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All Journal Jurnal Teknologi Informasi dan Multimedia Rengganis Jurnal Pengabdian Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) Bakti Sekawan : Jurnal Pengabdian Masyarakat
Muhammad Imam Dinata
UNIVERSITAS MUHAMMADIYAH MATARAM
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Health Professions Mathematics Social Sciences Other

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PENGAMBILAN KEPUTUSAN UNTUK MEMILIH MINUMAN DENGAN METODE WEIGHT PRODUCT (WP) DI KOTA MATARAM Muhammad Imam Dinata; Muhammad Rizkillah; Arif Rahman
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 5 No 1 (2023): EDISI 15
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v5i1.2429

Abstract

One of these micro-enterprises is a coffee shop. The number of coffee shops in the Mataram city area is currently approximately 50 coffee shops. Many forms and choices of drinks sell in coffee shops make buyers confused when choosing which beverage product to consume. Necessary to decide to choose beverage products with a Decision Support System Using the Weighted Products order to assist in the selection of beverages when placing an order at a coffee shop that suits the needs of buyers. Only 2 basic types of drinks are usually ordered at coffee shops, namely coffee, and milk. Produce the best alternative sequence used for decision-making. the decision to choose drinks in the city of Mataram using the Weighted Product (WP) with several criteria, namely price, composition, type of drink, and size. From the results of calculations carried out the type of coffee milk drink obtained the highest value, namely 0.016, then for the second rank the type of long black drink with a value of 0.0157, and third rank, the type of avocado milkshake drink with a value of 0.015.
Pendampingan Branding Produk Dengan Menggunakan Aplikasi Canva Pada LKP Khiara Training Centre Idham; Imam Dinata, Muhammad
Rengganis Jurnal Pengabdian Masyarakat Vol. 3 No. 2 (2023): November 2023
Publisher : Pendidikan Matematika, FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/rengganis.v3i2.354

Abstract

The utilization of digital technology in the era of Industry 4.0 provides significant benefits, especially in the tourism and culinary sectors. Digital branding, which creates product identity through technology, is crucial in promoting products and creating a positive perception in society. Training institutions such as Khiara Training Center play a role in imparting skills to the community. The use of digital marketing by small and medium-sized enterprises (SMEs) can expand their marketing reach nationally and internationally. Graphic design, including infographic design, involves arranging graphic elements for effective visual communication. The Canva application, a drag-and-drop-based design tool, is an effective solution for product branding and graphic design. The implementation methods of the outreach activities involve monologous methods for content delivery and dialogic methods through discussions. The preparation phase includes problem understanding, collecting reference materials, and scheduling. The execution phase involves a two-day training, with the presentation of Canva's features on the first day and hands-on practice on the second day. Evaluation and final reporting are used to assess participants' understanding and the outcomes of the activities. This initiative successfully trained 20 participants from various educational backgrounds in using the Canva application for product branding design
Features Extraction on Cleft Lip Speech Signal using Discrete Wavelet Transformation Yusuf, Siti Agrippina Alodia; Dinata, Muhammad Imam
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 6 No 2 (2024): August
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i2.545

Abstract

Cleft is one of the most common birth defects worldwide, including in Indonesia. In Indonesia, there are 1,596 cleft patients, with 50.53% having a cleft lip and palate (CL/P), 24.42% having a cleft lip (CL), and 25.05% having a cleft palate (CP). Individuals with clefts encounter difficulties with resonance and articulation during communication due to dysfunctions in the oral and nasal cavi-ties. This study investigates various types of mother wavelets as feature extractors for cleft speech signals. Five different mother wavelets, namely Symlet order 2, Reverse Biorthogonal order 1.1, Discrete Meyer, Coiflet order 1, and Biorthogonal order 1.1 are analyzed. This work aims to find the best type of mother wavelet. The extracted features are statistical features, such as mean, me-dian, standard deviation, kurtosis, and skewness. The dataset used in this study consists of 200 sound signals from 10 individuals with cleft conditions and 10 normal volunteers. To assess the performance of the extractor, classification is performed using K-Nearest Neighbor (KNN) and K-Fold cross-validation. The experimental results indicate that the Reverse Biorthogonal order 1.1 mother wavelet achieves the highest accuracy compared to other types of mother wavelet, where the accuracy is 93%, with sensitivity and specificity of 94% and 92%, respectively.
Speech Recognation Penderita Bibir Sumbing di Kabupaten Sumbawa Anggreni, Anggreni; Yusuf, Siti Agrippina Alodia; Dinata, Muhammad Imam; Sulistianingsih, Nani
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): Desember
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v4i2.673

Abstract

Kegagalan bersatunya dua sisi bagian rongga mulut dengan sempurna pada masa kehamilan mengakibatkan adanya celah pada langit-langit mulut (palatoschisis), dan menjadi kelainan bawaan pada bibir bagian atas disebut sebagai sumbing bibir (labioschisis). Bibir sumbing dapat dibedakan dalam dua kondisi yaitu sumbing bibir komplit mengakibatkan kelainan pda gusi, bantalan gigi (prosesus alveolis), langit-langit mulut (palatum) dan lubang hidung (nostril). Indonesia sebagai salah satu negara di Asia Tenggara menduduki peringkat ke tujuh, dengan 20,4 % penduduk menderita bibir sumbing dan lelangit. Dalam kaitan dengan kelahiran per tahun, prevalensi bayi lahir dengan bibir sumbing dan lelangit ditemukan semakin tinggi yaitu lebih dari 8.900 bayi lahir dengan bibir sumbing dan lelangit per tahun(Kemenkes RI, 2018). Kabupaten Sumbawa yang terdapat di Provinsi Nusa Tenggara Barat merupakan salah satu kabupaten dengan jumlah 21 orang penderita terdaftar sebagai calon pasien di Rumah Sakit Umum Sumbawa Besar. Pengabdian Masyarakat ini bertujuan untuk mengaplikasikan penggunaan Sistem Pengenalan Suara (Speech Recognation) pada penderita bibir sumbing berfokus pada pengucapan Huruf P. Data suara pengucapan kata kapak, paku dan atap diperoleh dari 7 orang penderita bibir sumbing di Kabupaten Sumbawa. Setiap kata diulang sebanyak 15 kali pengucapan. Metode K-nearest neighbor (KNN) digunakan untuk mengevaluasi performa dari . Hasil eksperimen menunjukkan akurasi masing-masing kata sebesar 90% untuk atap, 71% untuk kapak, dan 90% untuk paku. Akurasi keseluruhan sistem pengenalan adalah 84%. Dengan adanya sistem ini diharapkan dapat menjadi Solusi bagi orang terdekat penderita dalam mengoreksi ucapan penderita terkait huruf P.
OPTIMALISASI LAYANAN HOTLINE KESEHATAN MELALUI SISTEM INFORMASI BERBASIS TEKNOLOGI PEMROSESAN BAHASA ALAMI Dinata, Muhammad Imam; Rizkillah, Muhammad
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.6133

Abstract

Layanan hotline kesehatan mental menjadi solusi penting dalam menangani krisis psikologis secara cepat dan anonim. Namun, penilaian tingkat urgensi percakapan masih bergantung pada intuisi manusia yang rentan terhadap bias dan keterlambatan. Penelitian ini mengembangkan sistem berbasis Natural Language Processing (NLP) dengan model BERT untuk mengklasifikasikan tingkat urgensi percakapan pada layanan hotline ke dalam tiga kategori: rendah, sedang, dan tinggi. Sistem diimplementasikan dalam antarmuka berbasis web menggunakan Flask, dengan backend berbasis Python dan database MySQL. Penelitian menggunakan pendekatan dengan model Agile, dan dataset terdiri dari 150 percakapan yang telah dilabeli secara manual. Hasil pengujian menunjukkan akurasi model mencapai 70%, dengan precision dan recall tertinggi pada kategori "rendah". Sistem ini mampu melakukan klasifikasi real-time dan memberikan rekomendasi kepada operator. Implementasi awal menunjukkan bahwa sistem ini meningkatkan efisiensi dan objektivitas layanan. Penelitian ini memberikan kontribusi terhadap digitalisasi layanan kesehatan mental dan menunjukkan potensi NLP dalam intervensi krisis berbasis teks
Co-Authors Anggreni, Anggreni Arif Rahman Idham Muhammad Rizkillah Nani Sulistianingsih Yusuf, Siti Agrippina Alodia