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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Jurnal Pendidikan dan Pemberdayaan Masyarakat JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JURNAL REKAYASA TEKNOLOGI INFORMASI SINTECH (Science and Information Technology) Journal METIK JURNAL JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer
Hamdani Hamdani
Universitas Mulawarman
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering

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Implementasi Server Pulsa Menggunakan Multi Gateway Muhammad Olly; Hamdani Hamdani; Awang Harsa Kridalaksana
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 10, No 2 (2015): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (494.04 KB) | DOI: 10.30872/jim.v10i2.184

Abstract

Pengisian pulsa sudah menjadi kebutuhan utama pada pengguna ponsel (telepon seluler). Pulsa adalah satuan dalam perhitungan biaya penggunaan layanan jaringan seluler. Alat yang digunakan dalam pengisian pulsa berupa voucher fisik dan elektrik (elektronik) melalui pengisian terprogram. Dan cara pengisian pulsa yaitu secara konvensional dengan langsung datang ke gerai pulsa dan tersistem seperti server pulsa. Transaksi melalui server pulsa saat ini hanya dapat dilakukan via SMS (Short Message Service) ataupun via instant messaging (IM). Penelitian ini bertujuan untuk membuat server pulsa yang inovatif dan menggunakan multi gateway sehingga memudahkan user dalam melakukan pengisian pulsa. Gateway yang digunakan ialah berupa SMS, USSD, IM, Facebook dan Twitter. Hasil akhir dari penelitian ini berupa server pulsa menggunakan multigateway yang dapat melakukan pengisian pulsa melalui jejaring sosial yang merupakan inovasi baru pada server pulsa.
Sistem Pendukung Keputusan Wisata Kuliner Dengan Visualisasi Geografi Hamdani Hamdani
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 5, No 1 (2010): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (191.343 KB) | DOI: 10.30872/jim.v5i1.46

Abstract

Pariwisata Kuliner kini menjadi semakin populer di hidup warga negara untuk melakukan kunjungan ke tempat-tempat makanan yang menarik. Banyak perspektif yang berbeda dalam berbagai kebutuhan untuk menemukan tempat yang cocok untuk makan, yang jenis makanan, lokasi, bugdet, dan lainnya. Ini sangat beragam kebutuhan yang harus sesuai dengan menggunakan sistem pendukung keputusan untuk kuliner Wisata kuliner rekayasa sistem pendukung keputusan yang melibatkan data eksternal, model yang digunakan sebagai acuan dalam penilaian dan bobot, dan desain dialog layar terminal, akan menghasilkan sebuah sistem yang memberikan penilaian terhadap setiap kuliner tempat-tempat yang akan cocok untuk kunjungan wisatawan didasarkan pada kuliner kebutuhan pengguna. Sistem pendukung keputusan ini membantu melakukan penilaian setiap kriteria, membuat perubahan pada data kriteria, pemodelan nilai, dan juga komponen dan pembobotan penilaian seleksi. Ini berguna untuk memudahkan pengambil keputusan yang terkait dengan masalah menentukan tempat wisata kuliner di Yogyakarta, sehingga mereka akan mendapatkan yang terbaik dan paling layak tempat kuliner bagi pengguna berdasarkan sistem.
Weighting Model for Group Decision Support System: A Review Hamdani Hamdani; Retantyo Wardoyo; Khabib Mustofa
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp962-974

Abstract

This paper was conducted a survey of research findings related to decision-making in groups using weighting techniques This paper conducts a survey of research findings related to decision-making in groups using weighting techniques, therefore, a new weighting model can be proposed.. In order to make a decision, this model works based on the weighting parameters, criteria or decision makers (DM) to give ranking preference in the decision results. Weighting could be done objectively or subjectively by statistical calculations. Subjective weighting based on an understanding or expertise of the decision-making process, furthermore, a numerical value was needed to make it objective. The previous weighting models need to be modified for the development of group decision support systems (GDSS). It is required to accommodate the interests of all stakeholders to link the DM relationship. We formed several groups of weighting methods that currently use for the trend of group decision-making (GDM). It showed that the classical multi-criteria decision-making (MCDM) models are still dominant in solving GDSS problems, therefore, it was necessary to apply hybrid MCDM with an approach method of stakeholders models and social networks (SN) to improve decision model that has been applied in the previous research.
Analysis of Color Features Performance Using Support Vector Machine with Multi Kernel for Batik Classification Edy Winarno; Wiwien Hadikurniawati; Anindita Septirini; Hamdani Hamdani
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

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

Abstract

Batik is a sort of cultural heritage fabric that originated in many areas of Indonesia. Each area, particularly Semarang in Central Java, has its own batik design. Unfortunately, due to a lack of knowledge, not all residents are able to recognize the types of Semarang batik.  Therefore, this study proposed an automated approach for classifying Semarang batik. Semarang batik was classified into five categories according to this method:  Asem Arang, Blekok Warak, Gamblang Semarangan, Kembang Sepatu, and Semarangan. Since color was able to distinguish batik patterns, it is necessary to analyze color features based on the color space in order to generate discriminative features.  Color features were produced based on the RGB, HSV, YIQ, and YCbCr color spaces. Four different kernels were used to feed these features into the Support Vector Machine (SVM) classifier. The experiment was conducted using a local dataset of 1000 batik images classified into five classes (each class contains 200 images).  In order to evaluate the method, cross-validation was performed using a k-fold value of 10. The results showed that the proposed method could reach an accuracy of 1 in all SVM Kernels when employing the YIQ color space, which was consistent across all tests.
The Implementation of Training Programs to Make Tumpeng for the Community Hamdani Hamdani; A Ismail Lukman; Albert Richart Singal; Mustangin Mustangin; Hepy Tri Winarti; Muhammad Alisalman
JPPM (Jurnal Pendidikan dan Pemberdayaan Masyarakat) Vol 9, No 2 (2022): November 2022
Publisher : Departement of Nonformal Education, Graduate Scholl of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jppm.v9i2.50039

Abstract

The background of this research is the Empowerment of Citizens Learning through a Training Program to make Tumpeng in Sanggar Kegiatan Belajar (SKB) Samarinda give an influence on Knowledge, Attitudes and Skills. The purpose of this study is how the process of implementing the training program makes Tumpeng rice, as well as reviewing factors that inhibit and support the factors and impacts of the Training Program to make Tumpeng in SKB Samarinda City. The type of research used is the Type of Qualitative Research Method. The data sources in this study are the Head of Sanggar Kegiatan Belajar (SKB) Samarinda, Tutors and Learners. Data Collection techniques using Observation, Interviews and Documentation. Data Analysis techniques include Data Collection, Data Reduction, Data Display and Conclusion Drawing. The results of this research are (1) program planning is carried out through the identification of needs to the community (2) the implementation of the program is related to the learning process using methods of delivering material and practice to improve knowledge and skills and (3) evaluation is implemented to see the success of the program. Supporting Factors for Training Programs make Tumpeng is an excellent Learners Response, The Presence of Competent and Experienced Speakers. Factor The existence of other jobs such as gardening.
The Clustering Tindak Kekerasan Dalam Rumah Tangga Di Kota Samarinda Menggunakan Algoritma K-Means Roni Stepanus Ginting; Hamdani Hamdani; Anindita Septiariani; Faza Alameka
METIK JURNAL Vol 6 No 2 (2022): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v6i2.378

Abstract

Peran Kepolisian Resort Samarinda dalam membantu keamanan dan penegakan hukum sesuai dengan Pasal 5 Undang-Undang No. 23 Tahun 2004 dapat menggunakan data kdrt untuk clustering tingkat kdrt berdasarkan tinggi, sedang dan rendah. Clustering atau mengelompokkan data dapat dilakukan dengan menerapkan algoritma K-Means. Penerapan algoritma ini menggunakan 3 metode perhitungan jarak yaitu, Euclidean Distance, Minkowski Distance dan Manhattan Distance Dan hasil perhitungan algoritma kmeans dengan menggunakan Euclidean Distance Mendapatkan 2 Cluster di C1,9 cluster di C2 dan 1 cluster di C3,Selanjutnya menggunakan Manhattan Distance Dan hasil yang di dapat yaitu 3 Cluster di C1, 8 cluster di C2 dan 1 cluster di C3 dan yang terakhir Menggunakan , Minkowski Distance Distance Mendapatkan 2 Cluster di C1,9 cluster di C2 dan 1 cluster di C3. Penggunaan 3 metode ini dimaksudkan untuk mengetahui perhitungan jarak yang lebih ideal untuk digunakan. Selain menggunakan metode perhitungan jarak, digunakan juga metode pengukuran jarak yaitu SSE (Sum of Squared Errors) dan ketiga metode perhitungan tersebut mendapatkan hasil SSE (Sum of Squared Errors) nya sebagai berikut.Euclidean Distance=1,2535, Minkowski Distance=1,2418 dan Manhattan Distance=5,7154.
Penentuan Kelayakan Masyarakat Miskin Penerima Bantuan Menggunakan Metode Naïve Bayes (Studi Kasus: Kabupaten Penajam Paser Utara) Nur Madia; Anindita Septiarini; Heliza Rahmania Hatta; Hamdani Hamdani; Masna Wati
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 1 (2023): Januari 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.1.36-49

Abstract

Contents Poverty is the inability to meet the necessities of life, such as food, clothing, and shelter. The poor have an average monthly per capita expenditure below the poverty line. The case of poverty in Indonesia is still unresolved; the Government continues to try to give the best to the entire community so that the problem of poverty can at least continue to decrease. One form of government concern for the poor is the assistance program provided to the poor. This study will classify based on data from the North Penajam Paser (PPU) community obtained from the results of the National Socio-Economic Survey (Susenas) to know how the Naïve Bayes method is in determining the eligibility of the poor recipients of assistance. Based on the research that has been carried out, a system for determining the poor recipients of assistance is produced, where the test results get the highest accuracy in the third scenario, namely 60% or 328 training data and 40% or 218 test data, where the accuracy obtained is 77.98%.
Pemilihan Lokasi Lahan Perkebunan Tanaman Kakao Menggunakan Metode WP dan TOPSIS Muhammad Zaini; Hamdani Hamdani; Amin Padmo Azam Masa
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 7, No 1 (2023): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v7i1.10588

Abstract

Perkebunan merupakan sektor penting dalam perekonomian Indonesia, salah satunya yaitu perkebunan kakao. Dalam membudidayakan tanaman kakao ada beberapa hal yang harus diperhatikan diantaranya aspek pemilihan lahan. Kesalahan dalam memilih lokasi lahan perkebunan kakao dapat menyebabkan rendahnya hasil produksi kakao. Penelitian ini mebangun sistem pemilihan lokasi lahan kakao menggunakan metode Weighted Product (WP) untuk menghitung normalisasi bobot setiap kriteria dan metode Technique for Others Preference by Similarity to Ideal Solution (TOPSIS) untuk pemeringkatan altenatif lokasi terbaik. Kriteria yang digunakan yaitu kemiringan lereng, kedalaman solum tanah, pH tanah, tekstur tanah, dan kelembapan udara. Alternatif pada penelitian ini berjumlah delapan wilayah perkebunan kakao di provinsi Kalimantan Timur. Penelitian diharapkan dapat membantu memberikan rekomendasi lokasi lahan yang sesuai untuk perkebunan kakao. Berdasarkan hasil penelitian yang telah dilakukan, metode WP dan TOPSIS berhasil diterapkan di dalam sistem pendukung keputusan pemilihan lokasi lahan perkebunan kakao dengan hasil rekomendasi tertinggi yaitu Desa Datah Bilang Ilir dengan nilai sebesar 0.689898.
Sara Detection on Social Media Using Deep Learning Algorithm Development M. Khairul Anam; Lucky Lhaura Van FC; Hamdani Hamdani; Rahmaddeni Rahmaddeni; Junadhi Junadhi; Muhammad Bambang Firdaus; Irwanda Syahputra; Yuda Irawan
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.5390

Abstract

Social media has become a key platform for disseminating information and opinions, particularly in Indonesia, where SARA (Ethnicity, Religion, Race, and Intergroup) issues can fuel social tensions. To address this, developing an automated system to detect and classify harmful content is essential. This study develops a deep learning model using Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) to detect SARA-related comments on Twitter. The method involves data collection through web scraping, followed by cleaning, manual labeling, and text preprocessing. To address data imbalance, SMOTE (Synthetic Minority Over-sampling Technique) is applied, while early stopping prevents overfitting. Model performance is evaluated using precision, recall, and F1-score. The results demonstrate that SMOTE significantly improves model performance, particularly in detecting minority-class SARA comments. CNN+SMOTE achieves a accuracy of 93%, and BiLSTM+SMOTE records a recall of 88%, effectively capturing patterns in SARA and non-SARA data. With SMOTE and early stopping, the model successfully manages class imbalance and reduces overfitting. This research supports efforts to curtail hate speech on social media, especially in the Indonesian context, where SARA-related issues often dominate public discourse.
KOMBINASI METODE SAW DAN TOPSIS UNTUK MENDUKUNG KEPUTUSAN KESESUAIAN LAHAN PADI Syaffira Rizky Amalia; Hamdani Hamdani; Anindita Septiarini
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 12 No. 3 (2025): Prosisko Vol. 12 No. 3 November 2025
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/prosisko.v12i3.10142

Abstract

Tanaman padi (Oryza Sativa L.) merupakan komoditas tanaman pangan utama di Indonesia, karena sebagian besar penduduk Indonesia makanan pokoknya adalah beras. Salah satu penyebab rendahnya produksi padi di Indonesia, karena umumnya petani masih membudidayakan padi secara tidak tepat, seperti pengolahan tanah atau pemilihan lahan. Kesesuaian lahan dalam pertanian tanaman sangat berpengaruh terhadap produktivitas tanaman. Proses yang dapat dilakukan untuk mendukung keputusan kesesuaian lahan padi adalah membangun sebuahwebsite Sistem Pendukung Keputusan (SPK) dengan menggunakan kombinasi metode Simple Additive Weighting (SAW) dan Technique for Order Performance of Similarity to Ideal Solution (TOPSIS). Kombinasi ini dilakukan dengan cara mengambil rata-rata (µ) dari hasil akhir metode SAW dan TOPSIS. Skor akhir dari masing-masing metode dihitung terpisah, lalu dilakukan rata-rata (µ) dari kedua hasil tersebut untuk mendapatkan peringkat akhir alternatif. Data yang digunakan dalam menentukan kesesuaian lahan padi menggunakan data sebanyak 5 kriteria, yaitu jenis tanah, pH tanah, curah hujan, suhu, irigasi dan perairan. Data alternatif yang digunakan dalam penelitian ada 6 alternatif, yaitu Sungai Kunjang, Sambutan, Samarinda Utara, Palaran, Loa Janan Ilir dan Samarinda Seberang. Tujuan dari penelitian ini adalah untuk membantu memberikan informasi solusi alternatif kepada petani atau kelompok tani dalam menentukan kesesuaian lahan padi. Hasil kombinasi dari metode SAW dan TOPSIS menunjukkan bahwa alternatif dengan nilai akhir tertinggi adalah Samarinda Utara (A3), dengan nilai akhir sebesar 0,7337. Sedangkan, alternatif dengan nilai akhir terendah adalah Sambutan (A2), dengan nilai akhir sebesar 0,4402.
Co-Authors A. Ismail Lukman Agus Qomaruddin Munir Albert Richart Singal Amin Padmo Azam Masa Anam, M Khairul Andri Syafrianto Andrianus Layuk Anindita Septiariani Anindita Septiarini, Anindita Anindita Septirini Awang Harsa Kridalaksana Budi Rahmani Budi Rahmani Citra Tri Angga Dana Pranata Decky Aspandi Latif Didit Suprihanto, Didit Dyna Marisa Khairina Edy Winarno Faza Alameka Hatta, Heliza Rahmania Haviluddin Haviluddin Heliza Hatta Henderi . Hepy Tri Winarti Heru Ismanto Hugo Aprilianto Irwanda Syahputra Junadhi Junadhi Khabib Mustofa Lucky Lhaura Van FC, Lucky Lhaura Muhammad Alisalman Muhammad Bambang Firdaus Muhammad Olly Muhammad Sofian Sauri Muhammad Syarif Abdillah Muhammad Zaini Mustangin Mustangin Ngurah Satria Darmawangsa Nur Madia Puspitasari, Novianti Rahmaddeni Rahmaddeni Retantyo Wardoyo Roni Stepanus Ginting Sayekti Harits Suryawan Sumaini Sumaini Syaffira Rizky Amalia Wati, Masna Widians, Joan Angelina Wiwien Hadikurniawati Yuda Irawan Yulianto Yulianto Zainal Arifin