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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi dan Sistem Komputer Jurnal Sains dan Informatika Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Jurnal Teknologi dan Riset Terapan (JATRA) Jurnal Anugerah: Jurnal Pengabdian Kepada Masyarakat Bidang Keguruan dan Ilmu Pendidikan Journal of Innovation and Technology TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang
Nola Ritha
Universitas Maritim Raja Ali Haji, Tanjung Pinang, Kepulauan Riau
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

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Prediksi Curah Hujan dengan Menggunakan Algoritma Levenberg-Marquardt dan Backpropagation Ritha, Nola; Bettiza, Martaleli; Dufan, Ariel
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 5 No 2 (2016): Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (501.812 KB) | DOI: 10.31629/sustainable.v5i2.358

Abstract

Salah satu faktor yang mempengaruhi tipe iklim adalah curah hujan. Keakuratan dalam prediksi curah hujan menjadi faktor penting karena dapat digunakan dalam berbagai kepentingan. Data yang digunakan dalam penelitian ini adalah data curah hujan bulanan, suhu, kelembaban udara, kecepatan angin dan tekanan udara dari tahun 2010 sampai dengan 2014 yang diperoleh dari BMKG Tanjungpinang. Penelitian ini dilakukan dengan membandingkan dua buah algoritma yakni Algoritma Levenberg-Marquardt dan Backpropagation dalam memprediksi curah hujan. Hasil penelitian menunjukan pemodelan dengan Algoritma Levenberg Marquardt memberikan hasil terbaik pada pemodelan data dengan jumlah neuron hidden layer 10, Epoch 100, dengan nilai mse sebesar 0.0776. Sedangkan Algoritma Backpropagation jumlah neuron hidden layer 4, Epoch 1.000 dengan nilai mse sebesar 0.07876. Penelitian ini menunjukkan bahwa perbandingan hasil prediksi curah hujan dengan menggunakan Algoritma Levenberg Marquardt menghasilkan prediksi yang lebih baik dibanding dengan Algoritma Backpropagation.
Case Based Reasoning untuk Mendeteksi Kerusakan Harddisk Ritha, Nola; Sutoyo, M Nurtanzis
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 5 No 1 (2016): Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (331.87 KB) | DOI: 10.31629/sustainable.v5i1.361

Abstract

Diperlukan suatu teknologi yang dirancang untuk membantu menyelesaikan penanganan perbaikan perangkat keras komputer khususnys harddisk. Nearest neighbor adalah pendekatan untuk mencari kasus dengan menghitung kedekatan antara kasus baru dengan kasus lama. Harddisk Drive adalah media penyimpanan utama yang digunakan pada computer dengan kapasitas penyimpanan yang sangat tinggi dan bersifat non volatile. Berdasarkan hasil perhitungan, maka dapat disimpulkan bahwa gejala A (Harddisk bad sector) memiliki kedekatan terhadap kasus lama sebesar 0,35.
Prediksi Pasang Surut Air Laut Menggunakan Jaringan Syaraf Tiruan Backpropagation Nikentari, Nerfita; Ritha, Nola; Haryadi, Tri
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 7 No 1 (2018): Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.77 KB) | DOI: 10.31629/sustainable.v7i1.443

Abstract

The tide of sea water has an effect on the activities carried out in the sea, namely shipping activities, fishing activities, and loading and unloading of ships, because tidal events occur not at the same time therefore the need for tide level prediction. Tide level data for forecast based historical tide data obtained from BMKG Tanjungpinang from January 1 to February 11, 2015, research was done by using Backpropagation. This study using as many as 1000 high tide data with some input parameters such as max iteration, target error, learning rate, number of input, and update learning rate. The accuracy of this forecast is measured by calculating the average error using MSE (Means Square Error). The best modeling result of Backpropagation with 5 hidden layer and learning rate 0,9 produce the smallest MSE 0,0035861.
Perencanaan Kawasan Prioritas Penyediaan Air Bersih menggunakan Fuzzy Multi Criteria Decision Making Winata, Angger Setia; Suswaini, Eka; Ritha, Nola
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 7 No 2 (2018): Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (582.27 KB) | DOI: 10.31629/sustainable.v7i2.521

Abstract

The Provision of water for the community, there are some problems and until now can not be overcome completely. Especially in slum areas that are prone to water so that people have difficulty to get water. Many of slums in Kab. Lingga becomes a separate problem for the planning of water supply, from the problem it is designed a system that aims to determine the priority area of water supply by implementation the fuzzy multi criteria decision making method in the planning of the priority area of water supply, obtaining the region with the highest total integral value that is Marok Tua with a value of α0 is 0,34375, α0,5 is 0,51875, α1 is 0,69375.
Implementasi Neural Fuzzy Inference System dan Algoritma Pelatihan Levenberg-Marquardt untuk Prediksi Curah Hujan Nola Ritha; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 10, No 2 (2016): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.15532

Abstract

Rainfall prediction can be used for various purposes and the accuracy in predicting is important in many ways.  In this research, data of rainfall prediction use daily rainfall data from 2013-2014 years at rainfall station in Putussibau, West Kalimantan. Rainfall prediction using four parameters: mean temperature, average humidity, wind speed and mean sea level pressure.This research to determine how performance Neural Fuzzy Inference System with Levenberg-Marquardt training algorithm for rainfall prediction. Fuzzy logic can be used to resolve the linguistic variables used in rule of rainfall. While neural networks have ability to adapt and learning process, due to recognize patterns of data from input need training to prediction. And Levenberg-Marquardt algorithm is used for training because of effectiveness and convergence acceleration.The results showed five models NFIS-LM developed using a variety of membership functions as input obtained that model NFIS-LM with twelve of membership functions and use four inputs, such as mean temperature, average humidity, wind speed and mean sea level pressure gives best results to predict rainfall with values Mean Square Error (MSE) of 0.0262050. When compared with model NN-Backpropagation, NFIS-LM models showed lower accuracy. It is shown from MSE generated where model NN-Backpropagation generate MSE of 0.0167990.
Predictive Adaptive Test with Selective Weighted Bayesian Through Questions and Answers Patterns to Measure Student Competency Levels Tekad Matulatan; Martaleli Bettiza; Muhamad Radzi Rathomi; Nola Ritha; Nurul Hayaty
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 2, Year 2019 (April 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (333.815 KB) | DOI: 10.14710/jtsiskom.7.2.2019.83-88

Abstract

Computer Assisted Testing (CAT) system in Indonesia has been commonly used but only to displaying random exam questions and unable to detect the maximum performance of the test participants. This research proposes a simple way with a good level of accuracy in identifying the maximum ability of test participants. By applying the Bayesian probabilistic in the selection of random questions with a weight of difficulties, the system can obtain optimal results from participants compared to sequential questions. The accuracy of the system measured on the choice of questions at the maximum level of the examinee alleged ability by the system, compared to the correct answer from participants gives an average accuracy of 75% compared to 33% sequentially. This technique allows tests to be carried out in a shorter time without repetition, which can affect the fatigue of the test participants in answering questions.
Applying Improved Apriori Algorithm in Figuring out the Relation between Weather Factors and Rainfall Siti Zulaikha; Martaleli Bettiza; Nola Ritha
Jurnal Inovasi Teknologi Vol 1 No 1 (2020): April
Publisher : Engineering Forum of Western Indonesian Government Universities Board (Forum Teknik, BKS-PTN Wilayah Barat) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/jit.v1i1.2133

Abstract

Data on the rainfall is compelling to study as it becomes one of the major factors affecting the weather in a certain region and various aspects of life as well. Generally, predicting rainfall is performed by analyzing data in the past in certain methods. Rainfall is prone to follow repeated pattern in sequence of time. The utilization of big data mining is expected to result in any valuable information that used to be unrevealed in the big data store. Some methods used in data mining are Apriori Algorithm and Improved Apriori Algorithm. Improved Apriori itself is to represent the database in the form of matrix to describe its relation in the database. Data used in this research is the rainfall factor in 2016 in Tanjungpinang city. Based on the test of Improved Apriori Algorithm, it was found out that the relation of the rainfall and weather factors utilizing 2 item sets, that is, if the temperature is low (24,0 - 26,0), the humidity is high (85 - 100), then the rainfall is mild. If the temperature is low (24,0 - 26,0), the light intensity is low (0 – 3), then the rainfall is heavy, and 3 item sets if the temperature is low (24,0 - 26,0), the humidity is high (85 - 100), the sun light intensity is low (0-3), then the rainfall is medium.
Peningkatan High Order Thinking Skill Siswa Melalui Pendampingan Computational Thinking Ferdi Chahyadi; Martaleli Bettiza; Nola Ritha; Muhamad Radzi Rathomi; Nurul Hayaty
Jurnal Anugerah Vol 3 No 1 (2021): Jurnal Anugerah: Jurnal Pengabdian kepada Masyarakat Bidang Keguruan dan Ilmu Pen
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1221.995 KB) | DOI: 10.31629/anugerah.v3i1.3344

Abstract

Persaingan global yang dihadapi saat ini, menuntut adanya perubahan di dalam pembelajaran agar kecakapan dan keterampilan anak didik semakin berkembang. Kemampuan literasi matematika menjadi salah satu yang harus dimiliki para siswa dalam menghadapi tantangan global tersebut. Kegiatan pelatihan dan pendampingan Computational Thinking dengan menerapkan High Order Thinking Skill (HOTS) yang dilakukan diharapkan dapat menambah wawasan siswa terhadap pemahaman dalam melakukan problem solving. Serta, menumbuhkan kreativitas siswa, budaya informasi, algoritma dan berpikir komputasional dalam menyelesaikan suatu permasalahan dalam bentuk tantangan yang dikenal dengan nama Bebras Challenge. Dalam tahapan pelaksanaannya dilakukan tahapan-tahapan yakni pre-test, pelatihan & pendampingan, serta post-test. Pre-test terhadap 15 siswa menunjukkan rerata siswa dalam menjawab soal secara benar adalah sebanyak 60%. Pelatihan-dan pendampingan dilakukan melalui aplikasi daring. Pertemuan dilaksanakan sebanyak 5 kali pertemuan. Sedangkan hasil dari post-test mengalami peningkatan yakni menjadi 78%. Hal ini menunjukkan tingkat keberhasilan siswa dalam memecahkan persoalan mengalami peningkatan yang baik.
Penerapan Association Rule Menggunakan Algoritma Apriori Pada Poliklinik Penyakit Dalam (Studi Kasus: Rumah Sakit Umum Daerah Bintan) Nola Ritha; Eka Suswaini; Wisnu Pebriadi
Jurnal Sains dan Informatika Vol. 7 No. 2 (2021): Jurnal Sains dan Informatika
Publisher : Teknik Informatika, Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/jsi.v7i2.329

Abstract

Rekam Medis merupakan berkas yang berisi tentang identitas pasien, pemeriksaan, pengobatan, tindakan serta pelayanan yang diberikan kepada pasien. Data rekam medis seiring waktu akan terakumulasi setiap hari seiring dengan aktivitas di rumah sakit. Selama ini data rekam medis yang tersedia di Rumah Sakit Umum Daerah Bintan hanya menampilkan informasi berupa data statistik maupun grafik. Sedangkan, pola dan kecenderungan penyakit yang diderita oleh pasien masih belum di gali untuk dijadikan acuan untuk penyuluhan ke masyarakat maupun sebagai pencegahan penyakit, terutama data rekam medis yang berasal dari Poliklinik Penyakit Dalam. Poliklinik Penyakit Dalam merupakan salah satu Poliklinik yang banyak melayani pasien di Rumah Sakit Umum Daerah Bintan, sehingga data rekam medis yang berasal dari Poliklinik Penyakit Dalam belum bisa digali secara maksimal. Pada penelitian ini penulis melakukan penerapan Algoritma Apriori dalam menentukan aturan asosiasi berdasarkan jenis kelamin, umur, kelurahan, dan kode ICD10. Dengan menggunakan data sebanyak 1668 dan menggunakan minimal support sebesar 6% dan minimal confidence sebesar 50%, kemudian didapatkan hasil aturan asosiasi sebanyak 22 aturan. Aturan asosiasi yang dihasilkan pada penelitian ini dapat digunakan oleh pihak rumah sakit maupun pihak dinas kesehatan untuk melakukan sosialisasi dan penyuluhan kesehatan kepada masyarakat.
Open API untuk Warung Makan Usaha Kecil dan Industri Rumahan Tekad Matulatan; Nerfita Nikentari; Martaleli Bettiza; Hendra Kurniawan; Nola Ritha
Jurnal Teknologi dan Riset Terapan (JATRA) Vol 2 No 1 (2020): Jurnal Teknologi dan Riset Terapan (JATRA) - June 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jatra.v2i1.1800

Abstract

Many food stalls are small businesses or home industries with a capital under 10 million rupiah and are generally located in the yard of the stall owner, and do not have branches. The most common obstacle was the lack of customers caused by the location of the stall which was not strategic and the information about the stall service was not widespread. OPEN API Warung Makan is the implementation of Community Service activities funded from an internal grant 2019 Raja Ali Haji Maritime University. This API is intended to be open to any application developer to take advantage of this free service to be aimed at food stalls that fall into the category of small businesses or home industries. OPEN API Warung Makan provides two parts of service, namely for customers and stall owners. OPEN API Warung Makan uses Raja Ali Haji Maritime University's cloud infrastructure and does not require Authentication Tokens or the like.
Co-Authors Chahyadi, Ferdi Cut Putri Khairani Dufan, Ariel Eka Suswaini Haryadi, Tri Hayaty, Nurul Hendra Kurniawan Martaleli Bettiza Matulatan, Tekad Muh Nurtanzis Sutoyo Muhamad Radzi Rathomi Nikentari, Nerfita Rahmad Hidayat Raja Azian Retantyo Wardoyo Siti Zulaikha Winata, Angger Setia Wisnu Pebriadi