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Penerapan Algoritma C4.5 Untuk Klasifikasi Status Kesejahteraan Rumah Tangga Keluarga Binaan Sosial Di Kabupaten Bulukumba Mansyur Mansyur; Yuyun Yuyun; Rabiatul Adawiyah
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 9, No 2 (2019): Jurnal Inspiration Volume 9 Issue 2
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v9i2.2514

Abstract

Kemiskinan merupakan salah satu permasalahan dalam upaya peningkatan kesejahteraan di semua daerah. Dengan mengetahui status kesejateraan, memudahkan dalam pengelompokanya. Penelitian ini bertujuan untuk mengklasifikasi status kesejahteran Rumah Tangga, dikabupaten Bulukumba menggunakan  algoritma C4.5. Dalam penelitian ini, kami  menggunakan 10 (sepuluh) atribut yang terdiri dari jenis kelamin, umur, status tempat tinggal, jumlah anggota keluarga, lapangan usaha, jumlah atap terluas, jenis dinding, jenis lantai,  sumber air minum, dan sumber penerangan. Dari hasil analisis, ditemukan  18 (delapan belas) pola untuk menidentifikasi status kesejateraan keluarga. Dariperhitungan  algoritma C.45 diperole sumber air minum adalah indikator utama untuk mengukur tingkat kesejahteraan masyarakat dengan  nilai gain tertinggi 0.322. Kemudian nilai gain terendah terdapat pada atribut usia dengan nilai 0.001.
Klasifikasi Motif Citra Kain Sutera Bugis Mengunakan Metode Markerless Marker Zulfahmiz Abd Gani; Syafruddin Syarif; Yuyun Yuyun
PROtek : Jurnal Ilmiah Teknik Elektro Vol 7, No 2 (2020): PRotek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v7i2.1996

Abstract

Silk is one of the national cultural heritage with various motifs and patterns. This research aims to detect and classify the image of the silk cloth based on motive. This research uses Augemented Reality technology with Markerless Marker Tracking method. To display a 3D object, the proposed method uses a special pattern as a marker to recognize the fabric type. As a research sample, the authors used 10 types of bugis silk motifs. From the test results found that markers can detect fabric motifs in bright rooms and undetectable markers in dim rooms. The best distance in detecting markers is 10 cm – 50 cm.  Meanwhile at a distance of 110 cm, the marker cannot be detected.
Algoritma Multinomial Naïve Bayes Untuk Klasifikasi Sentimen Pemerintah Terhadap Penanganan Covid-19 Menggunakan Data Twitter Yuyun; Nurul Hidayah; Supriadi Sahibu
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 4 (2021): Agustus 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (585.342 KB) | DOI: 10.29207/resti.v5i4.3146

Abstract

Currently, the spread of information Covid-19 is spreading rapidly. Not only through electronic media, but this information is also disseminated by user posts on social media. Due to the user text posted is varies greatly, it’s needs a special approach to classify these types of posts. This research aims to classify the public sentiment towards the handling of COVID-19. The data from this study were obtained from the social media application i.e., Twitter. This study uses a derivative of the Naïve Bayes algorithm, namely Multinomial Nave Bayes to optimize the classification results. Three class labels are used to classify public sentiment namely positive, negative, and neutral sentiments. The stage starts with text preprocessing; cleaning, case folding, tokenization, filtering and stemming. Then proceed with weighting using the TF-IDF approach. To evaluate the classification results, data is tested using confusion matrix by testing accuracy, precision, and recall. From the test results, it is found that the weighted average for precision, recall and accuracy is 74%. Research shows that the accuracy of the proposed method has fair classification levels.
KOMBINASI METODE ANP DAN PROMETHEE DALAM MENENTUKAN PRIORITAS DISTRIBUSI LOGISTIK BENCANA ALAM Mushaf Mushaf; Yuyun Yuyun; Wardi Wardi
Sebatik Vol 25 No 1 (2021): Juni 2021
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (903.154 KB) | DOI: 10.46984/sebatik.v25i1.1337

Abstract

Bencana alam yang kerap terjadi di Indonesia menimbulkan banyak korban jiwa. Kejadian ini membuat masyarakat tergerak untuk menjadi relawan pasca bencana alam terjadi. Namun, kendala yang dialami salah satunya adalah saat pendistribusian bantuan logistik bencana alam. Tidak adanya data terpusat terkait data posko, jumlah korban, kondisi korban, dan kebutuhan korban yang dapat menjadi acuan bagi seluruh relawan membuat para relawan kesulitan menentukan tindakan untuk distribusi bantuan logistik yang menyebabkan distribusi bantuan logistik menjadi lambat dan tidak tepat sasaran. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan (SPK) pendistribusian bantuan logistik bencana alam menggunakan kombinasi metode Preference Ranking Organization Method for Enrichment Evaluation (Promethee) dan Analytic Network Process (ANP). Pada penelitian ini terdapat 6 kriteria yaitu korban berdasarkan jenis kelamin, korban berdasarkan usia, korban berdasarkan kondisi, jarak, kebutuhan pokok, kebutuhan sekunder, dan relawan. Kemudian terdapat 31 total sub kriteria dari masing-masing kriteria. Sistem kemudian diuji menggunakan metode Confusion Matrix. Dari hasil pengujian, diperoleh akurasi sebesar 87,5%. Hasil ini diharapkan dapat membantu pendistribusian bantuan logistik pasca bencana alam
DATA MINING UNTUK PENENTUAN MODEL KELULUSAN MURID SMA PADA PERGURUAN TINGGI NEGERI; STUDI KASUS DI IAIN BONE Irmawati Irmawati; Zahir Zainuddin; Yuyun Yuyun
JIKO (Jurnal Informatika dan Komputer) Vol 3, No 2 (2020)
Publisher : Journal Of Informatics and Computer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v3i2.1800

Abstract

Penelitian ini bertujuan untuk memprediksi tingkat keberhasilan kelulusan murid pada Institut Agama Islam Negeri (IAIN) Bone dengan menggunakan algoritma Naive Bayes dan C.45. Algoritma yang diusulkan untuk mempredikasi kriteria apa saja yang menjadi penentu kelulusan murid  pada penerimaan mahasiswa baru jalur mandiri tahun 2018. Tujuh kriteria yang digunakan sebagai variabel pendukung dalam melakukan analisis. Kriteria tersebuat adalah Tahun Lulus, Pendidikan Orang Tua, Penghasilan Orang Tua, Nilai Ujian Nasional, Nilai Tes, Nilai Wawancara dan Nilai Baca Tulis Huruf Qur’an (BTHQ). Dataset dalam penelitian ini bersumber dari Database Sistem Informasi Akademik (SISFO) IAIN Bone dari Tiga sekolah yaitu SMA 4 Watampone, MAN 1 Bone dan SMKN 1 Watampone. Hasil pengujian menunjukkan bahwa Nilai BTHQ menjadi syarat  utama kelulusan murid SMA jalur mandiri pada IAIN Bone sesuai dengan hasil olahan data training sebanyak 170 dan olahan data testing sebanyak 10. Kedua algoritma menghasilkan Nilai Precision sebesar 100%, Recall  100%, Accuracy 100%. Selain itu, ditemukan pola sequential baru dengan melakukan pengujian ulang berdasarkan hasil urutan kejadian dari variabel Nilai Ujian Nasional, Nilai Tes, Nilai Wawancara dan Nilai Baca Tulis Huruf Qur’an (BTHQ).
DATA MINING SOSIAL KEMASYARAKATAN UNTUK KELENGKAPAN DASBOARD DESA Zahir Zainuddin; Hajar Hasan; Yuyun Yuyun
JIKO (Jurnal Informatika dan Komputer) Vol 4, No 3 (2021)
Publisher : Journal Of Informatics and Computer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v4i3.3861

Abstract

Pemberdayaan masyarakat produktif merupakan upaya untuk memandirikan masyarakat, lewat perwujudan potensi kemampuan yang mereka miliki. Membangun sebuah desa yang lebih maju diperlukan langkah-langkah guna mendorong masyarakat untuk naik kelas. Tujuan penelitian ini adalah untuk mengelompokan penduduk desa dengan menggunakan pendekatan analisis kluster.  Klusterisasi data penduduk  pada Kota Tidore Kepulauan dengan menggunakan metode Rank Reciprocal dan Metode K-means dengan Kriteria sebanyak 38 dan Subkriteria sebanyak 134 yang berasal dari Dinas Sosial Kota Tidore Kepulauan. Hasil penelitian menunjukan bahwa hasil  klusterisasi dari 81 kepala keluarga Desa Bukit Durian Kecamatan Oba Utara Kota Tidore Kepulauan yang di uji, hasil yang peroleh yaitu penduduk berada pada kluster pertama yang memiliki nilai 0,1 yang dapat diartikan sebagai kelompok penduduk yang tidak produktif atau kluster rendah sebanyak 1 kepala keluarga, kluster kedua yang memiliki nilai 0,29 yang dapat diartikan sebagai kelompok penduduk yang kurang produktif atau kluster sedang sebanyak 44 kepala keluarga,  dan kluster ketiga yang memiliki nilai 0,50 yang dapat diartikan sebagai kelompok penduduk produktif  atau kluster Tinggi sebanyak 36 kepala keluarga.
Rekomendasi Strategi Sosialisasi Program Studi Melalui Jalur Undangan Menggunakan Algoritma ID3 dan K-Means Muhammad Azhar Hairudin; Hazriani Zainuddin; Yuyun Wabula
JITCE (Journal of Information Technology and Computer Engineering) Vol 6 No 01 (2022): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.6.01.14-18.2022

Abstract

Based on data obtained from SPAN-PTKIN registrants in 2018 and 2019, the number of interested people through the invitation path who chose the study program at UIN Alauddin as the first choice was 30523 records. Analysis using the ID3 algorithm found that those who interested in the study of religions were more dominant from vocational students. While analysis using the K-Means shows the regions / regencies from which those interested in study programs of religions are spread in 35 regencies / cities. It can be concluded that the socialization of study programs of religions through the invitation path is recommended to be more focused on SMAs that are located in 33 districts / cities as identified in cluster 3. The study programs of religions are prioritized, because these study programs experienced the lowest number of registrants. It is expected that by implementing this recommended strategy, the number of interested prospective new students will draw a significant increase in the future.
Decision support system on quality assessment of the prospective civil servant’s education and training using fuzzy method Aris Susanto; Omar Wahid; Hazriani Hazriani; Yuyun Yuyun
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp519-529

Abstract

This study aims to develop a decision support system using the fuzzy method in order to assess the quality of education and training of prospective civil servants and highlight possible improvement considerations. The assessment consists of six criterias, namely coaches, lecturers, preachers, mentors, examiners, and administrators. Based on the evaluation result of the quality level of each criterion, it is obtained that the top two criterion are examiners and preachers, followed by coaches, lecturers, advisors, and the lowest is organizer. In addition, the quality of the civil servant class III training is better than the class II civil servant training. It also shows that the value of the organizers criterion has different level of satisfactions. Overall, the quality of the training (according to the participants' opinion) was very good with a score of 92.50 for training class II and 95.20 for training class III. Furthermore, it is necessary to conduct research to determine the quality of the training each year by looking at the achievements of the participants. The >system testing obtained an accuracy of 100%, whichs implies that the system can be used to assess the quality of education and training appropriately.
Rancang Bangun Sistem Top-Up Meteran PDAM Berbasis Mikrokontroller Indar Kusmanto; Yuyun; Andani Achmad
Bulletin of Information Technology (BIT) Vol 3 No 3: September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v3i3.314

Abstract

This research aims to build a top-up based PDAM meter tools, which allows users to control water use in their daily needs. This type of research is experimental research where the scope of the problem can be carried out using the literature study method, field data collection methods. The system is made in the form of a prototype. This research produces a product in the form of a tool with a top-up as a payment system. This study uses an RFID sensor as a tool to enter voucher balances into the system. Then arduino uno as a controller of water use through a waterflow sensor and a solenoid valve instead of a faucet to close the water flow. The result of this research is that the device can display information in the form of remaining voucher balances and the amount of water consumption. In this study, water measurement trials have been carried out with an error value of 2.53 percent, and trial charging vouchers worth 20,000 to 100,000, as well as trial use and remaining balance with appropriate results
Klasifikasi Pembibitan Udang Vanamey Yang Ideal Menggunakan Algoritma Naive Bayes Hidayat Hidayat; Wardi; Andani Achmad; Yuyun
Bulletin of Information Technology (BIT) Vol 3 No 3: September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v3i3.316

Abstract

Data mining is the process of finding information by looking for certain patterns or rules from large amounts of data. This study applies the Naïve Bayes algorithm to classify the yield of Vanamey shrimp into three classes, namely successful, less successful and failed from the harvest sample data owned. To facilitate the analysis, the data is divided into 2 categories, namely 90 training data and 10 for testing data. Nine parameters were used, namely the number of distributions, land area, type of disease, water color, soil conditions, season, feed, capital and yields. To validate the classification, we used a confusion matrix to test the accuracy of the algorithm. The test results show an accuracy of 54.4%, 100% precision, and 77.7% recall
Co-Authors Andani Achmad Aris Susanto Hajar Hasan Hamdan Gani Hazriani, Hazriani Hidayat Hidayat Indar Kusmanto Irmawati Irmawati Mansyur Mansyur Mashur Razak Mudinillah, Adam Muhammad Azhar Hairudin Mushaf Mushaf Musliadi K H Najirah Umar Nurul Hidayah Omar Wahid Rabiatul Adawiyah Supriadi Sahibu Syafruddin Syarif Wardi Wardi Wardi Zahir Zainuddin Zahir Zainuddin Zulfahmiz Abd Gani