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All Journal Indonesian Journal of Geography Jurnal Ilmu Komputer dan Informasi Jupiter Jurnal Informatika dan Teknik Elektro Terapan SemanTIK : Teknik Informasi Jurnal Sumberdaya Akuatik Indopasifik JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal ULTIMA Computing STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Journal of Innovation and Future Technology (IFTECH) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Mnemonic Community Development Journal: Jurnal Pengabdian Masyarakat Reswara: Jurnal Pengabdian Kepada Masyarakat Community Empowerment Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal Media Informasi Teknologi Journal of Information Systems and Technology (JISTech) Mekongga: Jurnal Pengabdian Masyarakat TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang Media of Computer Science Jurnal Pusat Kolaborasi Pengabdian Kepada Masyarakat JROCK (Journal Research on Computing Knowledge) Jurnal Sistem Informasi dan Teknologi Informasi

Mutmainnah Muchtar

Universitas Sembilanbelas November Kolaka

Author-ID : 5719535

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 42 Documents Claim Missing Document

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Articles

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FRACTAL DIMENSION AND LACUNARITY COMBINATION FOR PLANT LEAF CLASSIFICATION Mutmainnah Muchtar; Nanik Suciati; Chastine Fatichah
Jurnal Ilmu Komputer dan Informasi Vol 9, No 2 (2016): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Plants play important roles for the existence of all beings in the world. High diversity of plant’s species make a manual observation of plants classifying becomes very difficult. Fractal dimension is widely known feature descriptor for shape or texture. It is utilized to determine the complexity of an object in a form of fractional dimension. On the other hand, lacunarity is a feature descriptor that able to determine the heterogeneity of a texture image. Lacunarity was not really exploited in many fields. Moreover, there are no significant research on fractal dimension and lacunarity combination in the study of automatic plant’s leaf classification. In this paper, we focused on combination of fractal dimension and lacunarity features extraction to yield better classification result. A box counting method is implemented to get the fractal dimension feature of leaf boundary and vein. Meanwhile, a gliding box algorithm is implemented to get the lacunarity feature of leaf texture. Using 626 leaves from flavia, experiment was conducted by analyzing the performance of both feature vectors, while considering the optimal box size r. Using support vector machine classifier, result shows that combined features able to reach 93.92 % of classification accuracy.

SIMILARITY BASED ENTROPY ON FEATURE SELECTION FOR HIGH DIMENSIONAL DATA CLASSIFICATION Jayanti Yusmah Sari; Mutmainnah Muchtar; Mohammad Zarkasi; Agus Zainal Arifin
Jurnal Ilmu Komputer dan Informasi Vol 7, No 2 (2014): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Abstract Curse of dimensionality is a major problem in most classification tasks. Feature transformation and feature selection as a feature reduction method can be applied to overcome this problem. Despite of its good performance, feature transformation is not easily interpretable because the physical meaning of the original features cannot be retrieved. On the other side, feature selection with its simple computational process is able to reduce unwanted features and visualize the data to facilitate data understanding. We propose a new feature selection method using similarity based entropy to overcome the high dimensional data problem. Using 6 datasets with high dimensional feature, we have computed the similarity between feature vector and class vector. Then we find the maximum similarity that can be used for calculating the entropy values of each feature. The selected features are features that having higher entropy than mean entropy of overall features. The fuzzy k-NN classifier was implemented to evaluate the selected features. The experiment result shows that proposed method is able to deal with high dimensional data problem with average accuracy of 80.5%.

Klasifikasi Citra Daun dengan Metode Gabor Co-Occurence Mutmainnah Muchtar; Laili Cahyani
Ultima Computing : Jurnal Sistem Komputer Vol 7 No 2 (2015): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Plant takes a crucial part in mankind existences. The development of digital image processing technique made the plant classification task become a lot of easier. Leaf is a part of plant that can be used for plant classification where texture of the leaf is a common feature that been used for classification process. Texture offers a unique feature and able to work even when the leaf is damaged or overly big in size which sometimes made the acquisition process become more difficult. This study offers a combination of Gabor filter methods and co-occurrence matrices to produce the most representative features for leaf classification. Classification using SVM with 5-fold cross validation system shows that the proposed Gabor Co-Occurence methods was able to reach average accuracy up to 89.83%. Terms: Leaf, Gabor Co-occurence, Support Vector Machine, Texture

APLIKASI PREDIKSI PENJUALAN BARANG MENGGUNAKAN METODE K-NEAREST NEIGHBOR (KNN) (STUDI KASUS TUMAKA MART) Hasmawati Hasmawati; Jumadil Nangi; Mutmainnah Muchtar
semanTIK Vol 3, No 2 (2017): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Salah satu kegiatan usaha yang harus dilakukan agar perusahaan tetap berjalan dan berkembang adalah penjualan. Keputusan yang diambil pemegang tanggung jawab perusahaan akan mempengaruhi perusahaan dimasa depan. Salah satu keputusan yang harus ditentukan yaitu produk yang akan diproduksi dan dijual untuk periode selanjutnya. Dalam menentukan keputusan diperlukan metode agar keputusan yang akan diambil dapat tepat sasaran. Teknik yang digunakan untuk memperkirakan keadaan pada periode selanjutnya disebut prediksi. Penelitian ini mengusulkan pengembangan aplikasi prediksi penjualan barang. Adapun metode yang di usulkan adalah metode K-Nearest Neighbor dengan studi kasus Tumaka Mart. Hasil penelitian menunjukan metode yang diusulkan berhasil diimplementasikan untuk menyelesaikan kasus prediksi penjualan dengan tingkat error atau Mean Absolute Percentage Error sebesar 6 % dan akurasi 94 % Kata kunci—Penjualan, Prediksi, K-Nearest Neighbor.

APLIKASI ISTILAH AKUNTANSI SEBAGAI MEDIA PEMBELAJARAN BERBASIS ANDROID MENGGUNAKAN ALGORITMA REVERSE COLUSSI Annisyah Januarti; Sutardi Sutardi; Mutmainnah Muchtar
semanTIK Vol 3, No 2 (2017): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Akuntansi adalah proses dari transaksi yang dibuktikan dengan faktur, lalu dari transaksi dibuat jurnal, buku besar, neraca lajur, kemudian akan menghasilkan informasi dalam bentuk laporan keuangan yang digunakan pihak-pihak tertentu. Kamus akuntansi merupakan salah satu media pembelajaran yang sangat dibutuhkan dalam dunia pendidikan. Namun, seringkali ditemukan masalah waktu yang kurang efisien dan ukuran kamus yang biasannya besar dan berat untuk dibawa kemana-mana. Salah satu cara untuk mengatasi masalah ini adalah dengan membuat aplikasi istilah akuntansi berbasis android. Algoritma Reverse Colussi memiliki kinerja pencarian kata dimulai dari akhir pattern yang disesuaikan dengan sumber teks.Untuk mempermudah pengguna kamus dalam mencari istilah di bidang akuntansi, maka diperlukan integrasi dari sistem manual ke sistem otomatis dengan mengimplementasikan Algoritma Reverse Colussi. Algoritma Reverse Colussi memiliki kinerja pencarian kata dimulai dari pattern yang dicocokkan dengan sumber teks. Jika terjadi ketidakcocokkan pada pattern maka secara langsung akan dilakukan perpindahan posisi pengecekan. Hasil yang diperoleh dari penelitian ini adalah sebuah aplikasi istilah akuntansi berbasis android offline sangat efisien karena rata-rata waktu pencarian paling lambat kurang dari 2 detik, dan tepat dalam melakukan pencarian string, selama istilah yang dicari ada dalam database.Kata kunci—Android, Algoritma Reverse Colussi.

SPK PEMBERIAN KREDIT MENGGUNAKAN METODE WP (WEIGHTED PRODUCT) PADA BMT MU’AMALAH SEJAHTERA KENDARI Abdul Jalil; Ika Purwanti Ningrum; Mutmainnah Muchtar
semanTIK Vol 3, No 1 (2017): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

BMT Mu’amalah Sejahtera Kendari merupakan sebuah lembaga yang bergerak dalam bidang pelayanan simpan pinjam. BMT Mu’amalah Sejahtera memprioritaskan kredit bagi usaha kecil dan menengah (UKM). Proses penentuan kelayakan kredit nasabah masih dilakukan secara manual sehingga kurang efisien dalam pelaksanaannya. Untuk itu diperlukan sistem baru dalam penentuan kelayakan pemberian kredit nasabah. Untuk merealisasikan sistem pendukung keputusan ini, digunakan metode Weighted Product (WP). Weighted Product (WP) Merupakan metode pengambilan keputusan dengan cara perkalian untuk menghubungkan rating atribut, dimana rating setiap atribut harus dipangkatkan dulu dengan bobot atribut yang bersangkutan . Hasil dari penelitian ini adalah sebuah sistem pendukung keputusan pemberian kredit, dimana implementasi sistem ini menunjukkan bahwa Weighted Product (WP) dalam proses perengkingan pada pemberian kredit nasabah baru mempunyai nilai hasil yang sama, apabila metode dihitung secara manual.Kata kunci—Sistem Pendukung Keputusan, Weighted Product (WP), Pemberian Kredit.

APLIKASI PENENTUAN MINAT STUDI SISWA MENGGUNAKAN METODE SINGLE LINKAGE CLUSTERING (STUDI KASUS : SMK NEGERI 1 KENDARI) Nurfinasari Nurfinasari; Sutardi Sutardi; Mutmainnah Muchtar
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

The process of determining the areas of interest (specialization) in Vocational Schools in Indonesia is organized to match the ability and interests of learners to the field of their choosing. SMK Negeri 1 Kendari is one of the institutions engaged in the field of education, especially vocational which stood under the auspices of Education Department of Kendari City and is located at Jl. Jend. A. Yani No. 17 Kota Kendari. This school has 4 majors that can be selected by students, among others: Accounting, Office Administration, Trade, Computer Engineering and Network (TKJ). The process of determining the program of expertise SMK Negeri 1 Kendari still using the manual way, if done by manual it will require extra precision because the data is quite a lot and has many weaknesses that allow errors in the process of majors. Therefore, proper classification of majors is required, one of them using technology in the field of data mining. In this research, single linkage clustering method is chosen, which is where the distance between clusters will get shorter time between clusters to achieve the final result and as media optimization in terms of facilitating the school in determining the majors of interest students. From the results of research and implementation note that the system can classify the data of student interest in SMKN 1 Kendari by using Single Linkage Clustering, Make it easier to clustering data by calculating the closest distance of each cluster object and student interest in SMKN 1 Kendari shows that 35.7 % Accounting and Finance, 28.6% Business and Marketing, 28.6% Office Management and 7.1% Computer & Network Engineering, from 438 student data.Keywords—Data Mining, Single Linkage Clustering, Interest in Studies DOI : 10.5281/zenodo.1402386

Training on making creative learning media using the canva application for MI and MTs Al-Mu'minin Kendari Teachers Fathur Rahman Rustan; Muhammad Syaiful; Rahmat Karim; Mutmainnah Muchtar; Jayanti Yusmah Sari; Phradiansah Phradiansah; Indar Ismail Jamaluddin; Suharsono Bantun; Nur Fajriah Muchlis; Yuwanda Purnamasari Pasrun; La Ode Hasnuddin S Sagala
Community Empowerment Vol 7 No 8 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.7106

Attractive learning media has become a necessity for teachers at all levels of education. For this reason, educators need to improve their competence in making good learning media. However, there are still many teachers who are not familiar with using technology to support their teaching and learning activities. As felt by MI and MTs AL-Mu'minin Kendari teachers who still find it difficult to make interesting and creative learning media. This service activity aims to improve the ability of teachers to create interesting media using the Canva application. The stages carried out in this activity are (1) coordinating with the school and identifying the needs of the target audience; (2) carry out community service activities with lecture, question and answer methods, and guided practice; and (3) evaluate and assign independent assignments. The results of this program showed an increase in teacher skills in making interesting learning media as seen from the independent assignments that were collected.

Kelimpahan Mikroplastik pada Sedimen Ekosistem Terumbu Karang di Pulau Bokori Sulawesi Tenggara Riska Riska; Ilham Antariksa Tasabaramo; Lalang Lalang; Mutmainnah Muchtar; Asni Asni
Jurnal Sumberdaya Akuatik Indopasifik Vol 6 No 4 (2022): November
Publisher : Fakultas Perikanan dan Ilmu Kelautan, Universitas Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46252/jsai-fpik-unipa.2022.Vol.6.No.4.252

Microplastic pollution is a threat to marine ecosystems. Microplatics in coral reef ecosystems can pose a threat to coral reef health. This study aims to determine the condition of coral reefs, and the distribution of microplastics in the tourist area of Bokori island as a first step for conservation and mitigation from the impact of microplastic pollution. Sampling wa carried out at 4 research stations. The environmental quality parameters measured were temperatur, dissolved oxygen, pH, salinity, water brightness, current, nitrate, and phosphate. Sampling using purposive sampling method. Sediment sampling using Scuba set and sediment grab at a depth of 3-10 meters. Sediment is taken ±1000 gr and stored in double zip lock plastic. The samples were the analyzed and observed using microplastics laboratory. The results showed that there are four types of microplastics found in sediments in the waters of the island of Bokori, namely fiber, foam, film, and fragments. Fiber is the most common type of microplastic with an average of 41.564 particles/kg dry sediment per aobservation station, while the lowest abundance was foam type with an average value of 9.379 particles/kg dry sediment. The abundance of microplastic at each sampling location was not the same due to the different characteristics of the study sites.

DETEKSI AREA KERUSAKAN PADA CITRA TERUMBU KARANG AKIBAT CORAL BLEACHING BERBASIS PENGOLAHAN CITRA DIGITAL Mutmainnah Muchtar; Riska Riska
Journal of Innovation And Future Technology (IFTECH) Vol 5 No 2 (2023): Vol 5 No 2 (August 2023): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v5i2.2701

Coral reefs have a very large role in marine ecosystems, because they provide rich habitats and support biodiversity. Segmentation on images of coral reefs experiencing coral bleaching is also very important. Coral bleaching is a phenomenon in which coral reefs lose their symbiotic algae pigments, resulting in bleaching and possibly death of coral reefs. By segmenting coral reef images that experience coral bleaching, we can separate areas affected by bleaching from areas that are still healthy. This study aims to detect areas of damage that occur in underwater images of coral reefs that have experienced coral bleaching. By using techniques in digital image processing and segmentation based on colour intensity, satisfactory results are obtained. The test results show that the RAE and ME values are quite low, namely 0.051 and 0.035 respectively with an average processing time of 0.2 seconds. This research is expected to assist in further analysis and modelling related to coral bleaching to understand the causative factors and develop appropriate protection strategies.

Co-Authors Abdul Jalil Abdul Malik Agus Zainal Arifin Aisyah, Wa Ode Nur Al Jum'ah, Muhammad Na'im alders paliling Andi Tenri Sumpala, Andi Tenri Andi, Ilham Annisyah Januarti Arjaliyah Muchtar, Rafiqah Asni Asni Asriani, Ika Chastine Fatichah Dirman ENDRI ENDRI Fardian, Fardian Fathur Rahman Rustan Fitra, Ramad Arya Fitri, Nurul Aisyah Hairani Idrus, Sitti Hamid Wijaya Hasidu, La Ode Abdul Fajar Hasmawati Hasmawati Ika Purwanti Ningrum Ilham Antariksa Tasabaramo Indar Ismail Jamaluddin Irma Irma Ismail, Rima Ruktiari Jaya, La Ode Muhammad Golok Jaya, Laode Muhammad Golok Jayanti Yusmah Sari Jayawarsa, A.A. Ketut Jimsan Jimsan Johar Nur Iin Jumadil Nangi Kasim, Ma'ruf La Ode Hasnuddin S. Sagala La Ode Ichlas Syahrullah Yunus Laili Cahyani Lalang Lalang Luh Putu Ratna Sundari Mardiawati Mardiawati Mardiawati Mardiawati, Mardiawati Maulana, Sahrul Maulidiah, Rizka Miftachurohmah, Nisa Muchtar, Rafiqah Arjaliyah Muh. Na’im Al Jum’ah Muhammad Syaiful Muliyadi Muliyadi Muliyadi Nanik Suciati Nisa Miftachurohmah Noorhasanah Zainuddin Nur Fajriah Muchlis Nur Fajriah Muchlis, Nur Fajriah Nurfinasari Nurfinasari Nurfitria Ningsi Nurjannah Nurjannah Phradiansah ., Phradiansah Rabiah Adawiyah, Rabiah Rafiqah Arjaliyah Muchtar Rahmat Karim Rasmiati Rasyid Rima Ruktiari Riska Risnawati Rizal Adi Saputra Sabi, Musini Sajiah, Adha Mashur Sarimuddin Sarimuddin, Sarimuddin Suharsono Bantun Sunyanti Sunyanti, Sunyanti Sutardi Sutardi Sutoyo, Muhammad Nurtanzis Sya'ban, Kharis Syaban, Kharis Utomo, Puji Prio Wellem, Karmila Alamsyah Yasmine, Mutiara Putri Yuandi, Intan Anuggrah Yuwanda Purnamasari Pasrun

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