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All Journal International Journal of Education Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Ilmiah KOMPUTASI Jurnal Teknologi dan Sistem Komputer 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
Martaleli Bettiza
Department Of Informatics, Faculty Of Engineering, Universitas Maritim Raja Ali Haji Jl. Politeknik Senggarang, Tanjungpinang
Aerospace Engineering Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics 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.
Penerapan Algoritma Local Binary Pattern untuk Pengenalan Pola Sidik Jari Hayaty, Nurul; Bettiza, Martaleli; Pratama, Eko Imam
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 6 No 2 (2017): 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 (1332.047 KB) | DOI: 10.31629/sustainable.v6i2.427

Abstract

Recognition of patterns in a person by using parts of the human body, such as on fingerprints, has been widely applied in life such as to perform absenteeism, tracking a criminal, system security and so on. Local Binary Pattern (LBP) algorithm is known as an algorithm that can describe local texture pattern in an area. LBP uses 8 scattered circular neighborhoods with center pixels centered. In a 3 x 3 pixel image, the binary value in the image center is compared with the surrounding value. The surrounding value will be 1 if the central pixel value is smaller, and is 0 if the central binary value is greater. A total of 78 data were used for this study where 26 data were using blue ink fingerprints, and 26 black ink data. After the fingerprint pattern data obtained then the image is scanned. After that the image in the crop to be 50 pixels x 50 pixels, so all the data becomes uniform. The algorithm used to make an introduction is the Manhattan Distance algorithm. Based on the test results of 26 test data with different color inks, the result obtained accuracy of 61.54%.
AN ANALYSIS OF SENIOR HIGH SCHOOL STUDENTS’ MATHEMATICS COMPETENCY IN THE FREE TRADE ZONE OF RIAU ISLANDS PROVINCE, INDONESIA Rahmatina, Desi; Bettiza, Martaleli
International Journal of Education Vol 11, No 1 (2018): August 2018
Publisher : UPI Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ije.v11i1.10891

Abstract

This study is intended to provide an analysis of the competency map of senior high school students in the Final National Exam (FNE) for mathematics subject in Free Trade Zone (FTZ) of Riau Islands province. Sample was determined by examining secondary data in the form of 2014 Final National Examination (FNE) results published by the Education Assessment Center of the Ministry of Education and Culture of the Republic of Indonesia in the FTZ of Riau Islands Province, namely Batam, Bintan, and Karimun regencies. Criteria of sample determination were schools with lower Graduate Competency Standards (GCS) than the regency/city GCS, distribution of public or private schools, and distribution of school locations, with a total sample of 37 schools. The research was conducted by using descriptive statistical method to gain a description of the senior high school students’ competency in mathematics subject based on their FNE scores. The findings of this research can be made input and consideration for schools and government to improve the quality of education through analysis of the FNE results. The research results show that low GCS achievements were found in geometry and trigonometry topics, especially in the skills of determining position, distance, and magnitude of angles involving points, lines, and fields in solid geometry. The mean percentage of GCS mastery in the FTZ was 22.86%, with Batam 26.02%, Bintan 18.66%, and Karimun 18.72%. The result of the interview shows that the low GCS is caused by the lack of teaching media in the visual forms or simulators to build students’ understanding and limited time allocated in teaching. The solution recommended to solve this problem is by applying ICT-based learning to improve students’ understanding of geometry and trigonometry materials and also the use of video conferencing during mathematics teacher working group meetings.
Prediksi Kecepatan Angin Menggunakan Adaptive Neuro Fuzzy (ANFIS) dan Radial Basis Function Neural Network (RBFNN) Nikentari, Nerfita; Bettiza, Martaleli; Sastypratiwi, Helen
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 4, No 1 (2018): Volume 4 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.842 KB) | DOI: 10.26418/jp.v4i1.25558

Abstract

Angin sebagai salah satu fenomena alam yang mempengaruhi berbagai aspek dalam kehidupan manusia baik pengaruh positif maupun negatif. Aspek ini berperan besar dalam ekonomi, pariwisata, pembangunan, transportasi maupun perdagangan masyarakat. Data angin dalam hal ini kecepatan angin belum dapat diketahui secara pasti nilainya oleh karena itu perlu adanya prediksi. Adaptive Neuro Fuzzy Inference System (ANFIS) dan Radial Basis Function Neural Networkc(RBFNN) adalah algoritma yang dapat digunakan untuk prediksi data. Penelitian ini  menggunakan ANFIS dan RBFNN untuk memprediksi kecepatan angin. Data prediksi yang digunakan dalam penelitian ini adalah data time series. Data kecepatan angin diperoleh dari BMKG (Badan Meteorologi Klimatogi dan Geofisika) Tanjungpinang, Kepualuan Riau. Hasil prediksi dengan kedua metode ini dibandingan dengan data asli untuk mengetahui metode mana yang lebih akurat dalam prediksi data. Hasil pengujian menggunakan kedua algoritma memperlihatkan akurasi terbaik (paling mendekati data asli/target) diperoleh oleh RBFNN yaitu dengan nilai RMSE adalah 0,1766 dan hasil RMSE ANFIS adalah 1,1456.
Building Student’s Study Path using Markov Chain Process with Apriori Cross Join Pearson Correlation Tekad Matulatan; Martaleli Bettiza
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 2: EECSI 2015
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (991.889 KB) | DOI: 10.11591/eecsi.v2.787

Abstract

Student’s study path could be advised by using bestpossible path from Markov Chain rule based on student’sacademic performance records with several assumption on thecurrent curriculum. Finding the Markov’s rule is crucial processbecause it will determine study path’s scenarios which rely onstudent current performance to choose the next best possiblepath. The rule would be built using the whole student’s academicperformance on the same curriculum by implementing AprioriCross Join Pearson Correlation Test on two consecutivesemesters. It will then create path consist of paired courses A->B with Pearson value that would be implemented as rule in Markov Process
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.
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.
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.
Co-Authors Chahyadi, Ferdi Dufan, Ariel Hayaty, Nurul Helen Sastypratiwi, Helen Hendra Kurniawan Malik, Riani Fitri Ibnul Matulatan, Tekad Muhamad Radzi Rathomi Nikentari, Nerfita Nola Ritha Nurfalinda, Nurfalinda Pratama, Eko Imam Ritha, Nola Siti Zulaikha Syafina, Syafina Wibisono, Ganda Bagus