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Developing Assessment Instrument of Data, Technology, and Human Literacy in Physics Learning Dewi, Candra; Rusilowati, Ani; Fianti, Fianti
Journal of Research and Educational Research Evaluation Vol 8 No 2 (2019)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.35 KB) | DOI: 10.15294/jere.v8i2.38370

Abstract

This study aims to determine validity of the assessment instrument data, technology, and human literacy in physics learning. The research method uses research and development (RnD) with modified 4-D model until development stage. Instrument of validation was assessed by 6 validators. The instrument was tested by 36 students of class X SMK Texmaco Semarang. The form of instruments is multiple choice test with 21 item to measure the cognitive domain. Data analysis in this research are tests of content validity, reliability, internal consistency, discrimination power, and level of difficulty. The results of the content validity by using Aiken’s coefficient get an average score 0.84 with a valid category at significance level of 0.05. Cronbach’s Alpha and ICC values from reliability test are 0.77 and 0.806 with reliable categories. The results of internal consistency showed that 80.95% items had a good internal consistency. There are 4 items with category not used from the discrimination power test. Furthermore from the results of the difficulty level, 7 items are easy, 13 items are medium, and 1 item is difficult. Based on results of the instrument analysis can be concluded that the instrument developed were valid and reliabel then can be used to measure ability of data, technology, and humans literacy in physics learning.
Peramalan Jumlah Kunjungan Wisatawan Kota Batu Menggunakan Metode Time Invariant Fuzzy Time Series Aria Bayu Elfajar; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 2 (2017): Februari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Forecasting systems with fuzzy time series capturing the pattern of past data and then use it to project future data. The process also does not require a complex learning system as it exists on genetic algorithms and neural networks, so that make the system is easy to develop. In the prediction using fuzzy time series, the length of the interval has been determined at the beginning of the calculation process. While determining the interval length is very influential in the formation of fuzzy relationships also will have an impact on the prediction of the outcome differences. Therefore, the formation of the fuzzy relationship must be precise and it requires the determination of an appropriate interval length. One method that can be used to determine the effective length of the interval is an average based method. In this paper, the authors implement the fuzzy time series to forecast the monthly visitor data, as for the data used for testing is derived from Dinas Pariwisata Kota Batu and from the results of tests conducted that data forecasting using Average based earned value error AFER best of 0.0056% by using 60 training data
Implementasi Jaringan Syaraf Tiruan Backpropagation untuk Mendiagnosis Penyakit Kulit pada Anak Rokky Septian Suhartanto; Candra Dewi; Lailil Muflikah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 7 (2017): Juli 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Immune systems owned by children who are weaker than adults make children more susceptible to disease. Skin disease is one of them, this is because the skin is the sense of touch for humans. The similarity of symptoms of any skin disease makes the layman difficult to distinguish the illness in suffering whereas every type of disease has a different treatment. In this study implements artificial neural network method backpropagation to study the past data in order to diagnose skin diseases in children. The input used in the form of symptoms of all diseases amounted to 19 then represented into binary 0 and 1 where the value will be worth 1 if experiencing the symptoms and vice versa. The activation function used is sigmoid binner. The initial weights are obtained using Nguyen-Widrow which will then be done by repeatedly learning so that the result of the network that gives the correct response to the input. Based on the result of the test, the optimal parameters are 4 hidden neurons, learning rate 0.4 and epoch maximum 300000 and The results of the accuracy of the study reached 87.22% which indicates that this backpropagation method can be used in diagnosing skin diseases in children.
Optimasi Komposisi Pakan Untuk Penggemukan Sapi Potong Menggunakan Algoritma Genetika Muhammad Noor Taufiq; Candra Dewi; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 7 (2017): Juli 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the problems that exist in Indonesia is not share of the number between the demand for beef cattle with the number of local beef cattle production. This caused by the increase in the number of people in Indonesia. It makes Indonesia have large enough dependencies to import cows from abroad to fulfill the need of Indonesian people. This study tries to implement the genetic algorithm to creating a qualified mixed ration at the reasonable cost. This study is expected to be able to increase the number of local beef cattle production to fulfill the need of Indonesian people. The representation used in this study is real code in which each chromosome initialize feed materials which used. The mutation method is the random mutation, and the selection method is elitism. The result of this study found the optimal parameter at 900 population, 800 generation and the combination of cr and mr as many as 0.9 and 0 with the highest fitness is 0,6266. The result obtained in the form of ration composition recommendation at minimal cost as daily based of the nutritional need of beef cattle
Implementasi Metode K-Medoids Clustering Untuk Pengelompokan Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas (Hotspot) Dyang Falila Pramesti; Muhammad Tanzil Furqon; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Forest / land wildfire is one of the disasters that occur every year in some countries in the world. This incident got more attention from the government because it caused many losses both in the economic, ecological, and social. Indonesia is a country with a high rate of forest / land wildfire disasters. Indonesia suffered losses of up to Rp 209 trillion by 2015. As a result of losses incurred an early prevention is needed, which one can be done by grouping areas with potential forest fires by utilizing hotspot data. Forest wildfires are marked by the detection of fire spots by satellites indicated as hot spots. This research uses hotspot data with parameter of latitude, longitude, brightness, frp (fire radiative power), and confidence by using K-Medoids method. K-Medoids method is a clustering method that serves to split the dataset into groups. The advantages of this method is able to resolve the weakness of K-Means method that is sensitive to outlier. The result of this research shows that the use of K-Medoids method can be used for the process of hot spot data clustering with the best silhouette coefficient in amount of 0.56745 on the use of 2 clusters by using 7352 data. The results of the clustering analysis showed that using 2 clusters resulted in a group of data with the potential of high potential with an average brightness of 344.470K with average confidence of 87.18% and medium potential with average brightness of 318.800K with Average confidence of 58.73%.
Optimasi Penjadwalan Damping Mahasiswa Difabel Menggunakan Algoritma Genetika (Studi Kasus PSLD Universitas Brawijaya) Mukh. Mart Hans Luber; Imam Cholissodin; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Mentoring scheduling for Disabled student is the preparation schedule implementation to a companion who served in the division of working time. On the good scheduling process then will maximize service to disabled students. This scheduling problem is difficult because the number of accompanying relative limited compared to the number of disabled students. The schedule created by the workload evenly to each escort. In this study applied the concepts of problem solving scheduling by using genetic algorithms. Application of genetic algorithm to find the optimal solution. In the settlement of this problem use an integer representation with the length of chromosome 45 genes that each section of the gene showed code mentoring. The method used is the crossover one-cut method of point mutation process, using the method of reciprocal exchange and mutation on the selection process using the method of elitism selection. From the results of testing that has been done optimal parameters obtained using a 100 generation with fitness value 0.966. The final results obtained in the form of a mentoring schedule for 5 days.
Penggunaan Ciri Geometric Invariant Moment pada Pengenalan Tanda Tangan Rahma Juwita Sany; Agus Wahyu Widodo; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Signature as a personal attribute is one of the person's identity verification equipment that is accepted widely by the society. The process of signature recognition starts from starts from preprocessing, which consist of filtering, thresholding, thinning, cropping and resizing. After preprocessing continued by feature extraction process using Geometric Invariant Moment to get the value of a feature that will be used for the classification process using K-Nearest Neighbour. The variations Geometric Invariant Moment feature that has the smallest of FAR value and FRR value on each data source are different. For data from Indonesia the smallest FAR obtained while using moment 7 with value is 7% and the smallest FRR obtained while combining moment 1,2,3,6 and 7 and using all of the moment with each value is 61.5%. For data from Spain the smallest FAR obtained while combining moment 3,4,5 and 7, moment 1,3,4,5 and 7 and combining 1,3,4,5,6 and 7 with each value is 7% and the smallest FRR obtained while combining moment 2,3,4,5,6 and 7 and using all of the moment with each value is 72%. For data from Persia the smallest FAR obtained while combining moment 3 and 5 and combining moment 3,5 and 6 with each value is 9.5% and the the smallest FRR obtained while combining moment 1,2,3,4,6 and 7 with value is 37%. The testing results of FAR and FRR is inversely proportional. The system can recoginize the fake signatures well that proven by getting FAR value is relatively small on all of data sources. But the system can't recognize the original signatures well that proven by getting the high FRR value on all data sources. Features of Geometric Invariant Moment that applied globally on an image don't provide high accuracy. Perhaps, it happened because when apply global feature, the local features can't recognize properly. It occurs on the original signature image, while the application of the features of Geometric Invariant globally on the fake signature image provide high accuracy.
Implementasi Metode Fuzzy - AHP Menggunakan Optimasi Particle Swarm Optimization (PSO) untuk Rekomendasi Pemilihan Tanaman Pomologi Maulana Putra Pambudi; Imam Cholissodin; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Pomology (fruit) is one of the most popular commodities in Indonesia. But, in indonesia fruit production rate is not bigger than fruit consumption rate. Lack of fruit production in Indonesia can be caused by various factor. One of the factor is production failure that caused by wrong fruit choice. That factor can happen because lack of farmer knowledge about compatibility between land and fruit. Therefore it takes a program that can used to help farmer check if their land is compatible with one kind of fruit or not. FAHP-PSO is a one of the method that can solve a problem with many determining factor inside it. This method is a combination of 2 previous method. That 2 previous method is Fuzzy-AHP and Particle Swarm Optimization (PSO). Particle Swarm Optimization method will be working to optimize criteria weight ratio that should be generated from AHP. From the test result, Spearman coefficient for comparing rank result in 3 land and 10 fruit is 0.8598. beside that from the classification result we can obtained Spearman coefficient is 0.9659.
Prediksi Nilai Tukar Rupiah Indonesia Terhadap Dolar Amerika Serikat Menggunakan Metode Recurrent Extreme Learning Machine Neural Network Daneswara Jauhari; Imam Cholissodin; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The exchange rate of money by some people who are involved in the economy, especially the inter-state economy is very payed, often influencing one's decision in taking a policy. However, the exchange rate is a very unstable value, has a lot of noise and fluctuation, it is very difficult to predict the exchange rate. Research on exchange rate prediction has become the most challenging research among researchers, and that is considered one of the most important areas of research in international finance. Therefore, an application is needed, which can better predict the exchange rate of Indonesian Rupiah against the US Dollar. In this study the authors use the method of Recurrent Extreme Learning Machine Neural Network (RELMNN), the method can handle time-ordered datasets and can improve the ability of the Extreme Learning Machine (ELM) method in training and adapting. After testing with optimum parameters, and compared with ELM method, we found out that RELMNN method is superior to ELM method with Mean Absolute Percentage Error (MAPE) value of 0.069502%, while ELM method get MAPE 0.090423%.
Peramalan Suku Bunga Acuan (BI Rate) Menggunakan Metode Fuzzy Time Series dengan Percentage Change Sebagai Universe of Discourse Wiratama Paramasatya; Dian Eka Ratnawati; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

BI rate is the interest rate policy that reflects the monetary stance policy which set by the Central Bank of Indonesia and announced to the public. BI rate greatly affects the trade, industry, stock prices, and especially banking. If the policy rate set by the Board of Governors is not in accordance with the trend of economic conditions at a certain time it will have a negative impact on the economic condition of Indonesia. This is what causes the importance of BI rate forecasting in the hope that business players can anticipate the long-term impact of BI rate determination. This research implements fuzzy time series using percentage change as the universe of discourse to predict BI rate in certain period. This method focuses on forming the universe of discourse and the development of steps to form an interval. Based on the results of the tests that have been done, using the best variable values ​​are 12 as the initial interval length, 2 as the value of n-topFrequency 2, and 10 as the length of sub-interval produce MAPE of 0.09005%. The final result obtained is the result of BI rate forecasting according to the period that the user wants to forecast.
Co-Authors Abdul Fatih Achmad Yusuf Adam Sulthoni Akbar Adinugroho, Sigit Aditya Chandra Nurhakim Aditya Septadaya Adiyasa, Bhisma Afrialdy, Firman Aghata Agung Dwi Kusuma Wibowo Agi Putra Kharisma Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmada Bastomi Wijaya Akmal Subakti Wicaksana Alan Primandana Almasyhur, Muhammad Bin Djafar Amalia Luhung Amita Tri Prasasti, Pinkan Anang Tri Wiratno Andhika Satria Pria Anugerah Anggita Mahardika Ani Budi Astuti Ani Rusilowati Anim Rofi'ah Annisa Puspitawuri Annisa Salamah Rahmadhani Aprianto, Anda Bagas Arbawa, Yoke Kusuma Aria Bayu Elfajar Arief Andy Soebroto Arjunani, Rusmalistia Intan Ayuri Alfarianti Azhari, Muhammad Rizqi Azizul Hanifah Hadi Barik Kresna Amijaya Bayu Rahayudi Brillian Aristyo Rahadian Budi Astuti Budi Darma Setiawan Chelsa Farah Virkhansa Daneswara Jauhari Daneswara Jauhari, Daneswara Dany Primanita Kartikasari Dennes Nur Dwi Iriantoro Deo Hernando Desy Wulandari Dewanti, Amalya Trisuci Diajeng Tania Ananda Paramitha Dian Eka Ratnawati Dloifur Rohman Alghifari Dwi Fitriani Dwi Novi Setiawan Dwi, Endah Dyang Falila Pramesti Edo Ergi Prayogo Edy Santoso Edy Santoso Erik Aditia Ismaya Eriq Muh. Adams Jonemaro Falih Gozi Febrinanto Faris Febrianto Febri Ramadhani Fenori, Muhammad Dajuma Feri Angga Saputra Fianti Fianti, Fianti Fitri Anggarsari Fitriana, Rosita Nur Fitriani , Dwi Fitriani, Delvi Guntur Syafiqi Adidarmawan Hartami, Edina Himawan, Alfian Iftinan, Salsa Nabila Ikhwanul Kiram, Muh Zaqi Ilham Harazki Imam Cholisoddin Imam Cholissodin Imam Cholissodin Indah Lestari, Indah Indah Wahyuning Ati Indah, Yuliana Indra Eka Mandriana Indriati Indriati Indriati Indriati Indriati, Indriati - Iqbal Santoso Putra Iskarimah Hidayatin JANAH, NURUL Jumadi Jumadi Khairiyyah Nur Aisyah Kharisma, Agi Krisyanto, Edy Kurnianingtyas, Diva Kurniawan, I Gede Jayadi Kusumawardani, Septyana Dwi Lailil Muflikah Lailil Muflikhah Maharani Tri Hastuti Mardji Mardji Marinda Ika Dewi Sakariana Marinda, Vira Marwa Mudrikatussalamah Maulan, Erika Maulana Putra Pambudi Maulida, Farida Merlya, Merlya Mochammad Tanzil Furqon Mohammad Nuh Mohammad Setya Adi Fauzi Muh Arif Rahman Muhammad Ihsan Diputra Muhammad Misbachul Asrori Muhammad Noor Taufiq Muhammad Prabu Sutomo Muhammad Riduan Indra Hariwijaya Muhammad Tanzil Furqon Muhja Mufidah Afaf Amirah Muhyidin Ubaiddillah Mukh. Mart Hans Luber Nabila Arief Nadia Artha Dewi Naily Zakiyatil Ilahiyah Naniek Kusumawati Nazzun Hanif Ahsani Nirzha Maulidya Ashar Nooriza Fariha Rumagutawan Noval Dini Maulana Novanto Yudistira Nur Hidayat Nur Sa'diyah Nurhidayati Desiani Nurul Faridah, Nurul Nurul Hidayat Nuryatman, Pamelia Nuzula, Nila Firdauzi Pande Made Rai Raditya Phutpitasari, Rosa Devi Pupung Adi Prasetyo Putra Pandu Adikara Putri Aprilia Putu Gede Pakusadewa Rachmalia Dewi Rahma Juwita Sany Randy Cahya Wihandika Rasya, Muhammad Ratih Kartika Dewi Rayhan Tsani Putra Reiza Adi Cahya Reza Wahyu Wardani Rifan, Mohamad Rina Christanti, Rina Rizal Setya Perdana Rizal, Moch. Khabibur Robih Dini Rohmah, Yushinta Lailatul Rohmanurmeta, Fauzatul Ma’rufah Rokky Septian Suhartanto Romlah Tantiati Rosyita, Elyana Santoso, Allegra Santoso, Andri Saputra, Rendi Ramadani Saputro, Rinaldi Eko Saputro Sekar Dwi Ardianti Selle, Nurfatima Selvi Marcellia Setya Perdana, Rizal Sigit Pangestu Siti Nurjanah Siti Nurlaela Sundari, Suci Sunyoto Eko Nugroho, Sunyoto Eko Susenohaji, Susenohaji Sutrisno . Syarif, Adnan Tirana Noor Fatyanosa, Tirana Noor Ulfah Mutmainnah Veni, Silvia Wahyu, Dwi Wayan Firdaus Mahmudy Werdha Wilubertha Himawati, Werdha Wilubertha Wiandono Saputro Wilis Biro Syamhuri Wiratama Paramasatya Yasin, Patbessani Septani Firman Yessica Inggir Febiola Yosua Christopher Sitanggang Yudha Eka Permana Yudistira, Indrajati Yuita Arum Sari Yulia Trianandi Yulian Ekananta Yusi Tyroni Mursityo Zulhan, Galang