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KLASIFIKASI TINGKAT KEMATANGAN CABAI MERAH KERITING MENGGUNAKAN SVM MULTICLASS BERDASARKAN EKSTRAKSI FITUR WARNA Irma, Irma; Muchtar, Mutmainnah; Adawiyah, Rabiah; Sarimuddin, Sarimuddin
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4430

Abstract

The utilization of digital image processing holds significant potential for classifying the ripeness of curly red peppers (Capsicum annuum L.). This study aims to develop an automatic classification method using multiclass Support Vector Machine (SVM) with a linear kernel. Images of peppers, captured using a smartphone camera, were categorized into three classes: ripe, unripe, and semi-ripe. Features such as mean, variance, and range from the RGB color space were extracted for training and testing data. Testing was conducted by dividing the data into training and test sets and employing 10-fold cross-validation. Results demonstrated a classification accuracy of 98.33%. The combination of mean, variance, and range features significantly improved accuracy compared to single features. This research demonstrates the effectiveness of the developed method and its applicability in automated classification systems to support the agricultural sector.
PERBANDINGAN JARAK EUCLIDEAN, CITYBLOCK, MINKOWSKI, CANBERRA, DAN CHEBYSHEV DALAM SISTEM TEMU KEMBALI CITRA BATIK Muchtar, Mutmainnah; Zainuddin, Noorhasanah; Sajiah, Adha Mashur; Ningsi, Nurfitria; Pasrun, Yuwanda Purnamasari
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5324

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Batik is a highly valuable cultural heritage in Indonesia, showcasing a rich diversity of motifs with deep meaning and aesthetics. To enhance the accessibility and utilization of batik collections, an efficient image retrieval system is essential. This study compares distance measurement methods in a batik image retrieval system: Euclidean, Cityblock, Minkowski, Canberra, and Chebyshev, using a combination of color and texture features. The dataset comprises 50 types of batik images. The results show that the Cityblock method achieves the highest Mean Average Precision (MAP) of 97.71, followed by Canberra with MAP 96.87. The Euclidean method also performs well with a MAP of 94.56, while Minkowski and Chebyshev have lower MAP values of 92.93 and 90.89, respectively. Chebyshev experiences the largest MAP drop when images are rotated (5.98), while Cityblock demonstrates the best resistance to rotation with the smallest MAP drop (1.51). This research successfully developed a Content-Based Image Retrieval (CBIR) system with a GUI in MATLAB and suggests integrating the latest image processing and machine learning techniques for further enhancement.
Peningkatan Kualitas Produksi dan Pemasaran Rumput Laut Melalui Implementasi Teknologi Modern di Desa Tanailandu Sarimuddin, Sarimuddin; Yunus, La Ode Ichlas Syahrullah; Fitra, Ramad Arya; Kasim, Ma'ruf; Jaya, La Ode Muhammad Golok; Muchtar, Mutmainnah
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 6, No 1 (2025)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v6i1.5252

Abstract

Desa Tanailandu di Kabupaten Buton Tengah memiliki potensi besar dalam budidaya rumput laut, yang menjadi sumber mata pencaharian utama masyarakat setempat. Namun, metode pengeringan tradisional yang masih banyak digunakan menyebabkan kualitas rumput laut menurun, sehingga mempengaruhi nilai jual di pasar. Program pengabdian masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan masyarakat dalam produksi rumput laut melalui penerapan teknologi pengeringan modern berbasis tenaga surya, sehingga mampu menghasilkan produk berkualitas yang dapat meningkatkan nilai jual dan kesejahteraan mitra di Desa Tanailandu. Mesin pengering ini dilengkapi dengan panel surya untuk sumber daya utama, sistem kontrol suhu otomatis, dan sistem kontrol mesin yang dapat diakses secara online. Selain itu, teknologi pengolahan citra juga diimplementasikan untuk menilai tingkat kekeringan rumput laut berdasarkan warna, yang memudahkan pengguna dalam mencapai kualitas optimal. Program ini juga mencakup pelatihan teknis dan pendampingan bagi para petani rumput laut, serta penerapan strategi pemasaran digital untuk memperluas pasar dan meningkatkan nilai jual produk. Hasil program menunjukkan adanya peningkatan efisiensi proses pengeringan dan kualitas produk yang lebih konsisten, mendukung kesejahteraan ekonomi masyarakat. Program ini diharapkan dapat berkontribusi pada keberlanjutan usaha rumput laut yang ramah lingkungan dan memperkuat ekonomi lokal di Tanailandu
Expert System for Determining Diseases and Pests in Seaweed Using Forward Chaining (Case Study : Watorumbe Village, Mawasangka Tengah) Asriani, Ika; Muchtar, Mutmainnah; Ismail, Rima Ruktiari; Paliling, Alders; Sya'ban, Kharis; Karim, Rahmat
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.175

Abstract

Seaweed is a marine organism that plays a crucial role in both ecosystem and economy. However, it often faces attacks from diseases and pests that can jeopardize the productivity and sustainability of the seaweed industry. Hence, the development of an expert system to diagnose seaweed diseases and pests becomes imperative. This research aims to develop an Expert System for Determining Diseases and Pests in Seaweed using the Forward Chaining method, with a case study conducted in the Watorumbe Village, Mawasangka Tengah Sub-district, Southeast Sulawesi. The Forward Chaining method is employed to identify symptoms appearing in seaweed and determine potential diseases or pests. Testing is carried out with 30 data samples compared against expert diagnoses, resulting in an accuracy rate of 90%. Therefore, this system has the potential to assist seaweed farmers in diagnosing diseases and pests more quickly and accurately, thereby enhancing the productivity and sustainability of seaweed cultivation efforts.
KLASIFIKASI JENIS KAIN TENUN BUTON DENGAN METODE K-NN BERDASARKAN FITUR WARNA RGB DAN HSV SERTA EKSTRAKSI TEKSTUR DENGAN GLCM Sabi, Musini; Muchtar, Mutmainnah; Sya'ban, Kharis; Paliling, Alders; Miftachurohmah, Nisa; Karim, Rahmat
Jurnal Mnemonic Vol 8 No 1 (2025): Mnemonic Vol. 8 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v8i1.13220

Abstract

Kain tenun Buton – Sulawesi Tenggara merupakan bentuk kreativitas tradisional masyarakat Buton dengan berbagai motif dan makna tersendiri. Namun, banyaknya jenis kain tenun Buton membuat tidak semua orang, termasuk masyarakat Buton, dapat mengenali jenisnya. Penelitian ini mengklasifikasikan citra kain tenun Buton menggunakan metode k-nearest neighbor (K-NN) dengan fitur warna RGB, HSV, dan GLCM. Dari hasil pengunjian yang telah dilakukan dengan menggunakan 150 citra uji, hasil cropping 2 loba yang terbagi ke dalam 10 kelas berbeda memperoleh nilai akurasi tertinggi yaitu 96% ketika menggunakan fitur RGB, 93,33% ketika menggunakan fitur HSV dan 88% ketika menggunakan fitur GLCM, pada masing-masing nilai k = 1 dan 2. Selain itu, pengujian juga dilakukan untuk 20 citra hasil cropping 4 loba dan memperoleh nilai akurasi tertinggi sebesar 95% ketika menggunakan fitur RGB pada nilai k = 1 dan 2, serta 100% ketika menggunakan fitur HSV pada nilai k = 3 dan 5. Akurasi yang cukup rendah yaitu sebesar 25% didapatkan ketika menggunakan fitur GLCM pada nilai k =1 sampai 5. Hasil ini menunjukkan bahwa metode K-NN dengan fitur warna RGB dan HSV memberikan akurasi tinggi dalam klasifikasi kain tenun Buton, sehingga dapat menjadi solusi efektif untuk identifikasi jenis kain secara otomatis
Pelatihan Penggunaan Aplikasi Penjualan Berbasis Barcode Pada Apotek Alwina II Kota Baubau Sarimuddin; Mutmainnah Muchtar; Rima Ruktiari Ismail; Muliyadi; Rahmat Karim; Kharis Sya’ban; Sunyanti; Hamid Wijaya; Muh. Na’im Al Jum’ah; Dirman
PUSAKA ABDIMAS Vol. 1 No. 1 (2024)
Publisher : Yayasan Serumpun Karang Konservasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61548/pa.v1i1.32

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Dalam era digital, penggunaan aplikasi penjualan menjadi sangat penting bagi apotek untuk meningkatkan efisiensi dan akurasi dalam proses administrasi penjualan serta manajemen persediaan. Kegiatan pengabdian ini bertujuan untuk meningkatkan efisiensi administrasi penjualan di Apotek Alwina Farma 2 Kota Bau-Bau melalui pelatihan penggunaan aplikasi penjualan berbasis barcode. Tim Pengabdian kepada Masyarakat (PkM) dari Universitas Sembilanbelas November (USN) Kampus B Buton Tengah mengembangkan aplikasi ini dan memberikan pelatihan intensif kepada para pegawai apotek. Evaluasi kegiatan dilakukan menggunakan lima item pertanyaan untuk mengukur pemahaman dan kemampuan operasional peserta terhadap aplikasi yang telah dikembangkan. Hasil evaluasi menunjukkan bahwa secara keseluruhan, para peserta mampu memahami dan mengoperasikan aplikasi penjualan berbasis barcode dengan baik. Pelatihan yang diberikan terbukti efektif dalam meningkatkan efisiensi proses administrasi penjualan di apotek, khususnya di Apotek Alwina Farma 2 Kota Bau-Bau. Diharapkan dengan adanya aplikasi ini, berbagai apotek lainnya juga dapat menerapkan teknologi serupa untuk meningkatkan efisiensi dan akurasi dalam proses penjualan dan manajemen persediaan.
Optimasi Pemilihan Tenaga Kerja Bagang dengan AHP dan Weighted Product Maulana, Sahrul; Pasrun, Yuwanda Purnamasari; Muchtar, Mutmainnah; Yuandi, Intan Anuggrah
JISTech : Journal of Information Systems and Technology Vol. 2 No. 1 (2025): Juni 2025
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71234/jistech.v2i1.61

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Choosing the appropriate personnel for bagang fishing units is essential for facilitating effective and efficient field operations. Nevertheless, selection processes dependent on subjective judgment frequently yield unsatisfactory outcomes. This study seeks to establish a decision support system utilizing a mix of the Analytical Hierarchy Process (AHP) and Weighted Product (WP) approaches to identify the optimal candidates. AHP calculates the hierarchical weight of each criterion by pairwise comparisons, whereas WP ranks alternatives based on preference values. The evaluation employs five primary criteria: work experience, physical endurance, discipline, capacity for night shifts, and technical skills. The results indicate that the most qualified individuals were objectively chosen, with A3, A7, and A5 receiving the greatest preference scores. This model provides a systematic framework for decision-making and is applicable in analogous circumstances necessitating multi-criteria selection. The implemented system has demonstrated an improvement in accuracy and transparency in labor recruiting in the conventional fishing sector.
Sistem Cerdas Deteksi Kematangan Buah Naga Berbasis HSV-KNN Paliling, Alders; Muchtar, Mutmainnah; Fardian, Fardian
e-Jurnal JUSITI (Jurnal Sistem Informasi dan Teknologi Informasi) Vol. 14 No. 1 (2025): e-Jurnal JUSITI
Publisher : Universitas Dipa Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36774/jusiti.v14i1.1718

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Penelitian ini mengembangkan sistem deteksi kematangan buah naga berbasis fitur warna menggunakan transformasi ruang warna HSV dan klasifikasi K-Nearest Neighbor (KNN). Penilaian kematangan secara manual sering subjektif dan tidak efisien, menyebabkan panen yang tidak optimal. Dataset terdiri dari 120 citra RGB buah naga dengan latar belakang putih (90 latih, 30 uji), diproses melalui konversi ke ruang warna HSV. Fitur rata-rata Hue, Saturation, dan Value diekstraksi untuk klasifikasi KNN dengan jarak Euclidean (k=3, 5, 7, 9, 11). Hasil menunjukkan akurasi rata-rata 91,94%, dengan akurasi tertinggi 96,7% pada k=9 dan k=11. Sistem efektif mengklasifikasikan kelas matang dan mentah, tetapi akurasi kelas setengah matang lebih rendah akibat gradasi warna kompleks. Penelitian ini menunjukkan sistem bisa menjadi langkah awal untuk membantu petani panen lebih baik di masa depan.
Pengembangan Sistem Informasi Manajemen Pengelolaan Sampah Digital Kawasan Pantai Kalomang Kabupaten Kolaka: Development of Digital Waste Management Information System for Kalomang Beach Area, Kolaka Regency Rasyid, Rasmiati; Ningsi, Nurfitria; Muchtar, Mutmainnah; Sarimuddin, Sarimuddin
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 2 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kalomang Beach is a famous tourist destination in Kolaka. Currently, waste management is carried out in a manner where the garbage pick-up process is carried out when the garbage is full and even pollutes this tourist area, this of course can lead to environmental damage and decreased visitor interest. This research seeks to identify critical issues in waste management at Kalomang Beach and provide an integrated waste management platform to assist the government in assessing waste activities and guidelines. The information provided by this system can improve public health on a local and global scale. The utilization of the SDLC System Development approach in this case the Waterfall method allows for a detailed and appropriate design which tends to be more measurable in terms of time and cost, the use of data modeling through the Unified Modeling Language, and blackbox testing shows that the waste input form is in accordance with the needs of the user where it places groupings of waste types that make it easier for tourist area officers to report the availability of waste that is ready to be picked up. Future system development is important to consider aspects of sustainability, user training, and integration with IOT or microcontroller based waste monitoring systems.   Keywords— Integrated Waste Management Information System, Kalomang Beach, Waterfall
PEMANFAATAN ARDUINO DAN SENSOR KY-038 UNTUK MEMBEDAKAN SUARA MESIN CHAINSAW DAN MESIN LAIN DI AREA PEMBALAKAN LIAR Hendri; Muchtar, Mutmainnah; Sarimuddin
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6797

Abstract

Illegal logging is a significant environmental issue in Indonesia, particularly in the tropical forests of Southeast Sulawesi, which threatens biodiversity and contributes to global climate change. Manual monitoring of illegal activities in remote areas is often ineffective, necessitating innovative and real-time solutions for early detection. This study aims to develop an early detection system to distinguish the sound of chainsaws commonly used in illegal logging activities from other machine sounds such as RX King motorcycles and ketinting boats. The KY-038 sound sensor connected to an Arduino was used to capture environmental sounds, and the obtained data was classified using the K-Nearest Neighbors (KNN) algorithm. Experiments were conducted by collecting training data and testing the system with sound samples from each machine. The results showed that the developed sound detection system could classify the sounds of chainsaws, RX King motorcycles, and ketinting boats with good performance. With the optimal k value in KNN, the average classification accuracy reached 90%. This system can be used as an effective monitoring tool for the early detection of illegal logging activities, contributing to the conservation of tropical forests.
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 Karmila Alam Syah Wellem 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 Yasmine, Mutiara Putri Yuandi, Intan Anuggrah Yuwanda Purnamasari Pasrun