Pub Date : 2020-02-21DOI: 10.14421/JISKA.2020.43-07
Firman Tawakal, Ahmedika Azkiya
Dengue Hemorrhagic Fever is a disease that is carried and transmitted through the mosquito Aedes aegypti and Aedes albopictus which is commonly found in tropical and subtropical regions such as in Indonesia to Northern Australia. in 2013 there are 2.35 million reported cases, which is 37,687 case is heavy cases of DHF. DHF’s symthoms have a similarity with typhoid fever, it often occur wrong handling. Therefore we need a system that is able to diagnose the disease suffered by patients, so that they can recognize whether the patient has DHF or Typhoid. The system will be built using Neural Network Learning Vector Quantization (LVQ) based on the best training results. This research is to diagnose Dengue Hemorrhagic Fever using LVQ with input parameters are hemoglobin, leukocytes, platelets, and heritrocytes. Based on result, the best accuracy is 97,14% with Mean Square Error (MSE) is 0.028571 with 84 train data and 36 test data. Conclution from the research is LVQ method can diagnose DHF Keywords: Dengue Hemorrhagic Fever; Learning Vector Quantization; classification; Neural Network;
{"title":"Diagnosa Penyakit Demam Berdarah Dengue (DBD) menggunakan Metode Learning Vector Quantization (LVQ)","authors":"Firman Tawakal, Ahmedika Azkiya","doi":"10.14421/JISKA.2020.43-07","DOIUrl":"https://doi.org/10.14421/JISKA.2020.43-07","url":null,"abstract":"Dengue Hemorrhagic Fever is a disease that is carried and transmitted through the mosquito Aedes aegypti and Aedes albopictus which is commonly found in tropical and subtropical regions such as in Indonesia to Northern Australia. in 2013 there are 2.35 million reported cases, which is 37,687 case is heavy cases of DHF. DHF’s symthoms have a similarity with typhoid fever, it often occur wrong handling. Therefore we need a system that is able to diagnose the disease suffered by patients, so that they can recognize whether the patient has DHF or Typhoid. The system will be built using Neural Network Learning Vector Quantization (LVQ) based on the best training results. This research is to diagnose Dengue Hemorrhagic Fever using LVQ with input parameters are hemoglobin, leukocytes, platelets, and heritrocytes. Based on result, the best accuracy is 97,14% with Mean Square Error (MSE) is 0.028571 with 84 train data and 36 test data. Conclution from the research is LVQ method can diagnose DHF Keywords: Dengue Hemorrhagic Fever; Learning Vector Quantization; classification; Neural Network;","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44122065","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 : 2020-02-01DOI: 10.14421/jiska.2020.53-03
Intan Fitriani, Aryo Baskoro Utomo
Along with the development of technology, Short Message Service (SMS) has begun to be used to communicate between someone and the system in an agency. But in some cases, the security of messages sent through the SMS application has not been well protected. To improve data security and confidentiality, cryptographic algorithms with Advanced Encryption Standard (AES) can be done. The method used is the Waterfall method. AES encryption testing is done by comparing the manual calculations and the results of the encryption on the system. Blackbox test, CrackStation test, and Avalanche Effect (AE) test were also carried out. Brute force test results using CrackStation software that ciphertext cannot be solved. And in the avalanche effect (AE) test, the AE value of each 128-bit AES key is 44.53%, 192-bit is 48.44%, and 256-bit is 56.25%. Therefore, 192-bit and 256-bit AES keys are recommended for use because AE values are in the range of 45% - 60%.
{"title":"Implementasi Algoritma Advanced Encryption Standard (AES) pada Layanan SMS Desa","authors":"Intan Fitriani, Aryo Baskoro Utomo","doi":"10.14421/jiska.2020.53-03","DOIUrl":"https://doi.org/10.14421/jiska.2020.53-03","url":null,"abstract":"Along with the development of technology, Short Message Service (SMS) has begun to be used to communicate between someone and the system in an agency. But in some cases, the security of messages sent through the SMS application has not been well protected. To improve data security and confidentiality, cryptographic algorithms with Advanced Encryption Standard (AES) can be done. The method used is the Waterfall method. AES encryption testing is done by comparing the manual calculations and the results of the encryption on the system. Blackbox test, CrackStation test, and Avalanche Effect (AE) test were also carried out. Brute force test results using CrackStation software that ciphertext cannot be solved. And in the avalanche effect (AE) test, the AE value of each 128-bit AES key is 44.53%, 192-bit is 48.44%, and 256-bit is 56.25%. Therefore, 192-bit and 256-bit AES keys are recommended for use because AE values are in the range of 45% - 60%.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43843105","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 : 2019-12-13DOI: 10.14421/JISKA.2019.42-03
Anita Sindar Sinaga
The low production of smallholder rubber is caused by various factors, one of the causes is interference from various diseases. Building a system (computer) that is intelligent to analyze problems, observe the work system of an expert or expert. Expertise comes from the development of knowledge of someone who is competent and directly provides instructions to solve a problem. Certainty Factor is a method to prove whether a fact is certain or not certain in the form of metrics that are usually used in expert systems. This method is very suitable for expert systems that diagnose something that is uncertain. To apply the Certainty Factor method to the expert system, data is needed that will be input into the system, processed and display the results of the diagnosis of rubber plant diseases. Input: rubber plant disease type data and disease symptom data. Process: carry out analysis and calculation to get the diagnosis results using the Certainty Factor method. Output: information on the diagnosis of rubber plant diseases and percentage of confidence level in the diagnosis results in accordance with the rules of the Certainty Factor method. Keywords : Rubber Disease, Symptoms Diagnosis, Value Combination, Certainty Factor
{"title":"Sistem Pakar Diagnosa Penyakit Pohon Karet dengan Metode Certainty Factor","authors":"Anita Sindar Sinaga","doi":"10.14421/JISKA.2019.42-03","DOIUrl":"https://doi.org/10.14421/JISKA.2019.42-03","url":null,"abstract":"The low production of smallholder rubber is caused by various factors, one of the causes is interference from various diseases. Building a system (computer) that is intelligent to analyze problems, observe the work system of an expert or expert. Expertise comes from the development of knowledge of someone who is competent and directly provides instructions to solve a problem. Certainty Factor is a method to prove whether a fact is certain or not certain in the form of metrics that are usually used in expert systems. This method is very suitable for expert systems that diagnose something that is uncertain. To apply the Certainty Factor method to the expert system, data is needed that will be input into the system, processed and display the results of the diagnosis of rubber plant diseases. Input: rubber plant disease type data and disease symptom data. Process: carry out analysis and calculation to get the diagnosis results using the Certainty Factor method. Output: information on the diagnosis of rubber plant diseases and percentage of confidence level in the diagnosis results in accordance with the rules of the Certainty Factor method. Keywords : Rubber Disease, Symptoms Diagnosis, Value Combination, Certainty Factor ","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46163867","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 : 2019-08-30DOI: 10.14421/JISKA.2019.33-04
Annisa Khodista Syaka, Agus Mulyanto
Jumlah jemaah umrah yang semakin meningkat mempengaruhi munculnya banyak perusahaan jasa perjalanan umrah khususnya di Daerah Istimewa Yogyakarta. Hal ini mengakibatkan calon jemaah umrah kesulitan menemukan biro perjalanan umrah yang sesuai dengan keinginannya, sehingga membutuhkan proses pemilihan biro perjalanan umrah dengan metode pengambilan keputusan yang relevan. Penelitian ini menganalisis tingkat sensitivitas metode Analytical Hierarchy Process (AHP) dan metode Weighted Product (WP) dalam pemilihan biro perjalanan umrah. Mengacu pada hasil analisis sensitivitas yang peneliti lakukan pada 6 percobaan dengan jumlah kriteria yang berbeda, metode AHP menghasilkan jumlah perubahan rangking sebesar 881 dan jumlah presentase sensitivitas sebesar 17.898%, sedangkan metode WP menghasilkan jumlah perubahan rangking sebesar 836 dan jumlah presentase sensitivitas sebesar 16.901%. Berdasarkan pada jumlah perubahan rangking dan presentase sensitivitas, dapat disimpulkan bahwa metode AHP merupakan metode yang relevan dalam pemilihan biro perjalanan umrah di Daerah Istimewa Yogyakarta.
{"title":"Analisis Perbandingan Sensitivitas AHP dan WP dalam Pemilihan Biro Perjalanan Umrah di Yogyakarta","authors":"Annisa Khodista Syaka, Agus Mulyanto","doi":"10.14421/JISKA.2019.33-04","DOIUrl":"https://doi.org/10.14421/JISKA.2019.33-04","url":null,"abstract":"Jumlah jemaah umrah yang semakin meningkat mempengaruhi munculnya banyak perusahaan jasa perjalanan umrah khususnya di Daerah Istimewa Yogyakarta. Hal ini mengakibatkan calon jemaah umrah kesulitan menemukan biro perjalanan umrah yang sesuai dengan keinginannya, sehingga membutuhkan proses pemilihan biro perjalanan umrah dengan metode pengambilan keputusan yang relevan. Penelitian ini menganalisis tingkat sensitivitas metode Analytical Hierarchy Process (AHP) dan metode Weighted Product (WP) dalam pemilihan biro perjalanan umrah. Mengacu pada hasil analisis sensitivitas yang peneliti lakukan pada 6 percobaan dengan jumlah kriteria yang berbeda, metode AHP menghasilkan jumlah perubahan rangking sebesar 881 dan jumlah presentase sensitivitas sebesar 17.898%, sedangkan metode WP menghasilkan jumlah perubahan rangking sebesar 836 dan jumlah presentase sensitivitas sebesar 16.901%. Berdasarkan pada jumlah perubahan rangking dan presentase sensitivitas, dapat disimpulkan bahwa metode AHP merupakan metode yang relevan dalam pemilihan biro perjalanan umrah di Daerah Istimewa Yogyakarta.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41816745","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 : 2019-08-30DOI: 10.14421/JISKA.2019.33-01
Muhammad Mustakim, Retantyo Wardoyo
Pertumbuhan jumlah data rekam medik yang pesat, menjadi masalah tersediri yang harus diantisipasi. Untuk menangani fenomena information overload dalam informasi rekam medis, perlu studi yang mendalam untuk dapat mengembangkan model filtering informasi rekam medik yang secara efektif mendukung peningkatan kualitas rekomendasi proses pencarian informasi. Berbagai penelitian terkait pencarian informasi medis telah banyak dilakukan, diantaranya mengembangkan penelitian dengan konsentrasi pada kebaruan dan keberagaman, menggunakan fuzzy ontology, berbasis factor tensor, memepertimbangkan niatan/intention pengguna ketika melakukan pencarian serta pendekatan dengan menggabungkan pencarian berbasis frasa dengan alat pemetaan konsep yang ada menggunakan MetaMap dan sumber data ULMS Metathesaurus.
{"title":"SURVEY MODEL-MODEL PENCARIAN INFORMASI REKAM MEDIK ELEKTRONIK","authors":"Muhammad Mustakim, Retantyo Wardoyo","doi":"10.14421/JISKA.2019.33-01","DOIUrl":"https://doi.org/10.14421/JISKA.2019.33-01","url":null,"abstract":"Pertumbuhan jumlah data rekam medik yang pesat, menjadi masalah tersediri yang harus diantisipasi. Untuk menangani fenomena information overload dalam informasi rekam medis, perlu studi yang mendalam untuk dapat mengembangkan model filtering informasi rekam medik yang secara efektif mendukung peningkatan kualitas rekomendasi proses pencarian informasi. Berbagai penelitian terkait pencarian informasi medis telah banyak dilakukan, diantaranya mengembangkan penelitian dengan konsentrasi pada kebaruan dan keberagaman, menggunakan fuzzy ontology, berbasis factor tensor, memepertimbangkan niatan/intention pengguna ketika melakukan pencarian serta pendekatan dengan menggabungkan pencarian berbasis frasa dengan alat pemetaan konsep yang ada menggunakan MetaMap dan sumber data ULMS Metathesaurus.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45251584","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 : 2019-06-11DOI: 10.14421/JISKA.2018.32-03
Y. Kurniawan, Farida Angguntina
An economy that tends to be unstable causes many people to make loans at banks and cooperatives to meet their increasing daily needs. But there are some people who cannot return the loan in a timely manner. These problems can be created or developed by an application that is used to predict whether the people who apply for loans can return loans smoothly, smoothly and stall. Use of attributes such as gender, age, type of work, number of loans, term of return, collateral and income and use the K-Nearest Neighbor algorithm to make predictions. From the research results obtained in the form of accuracy value of 80%, recall of 91% and preciison of 85%. Thus this application can be used to help the pinjman savings cooperative in considering prospective savings and loan credit members who deserve a capital loan. Keywords: data mining, K Nearest Neighbor, cooperatives, savings and loans.
{"title":"APLIKASI PREDIKSI KELAYAKAN CALON ANGGOTA KREDIT PADA KSPPS BMT ARTA JIWA MANDIRI WONOGIRI MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR","authors":"Y. Kurniawan, Farida Angguntina","doi":"10.14421/JISKA.2018.32-03","DOIUrl":"https://doi.org/10.14421/JISKA.2018.32-03","url":null,"abstract":"An economy that tends to be unstable causes many people to make loans at banks and cooperatives to meet their increasing daily needs. But there are some people who cannot return the loan in a timely manner. These problems can be created or developed by an application that is used to predict whether the people who apply for loans can return loans smoothly, smoothly and stall. Use of attributes such as gender, age, type of work, number of loans, term of return, collateral and income and use the K-Nearest Neighbor algorithm to make predictions. From the research results obtained in the form of accuracy value of 80%, recall of 91% and preciison of 85%. Thus this application can be used to help the pinjman savings cooperative in considering prospective savings and loan credit members who deserve a capital loan. Keywords: data mining, K Nearest Neighbor, cooperatives, savings and loans.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49101464","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 : 2019-06-11DOI: 10.14421/JISKA.2018.32-05
Muhammad Habibi
Classification of text with a large amount is needed to extract the information contained in it. Student comments containing suggestions and criticisms about the lecturer and the lecture process on the learning evaluation system are not well classified, resulting in a difficult assessment process. So from that, we need a classification model that can classify comments automatically into classification categories. The method used is the Cosine Similarity method, which is a method for calculating similarities between two objects expressed in two vectors. The data used in this study were 1,630 comment data with several different categories. The test in this study uses k-fold cross-validation with k = 10. The results showed that the percentage accuracy of the classification model was 80.87%.
{"title":"Implementation of Cosine Similarity in an automatic classifier for comments","authors":"Muhammad Habibi","doi":"10.14421/JISKA.2018.32-05","DOIUrl":"https://doi.org/10.14421/JISKA.2018.32-05","url":null,"abstract":"Classification of text with a large amount is needed to extract the information contained in it. Student comments containing suggestions and criticisms about the lecturer and the lecture process on the learning evaluation system are not well classified, resulting in a difficult assessment process. So from that, we need a classification model that can classify comments automatically into classification categories. The method used is the Cosine Similarity method, which is a method for calculating similarities between two objects expressed in two vectors. The data used in this study were 1,630 comment data with several different categories. The test in this study uses k-fold cross-validation with k = 10. The results showed that the percentage accuracy of the classification model was 80.87%.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48926924","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 : 2019-06-11DOI: 10.14421/JISKA.2018.32-06
A. S. Sinaga
Giving the best employee nicknames to spur other employees competing to provide the best, especially service to customers. Many things affect productivity and quality and comfort in the working environment. Then there needs to be clear and objective criteria in determining the best employees, not just based on qualitative values. In order to award the right target, the method for decision support systems can be applied in determining the best employees. The Analytical Hearachy Process (AHP) method requires criteria in making a decision so that the best employees can be chosen more quickly and objectively. There are 4 criteria: Attitude, Attendance, Performance and Work Period. of the 4 alternatives (4 employees) obtained by SRI RAHAYU: 0.419 or 41.9%, most deserve to be the best employee.
{"title":"Sistem Pendukung Keputusan Menentukan Karyawan Terbaik Dengan Metode AHP","authors":"A. S. Sinaga","doi":"10.14421/JISKA.2018.32-06","DOIUrl":"https://doi.org/10.14421/JISKA.2018.32-06","url":null,"abstract":"Giving the best employee nicknames to spur other employees competing to provide the best, especially service to customers. Many things affect productivity and quality and comfort in the working environment. Then there needs to be clear and objective criteria in determining the best employees, not just based on qualitative values. In order to award the right target, the method for decision support systems can be applied in determining the best employees. The Analytical Hearachy Process (AHP) method requires criteria in making a decision so that the best employees can be chosen more quickly and objectively. There are 4 criteria: Attitude, Attendance, Performance and Work Period. of the 4 alternatives (4 employees) obtained by SRI RAHAYU: 0.419 or 41.9%, most deserve to be the best employee.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44667169","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 : 2019-06-11DOI: 10.14421/JISKA.2018.32-02
Cataryana Lenny Dwi Rizka, F. Dewi, S. Wicaksono
Penelitian ini dilakukan agar mengetahui ukuran kemajuan teknologi website LinkedIn yang merupakan salah satu jejaring sosial untuk kepentingan korporasi. LinkedIn merupakan tempat bagi sarjana untuk menemukan pekerjaan terbaik sesuai pendidikan yang telah ditekuni. Dalam penelitian ini digunakan teori dari Allan Albrecht yang tetap dikembangkan oleh International Function Point User Goup (IFPUG) dan akan menggunakan metode pengukuran terkenal yaitu Function Point Analysis (FPA) sebagai cara untuk menghitung serta memperkirakan hasil pengukuran dari website LinkedIn. Pengukuran ini dilakukan sebagai bentuk partisipasi pengembangan pada website LinkedIn yang merupakan sebuah website besar dan sangat banyak diminati oleh pengguna internet. Di hasil akhir penelitian diharapkan dapat mengetahui angka kemudahan akses pemakaian website LinkedIn terhadap pengguna dengan menggunakan rumus Crude Function Points (CFP), mengetahui bagaimana dan seberapa besar kompleksitas dari website LinkedIn dengan menggunakan rumus Relative Complexity Adjustment Factor (RCAF), yang kemudian hasil dari perhitungan rumus CFP dan RCAF akan langsung diimplementasikan pada rumus pengukuran FPA.
{"title":"PENGUKURAN DAN KUALITAS PERANGKAT LUNAK WEBSITE “LINKEDIN” MENGGUNAKAN METODE FUNCTION POINT ANALYSIS","authors":"Cataryana Lenny Dwi Rizka, F. Dewi, S. Wicaksono","doi":"10.14421/JISKA.2018.32-02","DOIUrl":"https://doi.org/10.14421/JISKA.2018.32-02","url":null,"abstract":"Penelitian ini dilakukan agar mengetahui ukuran kemajuan teknologi website LinkedIn yang merupakan salah satu jejaring sosial untuk kepentingan korporasi. LinkedIn merupakan tempat bagi sarjana untuk menemukan pekerjaan terbaik sesuai pendidikan yang telah ditekuni. Dalam penelitian ini digunakan teori dari Allan Albrecht yang tetap dikembangkan oleh International Function Point User Goup (IFPUG) dan akan menggunakan metode pengukuran terkenal yaitu Function Point Analysis (FPA) sebagai cara untuk menghitung serta memperkirakan hasil pengukuran dari website LinkedIn. Pengukuran ini dilakukan sebagai bentuk partisipasi pengembangan pada website LinkedIn yang merupakan sebuah website besar dan sangat banyak diminati oleh pengguna internet. Di hasil akhir penelitian diharapkan dapat mengetahui angka kemudahan akses pemakaian website LinkedIn terhadap pengguna dengan menggunakan rumus Crude Function Points (CFP), mengetahui bagaimana dan seberapa besar kompleksitas dari website LinkedIn dengan menggunakan rumus Relative Complexity Adjustment Factor (RCAF), yang kemudian hasil dari perhitungan rumus CFP dan RCAF akan langsung diimplementasikan pada rumus pengukuran FPA.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45834803","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 : 2019-06-11DOI: 10.14421/JISKA.2018.32-01
Dadang Iskandar
Budidaya jamur mempunyai kesulitan tersendiri yaitu harus menjaga suhu dan kelembaban pada rentang tertentu. Ruang hidup ideal bagi pertumbuhan jamur yaitu pada suhu 28-30 derajat Celcius dan kelembaban berkisan 80 – 90 %. Untuk menjaga dalam kondisi ideal diperlukan suatu peralatan yang bias memonitor suhu dan kelembaban ruang serta mengkondisikan supaya terus terjaga pada kondisi ideal.Sistem otomatisasi kumbung berfungsi untuk menjaga kondisi kumbung selalu berada pada kondisi ideal. Untuk membaca kondisi ruang menggunakan sensor kelembaban dan dikendalikan oleh raspberry Pi yang menggerakan actuator berupa pompa kabut.
{"title":"Sistem Otomatisasi Kumbung Jamur Berbasis Raspberry PI","authors":"Dadang Iskandar","doi":"10.14421/JISKA.2018.32-01","DOIUrl":"https://doi.org/10.14421/JISKA.2018.32-01","url":null,"abstract":"Budidaya jamur mempunyai kesulitan tersendiri yaitu harus menjaga suhu dan kelembaban pada rentang tertentu. Ruang hidup ideal bagi pertumbuhan jamur yaitu pada suhu 28-30 derajat Celcius dan kelembaban berkisan 80 – 90 %. Untuk menjaga dalam kondisi ideal diperlukan suatu peralatan yang bias memonitor suhu dan kelembaban ruang serta mengkondisikan supaya terus terjaga pada kondisi ideal.Sistem otomatisasi kumbung berfungsi untuk menjaga kondisi kumbung selalu berada pada kondisi ideal. Untuk membaca kondisi ruang menggunakan sensor kelembaban dan dikendalikan oleh raspberry Pi yang menggerakan actuator berupa pompa kabut.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47742815","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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