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All Journal Jurnal Komputer Terapan Jurnal Informatika Universitas Pamulang Madani : Indonesian Journal of Civil Society Journal of Computer and Information System (J-CIS) Jurnal Pengabdian kepada Masyarakat Indonesia (JPKMI)
Nur, Nahya
Universitas Sulawesi Barat
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Nursing Physics Public Health

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Sistem Pakar Diagnosis Penyakit Stunting pada Balita menggunakan Metode Forward Chaining Farid Wajidi; Nahya Nur
Jurnal Informatika Universitas Pamulang Vol 6, No 2 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i2.11938

Abstract

Stunting is a condition that occurs in toddlers that fails to grow as a result of nutritional deficiencies so that the height or length of the child's body is not normal for his age. Malnutrition occurs from the moment the baby is in the womb and in the early stages of the baby is born, but the stunting condition is only apparent after the baby is two years old. Currently, the problem occurs a lack of maternal knowledge of the importance of child nutrition during the first 1000 days of life and poor sanitation of the daily environment. Therefore, an expert system is designed to diagnose stunting disease early in children. The method used in expert systems is forward chaining. Expert systems provide diagnostic output as well as user history information, solutions, and processing of user history data. The expert system developed is helpful to help people in diagnosing stunting diseases easily and quickly, where the accuracy system is equal to 91%.
Implementasi SPK untuk Pemilihan Konsentrasi Studi Mahasiswa menggunakan AHP-TOPSIS wahyuni wahyuni rahman; Nahya Nur; Sugiarto Cokrowibowo
Journal of Computer and Information System ( J-CIS ) Vol 3 No 2 (2020): J-CIS Volume 3 No. 2 2020
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jcis.v2i1.721

Abstract

Pemilihan konsentrasi studi mahasiswa masih sering terjadi kesalahan karena pemilihannya yang dilakukan secara asal-asalan dengan mengikuti pilihan temannya atau saran dari orangtuanya tanpa mempertimbangkan kemampuan dan bakat yang dimiliki sendiri oleh mahasiswa tersebut sehingga masih banyak mahasiswa yang menyesal dengan pilihan konsentrasi yang sudah dipilihnya. Dari masalah tersebut dibutuhkan suatu SistemPendukung Keputusan (SPK) yang dapat membantu mahasiswa dalam menentukan keputusan untuk memilih konsentrasi studi sesuai dengan kriteria Minat Bakat, Jurusan Sebelumnya dan Pekerjaan. Metode yang digunakan dalam Sistem Pendukung Keputusan (SPK) adalah metode Analytic Hierarchy Process (AHP) digunakan untuk menentukan bobot dari setiap kriteria dan subkriteria kemudian Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) digunakan untuk melakukan perangkingan hasil pemilihan konsentrasi studi mahasiswa. Dari pilihan rekomendasi konsentrasi yang diberikan oleh SPK diharapkan agar mahasiswa tidak lagi menyesal dengan pilihan konsentrasi yang sudah diambil.
Perbandingan Metode k-NN dan Naïve Bayes dalam Klasifikasi Penentuan Calon Pendonor Darah Nahya Nur; Asmawati; Nur Syahra
Journal of Computer and Information System ( J-CIS ) Vol 4 No 1 (2021): J-CIS Volume 4 Issue 1 2021
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (371.502 KB) | DOI: 10.31605/jcis.v4i1.875

Abstract

Donor darah adalah proses pengambilan darah dari seorang yang sehat dengan dinyatakan memenuhi syarat dengan meninjau beberapa faktor seperti seperti pengukuran tekanan darah, golongan darah, kadar hemoglobin (Hb), status pendonor, konsultasi medis dan sebagainya. Klasifikasi adalah proses menemukan fungsi atau model yang dapat membedakan suatu konsep atau kelas data untuk memprediksi kelas suatu objek yang tidak diketahui. Penelitian ini dilakukan untuk mencari metode terbaik berdasarkan perbandingan nilai akurasi menggunakan 100 data latih donor darah dari RSUD Majene yang diproses dengan mengimplementasikan metode K-Nearest Neighbor dan Naive Bayes. Hasil analisis menunjukkan bahwa algoritma K-Nearest Neighbor menunjukkan performa yang lebih baik dengan tingkat akurasi sebesar 86% sedangkan algoritma Naïve Bayes memperoleh nilai akurasi sebesar 76%.
Pengoptimalan Penghitungan Keuntungan Produksi menggunakan Algoritma Genetika Syarkia Yunus; Nahya Nur; heliawaty hamrul
Journal of Computer and Information System ( J-CIS ) Vol 4 No 1 (2021): J-CIS Volume 4 Issue 1 2021
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (295.919 KB) | DOI: 10.31605/jcis.v1i1.984

Abstract

Perkembangan ilmu pengetahuan dan teknologi yang semakin maju di era sekarang memunculkan berbagai permasalahan baru pula. Hal tersebut sangat dirasakan oleh para pelaku industri. Hal seperti ini tentu saja akan memberi tuntutan tersendiri pada para pelaku bisnis, sehingga dituntut untuk dapat mengambil langkah yang bijaksana dari pilihan-pilihan alternatif yang ada untuk mendukung keputusan agar tujuan perusahaan dapat tercapai. Adapun sampel yang akan menjadi tempat penelitian ini adalah perusahaan sabun mapaccing. Namun perusahaan ini tergolong masih baru, sehingga tentu saja perhitungan laba/kentungan pada perusahaan ini masih menggunakan cara manual. Cara seperti ini tentu saja tidak akan mampu memberikan hasil yang akurat dan cepat melihat banyaknya konsumen perusahaan tentu saja harus mencari solusi yang efektif untuk menangani masalah tersebut. Berdasarkan permasalahan pada setiap perusahaan, adanya optimasi keuntungan menjadi hasil utama dalam proses produksi pada perusahaan. Perhitungan dan analisis yang tepat sangat dibutuhkan untuk mendukung tercapainya keuntungan yang maksimal dari perusahaan. Maka dari itu, dibutuhkan sebuah yang digunakan untuk mendapatkan hasil optimasi keuntungan maksimum yang akurat dan efisien, dan salahsatu hal yang daoat diaplikasi adalah dengan penerapan algoritma genetika untuk melakukan optimasi laba/keuntungan disebuah perusahaan atau industry.
Pelatihan Microsoft Word dan Microsoft Excel pada Siswa SMK Negeri 1 Tinambung Nahya Nur; Sulfayanti Sulfayanti; Arnita Irianti
Madani : Indonesian Journal of Civil Society Vol. 4 No. 2 (2022): Madani, Agustus 2022
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v4i2.1455

Abstract

The development of technology has changed the writing and data storage media from physical to digital form. This is also supported by the development of the world of engineering software which is now able to create and facilitate various human needs through computer applications. The Informatics Study Program, Faculty of Engineering, University of West Sulawesi, through a community service program, carried out computer application training activities to operate the two applications. This service activity aims to add insight and knowledge to the community, especially Vocational High School students on the use of computer applications, especially Microsoft Word and Microsoft Excel. The activities carried out can be said to be successful based on the achievements of the activities evaluated by looking at the abilities of the participants. As a result, this activity was able to help participants gain additional knowledge about Microsoft Word and Microsoft Excel applications, as well as provide opportunities for students to gain experience being involved in training activities according to their field of knowledge.
Sistem Deteksi Penggunaan Masker secara Real Time menggunakan Metode Eigenface dan Support Vector Machine Nahya Nur; Indra Indra; Farid Wajidi; Iin Aisyah Khofifah
Jurnal Komputer Terapan Vol. 8 No. 2 (2022): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (499.23 KB) | DOI: 10.35143/jkt.v8i2.5449

Abstract

At the beginning of 2020, Indonesia was shocked by the outbreak of a virus called Covid-19. One of the measures to prevent the spread of the epidemic is to wear a mask. In this research, a real-time mask detection system will be developed using eigenface and support vector machine (SVM). There are three main stages in this research, namely reading the image through the camera, calculating the eigenvalues, and classifying using SVM. The results of the classification consist of two classes, namely masked and unmasked. In general, if the eigenvalues ​​of the testing image are closer to the masked image, the output is masked and vice versa. The results of the research are quite good where the test is carried out through several test scenarios including considering lighting conditions, use of accessories, object distance from the camera, and so on. Most of the results obtained through system testing can distinguish masked and unmasked faces in real time.
Implementasi Algoritma Random Forest Regression untuk Memprediksi Hasil Panen Padi di Desa Minanga Nahya Nur; Farid Wajidi; Sulfayanti Sulfayanti; Wildayani Wildayani
Jurnal Komputer Terapan Vol. 9 No. 1 (2023): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v9i1.5917

Abstract

Minanga Village, Bambang District, Mamasa Regency, the people of which cultivate rice plants, usually the yields fluctuate each season, which often decreases or increases unstable. This research is expected to assist in predicting rice yields in accordance with pre-existing criteria and data such as land area, number of seeds, type of fertilizer, rainfall, pests and weeds, pest and weed control, and the rice planting system used (jajar legowo) , by applying the Random Forest Regression algorithm. Evaluation of algorithm performance is measured using Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE) and the coefficient of determination (R²), the results of the Random Forest model obtained from 9 trees, the variable that has the highest value on the variable importance is the variable land area. So that from this model an accuracy value of 95.11% is obtained, the MAPE value in this model is 4.884%, the RMSE value is 0.250 and the R² value is 0.99.
Pelatihan Sitasi Karya Ilmiah Menggunakan Mendeley Sulfayanti Faharuddin Situju; Nahya Nur; Heliawaty Hamrul; Nurdina Rasjid; Dian Megah Sari
Madani : Indonesian Journal of Civil Society Vol. 6 No. 1 (2024): Madani : Februari 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v6i1.2078

Abstract

Writing of scientific paper is done by following specified rules and regulations. In reality there are many students at the Faculty of Engineering, University of Sulawesi Barat who do not understand this well, for example: not paraphrasing quotations and not including reference sources correctly. Mendeley application can help students in writing scientific papers or final assignments but it still underutilized by students. This shows the importance of reference citing skills and utilizing the Mendeley application. So, it is necessary to conduct scientific paper citation training. The training was done through planning, training and evaluation activities. Planning aims to prepare and determine the needs during the training. The main activity, training, was organized for two days using a webinar concept on the first day which focused on providing material for preparing scientific work references and a training concept on the second day which focused on practice using Mendeley and coaching research proposals. Last activity, an evaluation was carried out to measure the successfulness of the training and further plans related to similar activities. The results of the training activities showed the participation of 68 students on the first day and 36 students on the second day. The results of the survey showed 100% of students who participated in training felt the benefits of the training therefore they hoped similar activities could be held every year. Another evaluation result is that student supervision should be done in small groups, so the reception of material more effective regarding how to cite scientific papers.
Pemanfaatan Sistem Informasi Edukasi Mitigasi Bencana pada KSR PMI Unit Markas Majene Nahya Nur; Farid Wajidi; Ade Mulawarman; Muh. Adrian; Rifky Gunawan
Jurnal Pengabdian kepada Masyarakat Indonesia (JPKMI) Vol. 2 No. 3 (2022): Desember : Jurnal Pengabdian Kepada Masyarakat Indonesia (JPKMI)
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpkmi.v2i3.726

Abstract

The availability of information related to disasters is one of the efforts so that the public better understands the actions that must be taken to minimize the risks that occur. However, the availability of this information, especially in the Majene Regency area, is currently still quite minimal. In fact, Majene is one of the areas with a fairly high Disaster Risk Index. This activity embraces the Voluntary Corps (KSR) PMI Majene Headquarters Unit as a partner considering that KSR is one of the organizations engaged in the humanitarian field and actively participates in disaster management. The activities carried out include the use of a disaster education information system by providing training to KSR members in managing the system and creating disaster education content. The results of the activities obtained show an increase in the ability of KSR members in terms of management and content creation using Canva and hopes that the disaster education information system that has been built can continue to be used for the dissemination of disaster information.
Analisis Performa K-Nearest Neighbor Dalam Mengklasifikasi Sentimen Pengguna Aplikasi PeduliLindungi Sulfayanti; -, Ika Nurul Fadhillah; Nahya Nur
Journal of Computer and Information System ( J-CIS ) Vol 7 No 1 (2024): J-CIS Vol. 7 No. 1 Tahun 2024
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jcis.v7i1.3767

Abstract

Virus Corona 19 (Covid-19) merupakan inveksi vius menular yang kini telah menyebar ke berbagai negara, termasuk Indonesia. Pemantauan penyebaran Covid-19 di Indonesia ditangani langsung oleh Pemerintah Indonesia khususnya oleh Kementerian Komunikasi dan Informatika (KOMINFO) dengan pembuatan aplikasi PeduliLindungi yang dapat diunduh di Google Play Store. Pengguna memberikan ulasan atau komentar mereka tentang aplikasi dengan tujuan untuk mengevaluasi dan meningkatkan kualitas produk kedepannya. Salah datu cara dalam mengevaluasi ulasan adalah dengan menganalisis sentiment ulasan tersebut. Analisis terhadap sentiment ulasan dilakukan untuk menentukan apakah opini atau komentar terhadap suatu permasalahan atau isu terkait topik tertentu memiliki kecenderungan positif, negatif, atau netral. Sehingga peneliti ingin mengetahui sejauh mana gambaran umum masyarakat mengenai Aplikasi PeduliLindungi dengan memanfaatkan hasil analisis ini dengan melakukan teknik klasifikasi terhadap ulasan PeduliLindungi menggunakan Algoritma K-Nearest Neighbor. Hasil pengklasifikasian sentimen yang diperoleh yaitu opini kategori positif sebesar 58,66%, sentimen dengan kategori negatif sebesar 26,12%, dan sentimen dengan kategori netral sebesar 15,22% ulasan dari total 7.500 ulasan. Hasil ini menunjukkan bahwa masyarakat percaya dengan aplikasi PeduliLindungi dan menilai bahwa aplikasi tersebut layak untuk diinstal. Performa algoritma K-Nearest Neighbor dalam mengklasifikasi sentimen pengguna menghasilkan akurasi sebesar 60,66%, dengan nilai presisi 64%, recall 62,79%, dan F1-score 54,44%.
Co-Authors -, Ika Nurul Fadhillah Ade Mulawarman Agus Zainal Arifin Alifia Puspaningrum Arnita Irianti Asmawati Dian Megah Sari Dian Megah Sari Faharuddin Situju, Sulfayanti Farid Wajidi Heliawaty Hamrul Heliawaty Hamrul, Heliawaty Iin Aisyah Khofifah Indra Muh. Adrian Nur Syahra Nurdina Rasjid Rasjid, Nurdina Rifky Gunawan Riza, Ozzy Secio Sugiarto Cokrowibowo Sulfayanti Sulfayanti Syarkia Yunus wahyuni wahyuni rahman Wildayani Wildayani