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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta JIKO (Jurnal Informatika dan Komputer) Informatics for Educators and Professional : Journal of Informatics Jurnal Teknik Informatika STMIK Antar Bangsa Jurnal Sisfokom (Sistem Informasi dan Komputer) Petir IJISTECH (International Journal Of Information System & Technology) Jurnal Mantik Jurnal Ilmu Komputer dan Bisnis Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi International Journal of Educational Research and Social Sciences (IJERSC) SPEED - Sentra Penelitian Engineering dan Edukasi Journal of Innovation Research and Knowledge Paradigma Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Riset Sistem Informasi
Suhardjono S
Universitas Bina Sarana Informatika, Indonesia
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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ANALYSIS OF NIST METHODS ON FACEBOOK MESSENGER FOR FORENSIC EVIDENCE Suhardjono; Arman Syah Putra; Nurul Aisyah; V.H. Valentino
Journal of Innovation Research and Knowledge Vol. 1 No. 8: Januari 2022
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (229.942 KB)

Abstract

The background of this research is how to find evidence from forensics on Facebook Messenger using the NIST method. With this method, it can be described one by one the stages that will be used to prove the chat as forensic evidence. The method used in this research is to use the literature review method and perform an analysis of Facebook Messenger which will be used as a test site in this research so that it can be proven that there is forensic evidence. The problem raised in this research is how to find the problem of forensic evidence on Facebook Messenger so that it can be used as evidence to prove a crime. The purpose of this study is to prove that using the NIST method, you can find forensic evidence against Facebook Messenger so that it can be used as evidence at a later date.
Analysis of Internet Utilization for the Community in Terms of Rural and Urban Conditions in the Province of Indonesia Suhardjono S; Pandu Adi Cakranegara; Ade Risna Sari; Rudy Max Damara Gugat; Nanny Mayasari
Jurnal Mantik Vol. 6 No. 3 (2022): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i3.3013

Abstract

The advancement of information and communication technology necessitates the establishment of internet telecommunications networks to serve all regions of Indonesia. The necessity for internet connection has evolved into a pattern of community requirements toward a technologically savvy and digital society. The government of Indonesia has carried out equitable distribution of internet networks in order to assist the efforts of the 4.0 technology era. The purpose of this research is to examine how Indonesians use the internet, particularly in rural and urban locations across the country. The data visualizations are used in the analysis for each province in Indonesia to determine the purpose of internet use in the community. by understanding the purpose of internet use in rural and urban populations across all provinces in Indonesia in order to acquire statistics on telecommunications development and the most prevalent use that is useful in people's daily lives The data is based on Central Statistics Agency data on internet use in rural and urban areas throughout 34 Indonesian provinces. According to the findings, the most common reasons for people in Indonesia to use the internet are for social media purposes, for information and news, and for entertainment.
Audit Sistem Informasi Menggunakan Framework COBIT 4.1 Pada Badan Kependudukan dan Keluarga Berencana Nasional Ispandi Ispandi; Gilang Purnama Adji; Adjat Sudradjat; Rino Ramadan; Suhardjono Suhardjono
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol 7 No 1 (2022): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Desember 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v7i1.1989

Abstract

National Population and Family Planning Agency is one of the government agencies that implements an information system for its operations. Therefore, the National Population and Family Planning Agency requires a management system that is in accordance with the existing infrastructure. Therefore, this study aims to measure the quality of information system management that focuses on procurement, management, and maintenance. Referring to the problems that occurred, the appropriate problem formulation for this research is to carry out an information system audit with the COBIT 4.1 framework and use the Delivery and Support (DS) domain, which in this study are: DS1, DS2, DS3, DS4, DS5, DS10 and DS13. After the audit process is complete, it will get the current maturity value (current maturity level), expected maturity level (expected maturity level) and value (GAP). DS13 became the domain with the highest acquisition value of maturity level with a value of 3.95, while DS3 became the lowest domain with the acquisition of a maturity level value of 3.37. The final result of the audit process that has been carried out is that the current maturity level is 3.61 which is included on a scale of 4 or Managed and Measurable with an expected maturity level of 3.5. So in this study there is no GAP between Current Maturity Level and Expected Maturity.
Prediction Of Infant Mortality Using The Decission Tree And Genetic Algorithm Methods Suhardjono Suhardjono; Adjat Sudradjat; Bilal Abdul Wahid; Hari Sugiarto; Hafis Nurdin
Paradigma Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1819

Abstract

One of the things that plays a role in reducing infant mortality is the government. Based on infant mortality data in Jakarta in 2018 that has been previously tested with the decision tree algorithm, the update in this study is to use the genetic algorithm. The purpose of the update is to increase the accuracy of the results to be maximized. From the test results with the DT algorithm optimized by GA, the maximum accuracy value is 100%, and each attribute has a weight value of 1 where the value is the maximum value. After obtaining maximum results, the data will be used to reduce infant mortality, especially in Jakarta
Classifying Half-Unemployment Levels in Indonesian Provinces: A K-Means Approach for Informed Policy Decisions Suhardjono Suhardjono; Hari Sugiarto; Dewi Yuliandari; Adjat Sudradjat; Luthfia Rohimah
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 2 (2023): September 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i2.7390

Abstract

Half-level unemployment refers to individuals who work part-time and are not fully employed. Increasing the half-poverty rate from year to year can lead to challenges in the lives of these individuals. The issue arising with the rise in the half-poverty rate is the government's difficulty in prioritizing areas that require intervention to address these problems. Consequently, an increase in the half-poverty rate can have adverse consequences. Therefore, it is necessary to categorize underemployment rate data obtained from public sources, specifically from data.go.id, using the widely recognized clustering method known as K-Means. The purpose of this categorization is to identify and classify provinces with a significant prevalence of half-poverty levels. This classification will assist the government in making informed decisions when addressing individuals who meet the half-poverty criteria. The results were obtained by grouping the data from the first to the eighteenth iteration into three categories: 'large' (C1), 'medium' (C2), and 'small' (C3) in terms of half-poverty levels. Group C1 comprises 17 provinces with a high half-poverty rate, while C2 includes only 2 provinces, and C3 covers 16 provinces with a significant half-poverty rate. Based on these findings, it is advisable for the Indonesian government to consider implementing policies aimed at reducing the poverty level by half. Priority should especially be given to the C1 group when creating employment opportunities for the province's residents
Optimalisasi Pengambilan Keputusan Melalui Analisis Trend Penjualan pada Bisnis Retail Menggunakan Metode Least Square S Suhardjono
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 3 (2023): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i3.202

Abstract

The right business decisions are crucial in the business world to ensure business continuity and increase profitability. One important factor in making business decisions is sales sales. Businesses need accurate trading trade orders to fill inventory, improve sales performance, and maximize profits. This research case study focuses on the medical device retail business of CV. Independent Lakshmi. The company faces problems in replenishing inventory due to variable demand. The research objective is to analyze sales trends and customer buying interest using the least square method. The results showed that forecasting calculations yielded a MAPE value of 1% and there were sales trend analysis results, namely a total trend increase of 29.04% for karcher goods so that sales trend analysis could be contributed to the research site. Based on the results of system testing using Blackbox Testing, the results show that the system functionality is appropriate and valid.
ANALISIS UX DAN UI WEBSITE ASPIRASI FRAKSI PKS BERBASIS MODEL KEBERHASILAN SISTEM INFORMASI DELONE & MCLEAN Hilmiah; Ainayah Al Fathiyyah; Suhardjono Suhardjono
Jurnal Riset Sistem Informasi Vol. 2 No. 3 (2025): Juli : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/6tej5n67

Abstract

Ainayah Al Fathiyyah (19210306) Hilmiah (1921030721), UX and UI Analysis of the PKS Faction Aspiration Website Based on the Delone & Mclean Information System Success Model The Aspirasi Information System Website of the Prosperous Justice Party (PKS) is a digital platform designed to facilitate public participation in conveying aspirations directly to legislative representatives. The success of such an information system is not solely determined by its technical functionality but also by its visual quality, ease of user interaction, and perceived security. This study aims to analyze the influence of website quality, features, and security on user satisfaction, using the DeLone and McLean Information System Success Model combined with User Experience (UX) and User Interface (UI) principles.This research applies a quantitative approach through a survey method by distributing questionnaires to respondents who have used the PKS aspiration website. The research instrument is based on a Likert scale and includes several independent variables such as design and interface, features and functionality, and information and accessibility, which are analyzed for their influence on the dependent variable, namely user satisfaction. The data analysis techniques used include validity testing, reliability testing, descriptive statistics, and multiple linear regression analysis. This study is expected to contribute to the evaluation and development of public digital information systems, particularly in the context of political aspiration services that emphasize transparency, participation, and user comfort in online interactions.
PENERAPAN ALGORITMA KLASIFIKASI C4.5 REVIEW PELANGGAN DALAM BERTRANSAKSI PADA PT. DAPOER MAMIH Wahana Indra Komala; Andri Yansah; Resti Pebrina; Suhardjono Suhardjono
Jurnal Riset Sistem Informasi Vol. 3 No. 1 (2026): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/p6wz6n47

Abstract

Wahana Indra Komala (19242542), Andri Yansah (19242561), Resti Pebrina (19242563), Implementation of C4.5 Classification Algorithm Customer Review in Transactions at PT. Dapoer Mamih Dapoer Mamih is a company engaged in the culinary field and is committed to providing the best service to its customers. One way to radiate service quality and customer satisfaction is by analyzing customer Reviews. This study aims to classify customer Reviews in transactions using the C4.5 classification algorithm. The C4.5 algorithm was chosen because of its ability to form an effective Decision Tree in handling categorical and numeric data and handling missing data values. The data used in this study came from customer Reviews collected by the company. The analysis process begins with the data preprocessing stage, attribute selection, model training, and evaluation of model classification performance. The results of the study show that the C4.5 algorithm is able to group customer Reviews into certain categories such as positive, neutral, and negative with an adequate level of accuracy. These findings can be the basis for companies to make strategic decisions in improving service quality and customer experience. Keywords: Classification; C4.5; Customer Reviews; Decision Trees; Data Mining.
Optimalisasi Prediksi Dalam Kelulusan Berbasis Deep Learning: Perbandingan Kinerja Multi-Layer Perceptron dan Deep Neural Network Dewi, Yumi Novita; Iqbal, Muhammad; Lisnawanty; Maisyaroh; Suhardjono
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.30756

Abstract

Predicting on-time graduation is one of the significant challenges in education, aiming to model the factors influencing academic success. This study aims to compare the performance of two Deep Learning algorithms, namely Deep Neural Networks (DNN) and Multi-Layer Perceptron (MLP), in predicting on-time graduation. The methodology used involves evaluating both algorithms with various performance metrics, including Recall, Accuracy, Precision, AUC, MCC, and Cohen Kappa. The results show that DNN performs better in terms of Recall (0.9766), indicating its ability to capture most of the students who graduate on time, although its AUC (0.8625) and Precision (0.8803) are lower compared to MLP. On the other hand, MLP excels in Accuracy (0.8812) and Precision (0.9037), providing more stable results for MCC and Cohen Kappa, demonstrating a better balance in predicting students who graduate on time and those who do not. Overall, while DNN is more sensitive in capturing students who graduate on time, MLP performs better in terms of balance between accuracy and minimizing prediction errors. This study suggests using MLP if the primary priority is accuracy and prediction stability, while DNN is more suitable when the main focus is capturing as many students as possible who graduate on time.
Model Prediktif Keterlambatan Pembayaran Mahasiswa Berbasis Seleksi Fitur dengan Particle Swarm Optimization Desvia, Yessica Fara; Suharjanti; Suhardjono; Irmawati Carolina; Resti Lia Andharsaputri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.8973

Abstract

Keterlambatan pembayaran biaya kuliah menjadi salah satu permasalahan krusial di perguruan tinggi swasta yang dapat berdampak pada risiko akademik, seperti cuti atau putus studi. Penelitian ini diarahkan untuk mengembangkan model prediktif dalam mengidentifikasi keterlambatan pembayaran oleh mahasiswa, dengan memanfaatkan algoritma klasifikasi Decision Tree dan Random Tree, serta menerapkan metode Particle Swarm Optimization (PSO) untuk proses seleksi fitur. Data yang digunakan dalam penelitian ini mencakup 15.697 mahasiswa, masing-masing memiliki enam atribut sebagai variabel prediktor serta satu atribut target yang menunjukkan status mahasiswa, yaitu aktif atau cuti. Tahapan penelitian mencakup pengumpulan data, pra-pemrosesan, klasifikasi, seleksi fitur, dan evaluasi model dilakukan dengan menggunakan metrik akurasi, serta kurva ROC dan nilai AUC. Hasil penelitian menunjukkan akurasi model mencapai 98,83%, dengan peningkatan signifikan AUC pada Random Tree dari 0,632 menjadi 0,825 setelah seleksi fitur menggunakan PSO. Temuan ini menunjukkan bahwa PSO efektif dalam meningkatkan performa model klasifikasi dan mengurangi kompleksitas fitur yang tidak relevan. Sistem prediktif yang dihasilkan dapat membantu institusi pendidikan dalam melakukan deteksi dini mahasiswa berisiko menunggak, sehingga memungkinkan pengambilan tindakan preventif dan intervensi lebih tepat sasaran untuk mendukung keberlangsungan akademik mahasiswa.
Co-Authors Abdul Hamid Abdul Hamid Abdul Hamid ADE RISNA SARI Adjat Sudradjat Ainayah Al Fathiyyah Andri Yansah Arman Syah Putra Arman Syah Putra Arman Syah Putra Cakranegara, Pandu Adi Desvia, Yessica Fara Dewi Yuliandari Ganda Wijaya Ganda Wijaya, Ganda Gilang Purnama Adji Hafis Nurdin Hari Sugiarto - UBSI Hendra Hendra Herlina, Maria Hermanto Hermanto Hermanto Hilmiah Indah Ariyati Irmawati Carolina ispandi ispandi Istiqomah Sumadikarta Jajang Jaya Purnama Lisnawanty Maisyaroh Mochammad Abdul Azis Muhammad Faisal Muhammad Hilman Fakhriza Muhammad Iqbal Muhammad Ryansyah Nanny Mayasari Nurul Aisyah Nurul Aisyah Nurul Aisyah Olivia, Shinta Parulian, Dudi Priyono Priyono Priyono Priyono Resti Lia Andharsaputri Resti Pebrina Ridwansyah Ridwansyah Ridwansyah Rino Ramadan Rio Wirawan Rohimah, Luthfia Rudy Max Damara Gugat Sri Iswiyanti, Agus suharjanti Suryadhitia, Rachmat Syah Putra, Arman V.H. Valentino Wahana Indra Komala Wahid, Bilal Abdul Yumi Novita Dewi