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INDONESIA
Jurnal Komputasi
Published by Universitas Lampung
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Lingkup dan fokus jurnal berkaitan dengan tema-tema computer science, information technology, information system, software engineering, data mining, artificial intelligence, networking, multimedia, database, dan operating system
Arjuna Subject : -
Articles 10 Documents
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Search results for , issue "Vol 8, No 2 (2020)" : 10 Documents clear
Web Engineering Sistem Informasi Pelayanan Pengaduan Online Pada P2TP2A Provinsi Lampung suaidah suaidah
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2611

Abstract

P2TP2A adalah lembaga yang menyediakan pelayanan perlindungan perempuan dan anak seperti KDRT, penganiayaan, kekerasan seksual anak dll. Mekanisme pengaduan dilakukan dengan cara masyarakat datang langsung, menghubungi melalui telpon dan bisa diwakili oleh keluarga. Kendala pertama yang didapat pada saat proses pelaporan ialah bila korban tidak berani datang langsung serta merahasiakan alamatnya, dengan begitu pihak P2TP2A akan mengalami kesulitan untuk melakukan survei, edukasi dan pelayanan langsung dengan korban. Kendala kedua terputusnya akses komunikasi dan sering terjadi korban tidak mencantumkan nomor telpon pada saat melapor. Kendala ketiga ialah masyakarat mengeluhkan karna jarak tempuh dari rumah ke P2TP2A yang cukup jauh sehingga membutuhkan dana dan transportasi untuk datang ke P2TP2A. Kendala lainnya pihak P2TP2A belum memiliki simfoni data (Sistem Informasi Online) yang dapat mendata pendaftaran korban, pelaporan pengaduan masyakarat dan proses pelayanan, sehingga belum mampu meningkatkan produktivitas di mata publik.Tujuan dari penelitian ini adalah menjangkau semua aspek pelayanan publik, yaitu membantu masyarakat menyampaikan pengaduan, pengelolaan informasi, pelayanan konsultasi, dan penguluhan kepada masyarakat menggunakan web engineering. Tahapan metode penelitian yang dilakukan dengan analisis kejadian, pengumpulan data, tinjauan pustaka, studi literatur, merancang, implementasi, pengujian, analisis hasil prototype dan pembuatan buku panduan aplikasi. Hasil dari penelitian ini diharapkan sistem yang berjalan dapat terintegrasi dengan baik dan terpusat menjadi satu, membantu pihak P2TP2A untuk melayani pengaduan-pengaduan dari masyarakat secara online dengan mudah, cepat dan kapan saja
Implementasi Metode Ekstraksi Fitur Gabor Filter dan Probablity Neural Network (PNN) untuk Identifikasi Kain Tapis Lampung SYARIF, ADMI; TANJUNG, AKBAR RISMAWAN; ANDRIAN, RICO; LUMBANRAJA, FAVORISEN R.
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2641

Abstract

Tapis Fabric is a traditional clothing of the people of Lampung in the form of a shawl cloth or a sarong made of woven cotton thread with various motifs and ornaments, silver thread or gold thread by embroidered or punched. The pattern of filter cloth is quite complex, unlike the pattern of fabric in general, with its own uniqueness that has become the culture of Lampung society until now. This filter cloth will be investigated by identifying the three types of filter cloth, namely Sasab, Bintang Perak and Gunung Beradu and see the results of its identification. The method used to identify is by combining the Gabor Filter feature extraction method which has frequency and orientation parameters and Probability Neural Network classification methods. Previously, the combination of these two methods was used to identify objects with simple patterns. The results are quite good, such as detecting faces, leaf patterns, and other simple patterns. This research is expected to get maximum identification results on the filter cloth even though it has a pattern that is not simple and will be used as a research report to determine the suitability of the method used for the filter object.
Pendeteksian Sarkasme pada Proses Analisis Sentimen Menggunakan Random Forest Classifier Debby Alita; Auliya Rahman Isnain
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2615

Abstract

Kalimat sindiran atau sarkasme masih sering digunakan oleh kalangan publik untuk mengungkapkan maksud isi hati dan pikiran baik itu yang disampaikan secara langsng maupun tidak langsung. Sarkasme dilakukan untuk menyindir dan menyakiti hati seseorang dengan menggunakan bahasa atau kata yang didalamnya mengandung kata positif tetapi maknanya negatif sehingga sering sekali terjadi opini salah diklasifikasikan. Penelitian ini melakukan kombinasi antara proses sentimen analisis dengan deteksi sarkasme untuk pengklasifikasian opini yang terdapat pada Twitter. Proses analisis sentimen dilakukan dengan tahapan preprocessing dan ekstraksi fitur dan diklasifikan dengan menggunakan metode Support Vector Machine dilanjutkan dengan proses pendeteksian sarkasme yang dilakukan tahapan ekstraksi fitur dengan 4 set fitur yaitu sentiment related, punctuation-relate, lexical and syntactic, dan pattern-relate dan diklasifikasikan dengan menggunakan metode Random Forest Classifier. Hasil penelitian ini didapatkan peningkatan nilai rata-rata akurasi sebesar 16,61 %, nilai presisi sebesar 5,45 %, nilai recall sebesar 9,64% dan kenaikan nilai F1score sebesar 11,27% dengan jumlah data sebanyak 2.027 dengan rincian data dengan label positif berjumlah 1023, data dengan label negatif berjumlah 587 dan data dengan label netral berjumlah 462. Data sarkasme didapatkan dari tweet dengan label positif yang kemudian diberikan label sarkasme atau tidak sarkasme dan didapat hasil label dengan jumlah keseluruhan berlabel sarkasme berjumlah 354 dan tidak sarkasme berjumlah 669.
Efek Peningkatan Jumlah Paralel Korpus Pada Penerjemahan Kalimat Bahasa Indonesia ke Bahasa Lampung Dialek Api Permata Permata; Zaenal Abidin; Farida Ariyani
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2613

Abstract

Experimental observations of the effect of the number of parallel corpus on Indonesian translation into the Lampung dialect api were carried out using the statistical machine translation (SMT) method. SMT utilizes a parallel Indonesian corpus and its translation in the Lampung dialect api as a material for training data. The research strategy was carried out in three ways, namely first strategy with a corpus parallel number of 1000 sentences, the second strategy with a corpus parallel number of 2000 and the third strategy with a corpus parallel number of 3000 sentences. The research starts from the preprocessing phase followed by the training phase, namely the parallel corpus processing phase to obtain a language model and translation model. Then the testing phase, and ends with the evaluation phase. SMT testing uses 25 single sentences without out-of-vocabulary (OOV), 25 single sentences with OOV, 25 compound sentences without OOV and 25 compound sentences with OOV. The test results of translating Indonesian sentences intoLampung dialectic api are shown through the accuracy value of Bilingual Evaluation Undestudy (BLEU) obtained in testing 25 single sentences without out-of-vocabulary (OOV) in the first strategy, the second and the third are 21.49%, 59.58% and 73.21%. In testing 25 single sentences with out-of-vocabulary (OOV) obtained in the first strategy, the second and the third are 23.22%, 44.33% and 68.72%. In testing 25 compound sentences without out-of-vocabulary(OOV) obtained in the first strategy, the second and the third are 18.22%, 39.4% and 69.18%. In testing 25 compound sentences with out-of-vocabulary (OOV) obtained in the first strategy, the second and the third are 25.94%, 28.22% and 71.94%.
PENGEMBANGAN E-RAPORT KURIKULUM 2013 BERBASIS WEB PADA SMA TUNAS MEKAR INDONESIA Ajeng Savitri Puspaningrum; Neneng Neneng; Intan Saputri; Fenty Ariany
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2692

Abstract

SMA Tunas Mekar Indonesia is one of  Lampung Province schools that uses the 2013 curriculum. The assessment reporting process of student learning skills and achievement by teachers uses report cards that are distributed to parents at the end of each semester. In the managing the report card data process, there are several obstacles, namely the obstruction of grade recapitulation because the subject teacher is late in sending student grades, it takes a long time in managing grades because the processing value data done repeatedly from the attendance recap report then the application of Microsoft Excel and the report books are recapitulated by staff allows data writing errors. The solution developed for this problem is to build a Web-Based E-Report Card Application that will help SMA Tunas Mekar Indonesia by simplifying and accelerating teachers and homeroom teachers in assessing student learning outcomes reports process on inputting student scores. In this application, teachers and homeroom teachers no longer need to send assessment data via email, because the data entered is already integrated with other data. So that it doesn't take a long time to enter student grades, and minimize the damage and loss of report card data. The application built has provided complete information regarding student report card information and helps schools in reporting student grades based on the testing results using ISO 25010 standart with a percentage of success with a total average of 92.82%.
Aplikasi Monitoring Penderita Kardiovaskular dan Obesitas Berbasis Mobile Internet of Things (MIoT) Muhamad Bahrul Ulum; Nizirwan Anwar; Riya Widayanti; Alivia Yulfitri; Hendra Bratanata
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2648

Abstract

According to the World Health Organization (WHO), coronary heart disease is the biggest cause of death in Indonesia. In 2016, the death rate from heart disease was 122 people per 100,000 population. This figure is higher than other causes, such as stroke, tuberculosis, and diabetes. The number is increasing every year due to changes in lifestyle of Indonesian people who like to eat high-fat foods and lifestyle factors that affect the risk of cardiovascular disease, including lack of physical activity, smoking, unhealthy diet, and alcohol consumption habits. This study aims to monitor the heart rate of cardiovascular sufferers with the mobile internet of things (MIoT) approach. Using the ESP8266 Wifi module for communication to the database server and heart rate sensor to detect heart rate then convert it to Bit per Minute (BPM). Every patient with cardiovascular disease can be monitored using a sensor connected to a smartphone to record any changes that occur. The research method consists of several stages, namely: Prepare, Plan, Design, Implement, Operate and Optimize (PPDIOO). The results obtained in the form of a aplication heart rate monitoring for patients with cardiovascular for healthcare services.
Penerapan Algoritma C4.5 Untuk Prediksi Churn Rate Pengguna Jasa Telekomunikasi Yohana Tri Utami; Dewi Asiah Shofiana; Yunda Heningtyas
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2647

Abstract

Telecommunication industries are experiencing substantial problems related to the migration of customers due to a large number of competing companies, dynamic circumstances, as well as the presence of many innovative and attractive offerings. The situation has resulted in a high level of customer migration, affecting a decrement toward the company revenue. Regarding that condition, the customer churn is one well-know approach that can help in increasing the company's revenue and reputation. As to predict the reason behind the migration of customer, this study proposed a data mining classification technique by applying the C4.5 algorithm. Patterns generated by the model were implemented using 10-fold cross-validation, resulting in a model with an accuracy rate of 87%, precision 87.5%, and a recall of 97%. Based on the good performance quality of the model, it can be stated that the C4.5 algorithm succeeded to discover several causes from the migration of telecommunication users, in which price holds the top place as the primary reason
ANALISA KOMPUTASI PARALEL MENGURUTKAN DATA DENGAN METODE RADIX DAN SELECTION Favorisen R. Lumbanraja; Aristoteles Aristoteles; Nadila Rizqi Muttaqina
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2662

Abstract

Increasing computing power is now achieved by replacing the programming paradigm with parallel programming. Parallel computing is a method of solving problems by dividing the computational load into small parts of the computation sub-process. This study describes the comparative analysis of parallel computations in the Selection Sort and Radix Sort algorithms. The data used are in the form of whole numbers and decimal numbers totaling 100 to 2 million data. The test was carried out with three scenarios, namely using two processors, four processors, and 3 computers connected to each other via a LAN network. The results showed that the parallel Selection Sort algorithm for small data was better than the parallel Radix Sort. On the other hand, parallel Radix Sort is better for millions of data than Selection Sort.
Metrics Based Feature Selection for Software Defect Prediction Radityo Adi Nugroho; Friska Abadi; M. Reza Faisal; Rudy Herteno; Rahmat Ramadhani
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2670

Abstract

Nowadays, software is very influential on various sectors of life, both to solve business needs, as well as personal needs. To have a Software with high quality, testing is needed to avoid software defect. Research on software defects involving Machine Learning is currently being carried out by many researchers. This method contains one important step, which is called feature selection. In this study, researchers conducted a feature selection based on the software metric category to determine the level of accuracy of the prediction of software defects by utilizing 13 (thirteen) datasets from NASA MDP namely CM1, JM1, KC1, KC3, KC4, MC1, MC2, MW1, PC1, PC2, PC3, PC4, and PC5. To classify, the researchers involved 5 (five) classifiers, namely Naive Bayes, Decision Trees, Random Forests, K-Nearest Neighbor, and Support Vector Machines. The research result shows that each attribure on software metric categories has effect on each dataset. Naive Bayes Algorithm and Random Forest Algorithm can give better performance than other algorithm in classifieng software defect with feature selection based on metrics. On the other hand, the best metrics category on each classifier algorithm is metric Misc. From average AUC value, it can be concluded that metrics category which can give best performance is metric LoC, followed by metric Misc. Both categories have achieved highest AUC value in Random Forest classifier.
Dampak dari Parameter Variasi Koneksi, Node dan Kecepatan Node Terhadap Delay pada Routing Protocol AODV dan BATMAN Jaringan MANET Dodon Turianto Nugrahadi; M Reza Faisal; Liling Triyasmono; Muhammad Janawi
Jurnal Komputasi Vol 8, No 2 (2020)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i2.2675

Abstract

Mobile ad-hoc Network (MANET) is a multihop wireless network that a many collection of mobile nodes that are dynamic. MANET each node on the network have the same position, so it needs the appropriate routing protocol, to support the exchange of data to be optimal. In this study, the routing protocol to be tested is AODV and BATMAN based scenario increasing the number of connections, nodes and speed. Simulation parameter scenarios is number connection 1 UDP, 2 UDP, 3 UDP, and number of node 25 node, 50 node, 100 node, and then number node speed 20 m/s, 50 m/s. in this AODV routing protocol will establish a rute from the source node to the destination only if there is a request from the source node. BATMAN routing protocols, all decisions and information disseminated throughout the node and will regularly update on each node. The performance parameters to be measured such as delay by using OMNET ++ 4.6. Output of simulation will analysis with two way anova and multivariate to know correlation between variation scenario impact to delay. The results obtained in this study AODV and BATMAN have their respective advantages, analisys with two-way anova show that both AODV and BATMAN get the impact of the scenario from incrising the number of connections, the number of nodes and the number of nodes speed with a p-value of 0.012212 (<0.05) with two-way anova. From all scenarios, the number of UDP connections has the greatest impact, from UDP 1, UDP 2 and UDP 3. Followed by the number of speed 50 and node 100. So it can be concluded that the connection has an effect on increasing delay. The increasing number of speed and nodes can contribute to an increase in delay if number of nodes above 100 and speed above 50. With multivariate analysis, the BATMAN protocol had the most impact on the delay under the scenario then AODV.

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