan ditentukan melalui standar nilai yang ditentukan. Pada tahun keempat klasifikasi dibagi menjadi dua kelompok, yaitu kelompok Lulus dan Drop Out. Proses klasifikasi yang dilakukan pada tahun keempat, menggunakan algoritma Naive Bayes yang terbukti memiliki tingkat keakurasian yang tinggi dengan metode maximum likehood atau berdasarkan kemiripan tertinggi dari data yang diolah. Pada proses penghitungan Naive Bayes terdapat sedikit keraguan apabila ada peluang yang bernilai 0. Oleh karena itu untuk memaksimalkan performa dari Naive Bayes dalam klasifikasi ini, maka digunakan Dirichlet Smoothing. Berdasarkan hasil pengujian terhadap 200 data uji maka didapatkan nilai akurasi mencapai 91.50%, nilai precision sebesar 88.78% dan nilai recall adalah 95%. Dengan demikian dapat diketahui bahwa data memiliki nilai yang konsisten.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49572960","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 : 2018-10-09DOI: 10.12962/J24068535.V16I2.A762
M. D. E. Susanti, H. Tjandrasa, C. Fatichah
Sebuah sistem penyaringan otomatis dan sistem diagnosa yang akurat sangat berguna untuk proses analisis hasil pemeriksaan pap smear. Langkah yang paling utama dari sistem tersebut adalah proses segmentasi sel nukleus dan sitoplasma pada citra hasil pemeriksaan pap smear , karena dapat memengaruhi keakuratan sistem. Normally Biased Generalized Gradient Vector Flow Snake (NBGGVFS) merupakan sebuah algoritma gaya eksternal untuk active contour (snake) yang menggabungkan metode Generalized Gradient Vector Flow Snake (GGVFS) dan Normally Biased Gradient Vector Flow Snake (NBGVFS). Dalam memodelkan snake, terdapat fungsi edge map. Edge map biasanya dihitung dengan menggunakan operator deteksi tepi seperti sobel. Namun, metode ini tidak dapat mendeteksi daerah nukleus dari citra smear serviks dengan benar. Penelitian ini bertujuan untuk segmentasi citra sel tunggal smear serviks dengan memanfaatkan penggunaan Radiating Edge Map untuk menghitung edge map dari citra dengan metode NBGGVFS. Metode yang diusulkan terdiri atas tiga tahapan utama, yaitu tahap praproses, segmentasi awal dan segmentasi kontur. Uji coba dilakukan dengan menggunakan data set Herlev. Pengujian dilakukan dengan membandingkan hasil segmentasi metode yang diusulkan dengan metode pada penelitian sebelumnya dalam melakukan segmentasi citra sel tunggal smear serviks. Hasil pengujian menunjukkan bahwa metode yang diusulkan mampu mendeteksi area nukleus lebih optimal metode penelitian sebelumnya. Nilai rata-rata akurasi dan Zijdenbos Similarity Index (ZSI) untuk segmentasi nukleus adalah 96,96% dan 90,68%. Kemudian, nilai rata-rata akurasi dan ZSI untuk segmentasi sitoplasma adalah 86,78% and 89,35%. Dari hasil evaluasi tersebut, disimpulkan metode yang diusulkan dapat digunakan sebagai proses segmentasi citra smear serviks pada identifikasi kanker serviks secara otomatis.
{"title":"Segmentasi Citra Sel Tunggal Smear Serviks Menggunakan Metode Radiating Normally Biased Generalized Gradient Vector Flow Snake","authors":"M. D. E. Susanti, H. Tjandrasa, C. Fatichah","doi":"10.12962/J24068535.V16I2.A762","DOIUrl":"https://doi.org/10.12962/J24068535.V16I2.A762","url":null,"abstract":"Sebuah sistem penyaringan otomatis dan sistem diagnosa yang akurat sangat berguna untuk proses analisis hasil pemeriksaan pap smear. Langkah yang paling utama dari sistem tersebut adalah proses segmentasi sel nukleus dan sitoplasma pada citra hasil pemeriksaan pap smear , karena dapat memengaruhi keakuratan sistem. Normally Biased Generalized Gradient Vector Flow Snake (NBGGVFS) merupakan sebuah algoritma gaya eksternal untuk active contour (snake) yang menggabungkan metode Generalized Gradient Vector Flow Snake (GGVFS) dan Normally Biased Gradient Vector Flow Snake (NBGVFS). Dalam memodelkan snake, terdapat fungsi edge map. Edge map biasanya dihitung dengan menggunakan operator deteksi tepi seperti sobel. Namun, metode ini tidak dapat mendeteksi daerah nukleus dari citra smear serviks dengan benar. Penelitian ini bertujuan untuk segmentasi citra sel tunggal smear serviks dengan memanfaatkan penggunaan Radiating Edge Map untuk menghitung edge map dari citra dengan metode NBGGVFS. Metode yang diusulkan terdiri atas tiga tahapan utama, yaitu tahap praproses, segmentasi awal dan segmentasi kontur. Uji coba dilakukan dengan menggunakan data set Herlev. Pengujian dilakukan dengan membandingkan hasil segmentasi metode yang diusulkan dengan metode pada penelitian sebelumnya dalam melakukan segmentasi citra sel tunggal smear serviks. Hasil pengujian menunjukkan bahwa metode yang diusulkan mampu mendeteksi area nukleus lebih optimal metode penelitian sebelumnya. Nilai rata-rata akurasi dan Zijdenbos Similarity Index (ZSI) untuk segmentasi nukleus adalah 96,96% dan 90,68%. Kemudian, nilai rata-rata akurasi dan ZSI untuk segmentasi sitoplasma adalah 86,78% and 89,35%. Dari hasil evaluasi tersebut, disimpulkan metode yang diusulkan dapat digunakan sebagai proses segmentasi citra smear serviks pada identifikasi kanker serviks secara otomatis.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42488724","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 : 2018-10-09DOI: 10.12962/J24068535.V16I2.A661
Nursanti Novi Arisa, Chastine Fatichah
Leukemia is one of the dangerous diseases that can cause death. One of the types of leukemia is acute leukemia that includes ALL ( A cute L ymphoblastic L eukemia) and AML (Acute Myeloid Leukemia). The fastest identification against this disease can be done by computing and analysing white blood cell types. However, the manual c ounting and identification of the white blood cell types are still limited by time. Therefore, automatic counting process is necessary to be conducted in order to get the results more quickly and accurately. Previous studies showed that automatic counting process in the image of Acute Leukemia cells faced some obstacles, the existence of touching cell and the implementation of geometry feature that cannot produce an accurate counting. It is because the shapes of the cell are various. This study proposed a method for the counting of white blood cells and the separation of touching cells on Acute Leukemia cells image by using Multi Pass Voting method (MPV) based on seed detection (centroid) and K-Means method. Initial segmentation used for separating foreground and background area is canny edge detection. The next stage is seed detection (centroid) using Multi Pass Voting method. The co unting of white blood cells is based on the results of the centroid produced. The existence of the touching cells are separated using K-Means method, the determination of the initial centroid is based on the results of the Multi Pass Voting method. Based on the evaluation results of 40 images of Acute Leukemia dataset, the proposed method is capable to properly compute based on the centroid. It is also able to separate the touching cell into a single cell. The accuracy of the white blood cell counting result is about 98,6%.
{"title":"PERHITUNGAN DAN PEMISAHAN SEL DARAH PUTIH BERDASARKAN CENTROID DENGAN MENGGUNAKAN METODE MULTI PASS VOTING DAN K-MEANS PADA CITRA SEL ACUTE LEUKEMIA","authors":"Nursanti Novi Arisa, Chastine Fatichah","doi":"10.12962/J24068535.V16I2.A661","DOIUrl":"https://doi.org/10.12962/J24068535.V16I2.A661","url":null,"abstract":"Leukemia is one of the dangerous diseases that can cause death. One of the types of leukemia is acute leukemia that includes ALL ( A cute L ymphoblastic L eukemia) and AML (Acute Myeloid Leukemia). The fastest identification against this disease can be done by computing and analysing white blood cell types. However, the manual c ounting and identification of the white blood cell types are still limited by time. Therefore, automatic counting process is necessary to be conducted in order to get the results more quickly and accurately. Previous studies showed that automatic counting process in the image of Acute Leukemia cells faced some obstacles, the existence of touching cell and the implementation of geometry feature that cannot produce an accurate counting. It is because the shapes of the cell are various. This study proposed a method for the counting of white blood cells and the separation of touching cells on Acute Leukemia cells image by using Multi Pass Voting method (MPV) based on seed detection (centroid) and K-Means method. Initial segmentation used for separating foreground and background area is canny edge detection. The next stage is seed detection (centroid) using Multi Pass Voting method. The co unting of white blood cells is based on the results of the centroid produced. The existence of the touching cells are separated using K-Means method, the determination of the initial centroid is based on the results of the Multi Pass Voting method. Based on the evaluation results of 40 images of Acute Leukemia dataset, the proposed method is capable to properly compute based on the centroid. It is also able to separate the touching cell into a single cell. The accuracy of the white blood cell counting result is about 98,6%.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42637128","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 : 2018-10-09DOI: 10.12962/J24068535.V16I2.A754
Vynska Amalia Permadi, T. Ahmad, B. J. Santoso
K-Most Promising (K-MPP) product is a strategy for selecting a product that used in the process of determining the most demanded products by consumers. The basic computations used to perform K-MPP are two types of skyline queries: dynamic skyline and reverse skyline. K-MPP selection is done on the application layer, which is the last layer of the OSI model. One of the application layer functions is providing services according to the user's preferences. In the K-MPP implementation, there exists the situation in which the manufacturer may be less satisfied with the query results generated by the database search process (why-not question), so they want to know why the database gives query results that do not match their expectations. For example, manufacturers want to know why a particular data point (unexpected data) appears in the query result set, and why the expected product does not appear as a query result. The next problem is that traditional database systems will not be able to provide data analysis and solution to answer why-not questions preferred by users. To improve the usability of the database system, this study is aiming to answer why-not K-MPP and providing data refinement solutions by considering user feedback, so users can also find out why the result set does not meet their expectations. Moreover, it may help users to understand the result by performing analysis information and data refinement suggestion.
{"title":"DATA REFINEMENT APPROACH FOR ANSWERING WHY-NOT PROBLEM OVER K-MOST PROMISING PRODUCT (K-MPP) QUERIES","authors":"Vynska Amalia Permadi, T. Ahmad, B. J. Santoso","doi":"10.12962/J24068535.V16I2.A754","DOIUrl":"https://doi.org/10.12962/J24068535.V16I2.A754","url":null,"abstract":"K-Most Promising (K-MPP) product is a strategy for selecting a product that used in the process of determining the most demanded products by consumers. The basic computations used to perform K-MPP are two types of skyline queries: dynamic skyline and reverse skyline. K-MPP selection is done on the application layer, which is the last layer of the OSI model. One of the application layer functions is providing services according to the user's preferences. In the K-MPP implementation, there exists the situation in which the manufacturer may be less satisfied with the query results generated by the database search process (why-not question), so they want to know why the database gives query results that do not match their expectations. For example, manufacturers want to know why a particular data point (unexpected data) appears in the query result set, and why the expected product does not appear as a query result. The next problem is that traditional database systems will not be able to provide data analysis and solution to answer why-not questions preferred by users. To improve the usability of the database system, this study is aiming to answer why-not K-MPP and providing data refinement solutions by considering user feedback, so users can also find out why the result set does not meet their expectations. Moreover, it may help users to understand the result by performing analysis information and data refinement suggestion.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47826315","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 : 2018-10-09DOI: 10.12962/j24068535.v16i2.a721
Siprianus Septian Manek, H. Tjandrasa
Soft Weighted Median Filter Method (SWMF) is one of the new methods for noise filtering in image processing. This method is used for two types of noise in images, there is fixed valued noise (FVN) and random valued noise (RVN). Fixed valued noise is a noise type with an unchanged value, it changes the pixel value of the image to the maximum and minimum values (0 and 255), while random valued noise is a noise type with a changed value. An example of fixed valued noise is salt & pepper noise, while for random valued noise can be exemplified as gaussian, poisson, speckle, and localvar noise. Based on previous research, SWMF method can be applied to all images with all kinds of noise (FVN and RVN) and able to reduce the noise well. This method has a higher PSNR value than other methods, especially for random valued noise types such as: gaussian, speckle, and localvar noise. In this study, we propose to examine the performance of the SWMF method further by comparing this method with other methods such as Median Filter, Mean Filter, Gaussian Filter, and Wiener Filter in an image segmentation process. The image segmentation process in this research is based on area detection using Top-Hat transform and Otsu thresholding and line detection using Sobel edge detection. The performance measurement process uses the calculation of sensitivity value, specificity, and accuracy on the image segmentation with the groundtruh image. The results show that Soft Weighted Median Filter method can improve the quality of image segmentation with the average accuracy of 95.70% by reducing fixed value noise and random valued noise in the images.
{"title":"Soft Weighted Median Filter Method for Improved Image Segmentation with Noise","authors":"Siprianus Septian Manek, H. Tjandrasa","doi":"10.12962/j24068535.v16i2.a721","DOIUrl":"https://doi.org/10.12962/j24068535.v16i2.a721","url":null,"abstract":"Soft Weighted Median Filter Method (SWMF) is one of the new methods for noise filtering in image processing. This method is used for two types of noise in images, there is fixed valued noise (FVN) and random valued noise (RVN). Fixed valued noise is a noise type with an unchanged value, it changes the pixel value of the image to the maximum and minimum values (0 and 255), while random valued noise is a noise type with a changed value. An example of fixed valued noise is salt & pepper noise, while for random valued noise can be exemplified as gaussian, poisson, speckle, and localvar noise. Based on previous research, SWMF method can be applied to all images with all kinds of noise (FVN and RVN) and able to reduce the noise well. This method has a higher PSNR value than other methods, especially for random valued noise types such as: gaussian, speckle, and localvar noise. In this study, we propose to examine the performance of the SWMF method further by comparing this method with other methods such as Median Filter, Mean Filter, Gaussian Filter, and Wiener Filter in an image segmentation process. The image segmentation process in this research is based on area detection using Top-Hat transform and Otsu thresholding and line detection using Sobel edge detection. The performance measurement process uses the calculation of sensitivity value, specificity, and accuracy on the image segmentation with the groundtruh image. The results show that Soft Weighted Median Filter method can improve the quality of image segmentation with the average accuracy of 95.70% by reducing fixed value noise and random valued noise in the images.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42319578","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 : 2018-10-09DOI: 10.12962/J24068535.V16I2.A750
A. Rosyadi, N. Suciati
Transition region based image segmentation is one of the simple and effective image segmentation methods. This method is capable to segment image contains single or multiple objects. However, this method depends on the background. It may produce a bad segmentation result if the gray level variance is high or the background is textured. So a method to repair the transition region is needed. In this study, a new method to repair the transition region with median filter based on the percentage of the adjacent transitional pixels is proposed. Transition region is extracted from the grayscale image. Transition region refinement is conducted based on the percentage of the adjacent transitional pixels. Then, several morphological operations and the edge linking process are conducted to the transition region. Afterward, region filling is used to get the foreground area. Finally, image of segmentation result is obtained by showing the pixels of grayscale image that are located in the foreground area. The value of misclassification error (ME), false negative rate (FNR), and false positive rate (FPR) of the segmentation result are calculated to measure the proposed method performance. Performance of the proposed method is compared with the other method. The experimental results show that the proposed method has average value of ME, FPR, and FNR: 0.0297, 0.0209, and 0.0828 respectively. It defines that the proposed method has better performance than the other methods. Furthermore, the proposed method works well on the image with a variety of background, especially on image with textured background.
{"title":"Median Filter For Transition Region Refinement In Image Segmentation","authors":"A. Rosyadi, N. Suciati","doi":"10.12962/J24068535.V16I2.A750","DOIUrl":"https://doi.org/10.12962/J24068535.V16I2.A750","url":null,"abstract":"Transition region based image segmentation is one of the simple and effective image segmentation methods. This method is capable to segment image contains single or multiple objects. However, this method depends on the background. It may produce a bad segmentation result if the gray level variance is high or the background is textured. So a method to repair the transition region is needed. In this study, a new method to repair the transition region with median filter based on the percentage of the adjacent transitional pixels is proposed. Transition region is extracted from the grayscale image. Transition region refinement is conducted based on the percentage of the adjacent transitional pixels. Then, several morphological operations and the edge linking process are conducted to the transition region. Afterward, region filling is used to get the foreground area. Finally, image of segmentation result is obtained by showing the pixels of grayscale image that are located in the foreground area. The value of misclassification error (ME), false negative rate (FNR), and false positive rate (FPR) of the segmentation result are calculated to measure the proposed method performance. Performance of the proposed method is compared with the other method. The experimental results show that the proposed method has average value of ME, FPR, and FNR: 0.0297, 0.0209, and 0.0828 respectively. It defines that the proposed method has better performance than the other methods. Furthermore, the proposed method works well on the image with a variety of background, especially on image with textured background.","PeriodicalId":31796,"journal":{"name":"JUTI Jurnal Ilmiah Teknologi Informasi","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42997435","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：